Intro to {purrr}

class: center, middle, inverse, title-slide

# Intro to {purrr}
## And a more explicit description of functional programming
### Daniel Anderson
### Week 3, Class 1

---

layout: true

---
# Agenda
* Thinking more about functional programming

+ A small example

* Introduce you to {purrr} and contrast it with the base functions we learned last week

---
# Learning objectives
* Understand how `purrr::map` relates to `lapply` and `for` loops

* Understand the six basic variants of `purrr::map`, when they should be used,
and when they will fail

* Understand what functional programming is, and how `{purrr}` can help
facilitate the process

---
class: inverse-blue middle
# Functional Programming

---
# What is FP?
> decomposing a big problem into smaller pieces, then solving each piece with a 
function or combination of functions

\- [Adv-R](https://adv-r.hadley.nz/fp.html)

---
# Example
### Calculate top mpg manufactures

* First, we'll subset the data to 4 cylinders. This will be the dataset we'll
solve the problem on:

```r
library(tidyverse)
four_cyl <- filter(mpg, cyl == 4)
```

---
* Next, we'll filter for cases where the city miles per gallon is in the top 10% (i.e.,greater than or equal to the 90th percentile).

```r
ninety <- four_cyl %>%
	filter(cty >= quantile(cty, probs = 0.9))
ninety
```

```
## # A tibble: 10 x 11
##    manufacturer model      displ  year   cyl trans      drv     cty   hwy fl   
##    <chr>        <chr>      <dbl> <int> <int> <chr>      <chr> <int> <int> <chr>
##  1 honda        civic        1.6  1999     4 manual(m5) f        28    33 r    
##  2 honda        civic        1.6  1999     4 manual(m5) f        25    32 r    
##  3 honda        civic        1.8  2008     4 manual(m5) f        26    34 r    
##  4 honda        civic        1.8  2008     4 auto(l5)   f        25    36 r    
##  5 toyota       corolla      1.8  1999     4 manual(m5) f        26    35 r    
##  6 toyota       corolla      1.8  2008     4 manual(m5) f        28    37 r    
##  7 toyota       corolla      1.8  2008     4 auto(l4)   f        26    35 r    
##  8 volkswagen   jetta        1.9  1999     4 manual(m5) f        33    44 d    
##  9 volkswagen   new beetle   1.9  1999     4 manual(m5) f        35    44 d    
## 10 volkswagen   new beetle   1.9  1999     4 auto(l4)   f        29    41 d    
## # … with 1 more variable: class <chr>
```

---
* Now count the unique occurrences for each manufacturer,
manufacturer/model, and class

```r
count_mfr <- count(ninety, manufacturer)
count_model <- count(ninety, manufacturer, model)
count_class <- count(ninety, class)
```

---
* Produce a plot for each

```r
plot_mfr <- 
	ggplot(count_mfr, aes(fct_reorder(manufacturer, -n), n)) +
		geom_col(aes(fill = manufacturer)) +
		scale_fill_brewer(palette = "Set3") +
		labs(title = "Manufacturers",
		     x = "",
		     y = "") +
		guides(fill = "none")

plot_car <- count_model %>%
	unite(car, manufacturer, model, sep = " ") %>%
	ggplot(aes(fct_reorder(car, -n), n)) +
		geom_col(aes(fill = car)) +
		scale_fill_brewer(palette = "Set3") +
		labs(title = "Top 10% of city mpg",
		     subtitle = "Car frequency",
		     x = "",
		     y = "") +
		guides(fill = "none")
```

---

```r
plot_class <- 
  ggplot(count_class, aes(fct_reorder(class, -n), n)) +
		geom_col(aes(fill = class)) +
		scale_fill_brewer(palette = "Set3") +
		labs(title = "Car Class",
		     x = "", 
		     y = "") +
		guides(fill = "none")
```

---
# Assemble the plots

```r
library(patchwork)
plot_car / (plot_mfr + plot_class)
```

![](w3p1_files/figure-html/patchwork-1.png)

---
class: inverse-red middle

# Functional Programming Version
### At least in spirit

---
# Filter all

```r
by_cyl <- split(mpg, mpg$cyl)
top_10 <- lapply(by_cyl, function(x) {
	filter(x, cty >= quantile(cty, probs = 0.9))
})
str(top_10)
```

```
## List of 4
##  $ 4: tibble[,11] [10 × 11] (S3: tbl_df/tbl/data.frame)
##   ..$ manufacturer: chr [1:10] "honda" "honda" "honda" "honda" ...
##   ..$ model       : chr [1:10] "civic" "civic" "civic" "civic" ...
##   ..$ displ       : num [1:10] 1.6 1.6 1.8 1.8 1.8 1.8 1.8 1.9 1.9 1.9
##   ..$ year        : int [1:10] 1999 1999 2008 2008 1999 2008 2008 1999 1999 1999
##   ..$ cyl         : int [1:10] 4 4 4 4 4 4 4 4 4 4
##   ..$ trans       : chr [1:10] "manual(m5)" "manual(m5)" "manual(m5)" "auto(l5)" ...
##   ..$ drv         : chr [1:10] "f" "f" "f" "f" ...
##   ..$ cty         : int [1:10] 28 25 26 25 26 28 26 33 35 29
##   ..$ hwy         : int [1:10] 33 32 34 36 35 37 35 44 44 41
##   ..$ fl          : chr [1:10] "r" "r" "r" "r" ...
##   ..$ class       : chr [1:10] "subcompact" "subcompact" "subcompact" "subcompact" ...
##  $ 5: tibble[,11] [2 × 11] (S3: tbl_df/tbl/data.frame)
##   ..$ manufacturer: chr [1:2] "volkswagen" "volkswagen"
##   ..$ model       : chr [1:2] "jetta" "jetta"
##   ..$ displ       : num [1:2] 2.5 2.5
##   ..$ year        : int [1:2] 2008 2008
##   ..$ cyl         : int [1:2] 5 5
##   ..$ trans       : chr [1:2] "auto(s6)" "manual(m5)"
##   ..$ drv         : chr [1:2] "f" "f"
##   ..$ cty         : int [1:2] 21 21
##   ..$ hwy         : int [1:2] 29 29
##   ..$ fl          : chr [1:2] "r" "r"
##   ..$ class       : chr [1:2] "compact" "compact"
##  $ 6: tibble[,11] [23 × 11] (S3: tbl_df/tbl/data.frame)
##   ..$ manufacturer: chr [1:23] "audi" "audi" "chevrolet" "chevrolet" ...
##   ..$ model       : chr [1:23] "a4" "a4" "malibu" "malibu" ...
##   ..$ displ       : num [1:23] 2.8 3.1 3.1 3.5 3.8 3.8 2.5 2.5 3.3 3.5 ...
##   ..$ year        : int [1:23] 1999 2008 1999 2008 1999 1999 1999 1999 2008 2008 ...
##   ..$ cyl         : int [1:23] 6 6 6 6 6 6 6 6 6 6 ...
##   ..$ trans       : chr [1:23] "manual(m5)" "auto(av)" "auto(l4)" "auto(l4)" ...
##   ..$ drv         : chr [1:23] "f" "f" "f" "f" ...
##   ..$ cty         : int [1:23] 18 18 18 18 18 18 18 18 19 19 ...
##   ..$ hwy         : int [1:23] 26 27 26 29 26 25 26 26 28 27 ...
##   ..$ fl          : chr [1:23] "p" "p" "r" "r" ...
##   ..$ class       : chr [1:23] "compact" "compact" "midsize" "midsize" ...
##  $ 8: tibble[,11] [11 × 11] (S3: tbl_df/tbl/data.frame)
##   ..$ manufacturer: chr [1:11] "audi" "chevrolet" "chevrolet" "chevrolet" ...
##   ..$ model       : chr [1:11] "a6 quattro" "corvette" "corvette" "corvette" ...
##   ..$ displ       : num [1:11] 4.2 5.7 5.7 6.2 6.2 7 4.6 4.6 4.6 4.6 ...
##   ..$ year        : int [1:11] 2008 1999 1999 2008 2008 2008 1999 1999 2008 2008 ...
##   ..$ cyl         : int [1:11] 8 8 8 8 8 8 8 8 8 8 ...
##   ..$ trans       : chr [1:11] "auto(s6)" "manual(m6)" "auto(l4)" "manual(m6)" ...
##   ..$ drv         : chr [1:11] "4" "r" "r" "r" ...
##   ..$ cty         : int [1:11] 16 16 15 16 15 15 15 15 15 15 ...
##   ..$ hwy         : int [1:11] 23 26 23 26 25 24 21 22 23 22 ...
##   ..$ fl          : chr [1:11] "p" "p" "p" "p" ...
##   ..$ class       : chr [1:11] "midsize" "2seater" "2seater" "2seater" ...
```

---
# All counts

```r
counts <- lapply(top_10, function(x) {
	count_manufacturer <- count(x, manufacturer)
	count_class <- count(x, class)

count_model <- count(x, manufacturer, model) %>%
		unite(car, manufacturer, model, sep = " ")

return(list(mfr = count_manufacturer, 
	            car = count_model, 
	            class = count_class))
})
counts
```

```
## $`4`
## $`4`$mfr
## # A tibble: 3 x 2
##   manufacturer     n
##   <chr>        <int>
## 1 honda            4
## 2 toyota           3
## 3 volkswagen       3
## 
## $`4`$car
## # A tibble: 4 x 2
##   car                       n
##   <chr>                 <int>
## 1 honda civic               4
## 2 toyota corolla            3
## 3 volkswagen jetta          1
## 4 volkswagen new beetle     2
## 
## $`4`$class
## # A tibble: 2 x 2
##   class          n
##   <chr>      <int>
## 1 compact        4
## 2 subcompact     6
## 
## 
## $`5`
## $`5`$mfr
## # A tibble: 1 x 2
##   manufacturer     n
##   <chr>        <int>
## 1 volkswagen       2
## 
## $`5`$car
## # A tibble: 1 x 2
##   car                  n
##   <chr>            <int>
## 1 volkswagen jetta     2
## 
## $`5`$class
## # A tibble: 1 x 2
##   class       n
##   <chr>   <int>
## 1 compact     2
## 
## 
## $`6`
## $`6`$mfr
## # A tibble: 8 x 2
##   manufacturer     n
##   <chr>        <int>
## 1 audi             2
## 2 chevrolet        2
## 3 ford             2
## 4 hyundai          3
## 5 nissan           5
## 6 pontiac          2
## 7 toyota           6
## 8 volkswagen       1
## 
## $`6`$car
## # A tibble: 10 x 2
##    car                     n
##    <chr>               <int>
##  1 audi a4                 2
##  2 chevrolet malibu        2
##  3 ford mustang            2
##  4 hyundai sonata          3
##  5 nissan altima           2
##  6 nissan maxima           3
##  7 pontiac grand prix      2
##  8 toyota camry            3
##  9 toyota camry solara     3
## 10 volkswagen passat       1
## 
## $`6`$class
## # A tibble: 3 x 2
##   class          n
##   <chr>      <int>
## 1 compact        5
## 2 midsize       16
## 3 subcompact     2
## 
## 
## $`8`
## $`8`$mfr
## # A tibble: 4 x 2
##   manufacturer     n
##   <chr>        <int>
## 1 audi             1
## 2 chevrolet        5
## 3 ford             4
## 4 pontiac          1
## 
## $`8`$car
## # A tibble: 4 x 2
##   car                    n
##   <chr>              <int>
## 1 audi a6 quattro        1
## 2 chevrolet corvette     5
## 3 ford mustang           4
## 4 pontiac grand prix     1
## 
## $`8`$class
## # A tibble: 3 x 2
##   class          n
##   <chr>      <int>
## 1 2seater        5
## 2 midsize        2
## 3 subcompact     4
```

---
# Plots
### Let's write a couple functions
We'll mostly ignore how for now.

```r
counts_plot <- function(counts_df) {
  var <- names(counts_df)[1]
	
  p <- ggplot(counts_df, aes(fct_reorder(!!sym(var), -n), n)) +
		geom_col(aes(fill = !!sym(var))) +
		scale_fill_brewer(palette = "Set3") +
		labs(title = stringr::str_to_title(var),
		     x = "",
		     y = "") +
		guides(fill = "none")

if(var == "car") {
		p <- p + labs(title = "Top 10% of city mpg",
		              subtitle = var)
	}
 p
}
```

---
# Test it

```r
counts_plot(counts[["4"]]$mfr)
```

![](w3p1_files/figure-html/indiv_plot1-1.png)

---

```r
counts_plot(counts[["8"]]$car)
```

![](w3p1_files/figure-html/indiv_plot2-1.png)

---

```r
counts_plot(counts[["6"]]$class)	
```

![](w3p1_files/figure-html/indiv_plot3-1.png)

---
# Compile plots function

```r
full_plot <- function(l) {
	counts_plot(l[["car"]]) / (
	  counts_plot(l[["mfr"]]) +
	  counts_plot(l[["class"]])
	)
}
```

---
# Test it

```r
full_plot(counts[[1]])
```

![](w3p1_files/figure-html/full_plot-test-1.png)

---
# Finish up

```r
plots <- lapply(counts, full_plot)
```

---

```r
plots[[1]]
```

![](w3p1_files/figure-html/p1-1.png)

---

```r
plots[[2]]
```

![](w3p1_files/figure-html/p2-1.png)

---

```r
plots[[3]]
```

![](w3p1_files/figure-html/p3-1.png)

---

```r
plots[[4]]
```

![](w3p1_files/figure-html/p4-1.png)

---
class: inverse-blue middle

# {purrr}

---
# functionals

> a function that takes a function as input and returns a vector as output.

- What does this mean?

---
# `purrr::map`

```r
library(purrr) # loaded automatically by tidyverse
map(1:3, rnorm)
```

```
## [[1]]
## [1] -0.4482679
## 
## [[2]]
## [1] -0.173540  0.380198
## 
## [[3]]
## [1]  1.0516711 -0.3236391 -0.8136803
```

---
background-image:url(https://d33wubrfki0l68.cloudfront.net/f0494d020aa517ae7b1011cea4c4a9f21702df8b/2577b/diagrams/functionals/map.png)
background-size:contain
# Graphically

---
# Comparison to `base::lapply`

.pull-left[
### lapply

```r
lapply(1:3, rnorm)
```

```
## [[1]]
## [1] -1.865053
## 
## [[2]]
## [1] -1.4890407 -0.7752085
## 
## [[3]]
## [1] -2.4288944  0.7203176 -1.0228311
```
]

.pull-right[
### map

```r
map(1:3, rnorm)
```

```
## [[1]]
## [1] -1.088205
## 
## [[2]]
## [1]  0.6405202 -0.6947191
## 
## [[3]]
## [1] -0.09712152  0.57064072  1.63741148
```
]

side note: What exactly is going on here?

---
> The base equivalent to `map()` is `lapply()`. The only difference is that `lapply()` does not support the helpers that you’ll learn about (next), so if you’re only using `map()` from {purrr}, you can skip the additional dependency and use `lapply()` directly.

\- [Adv R](https://adv-r.hadley.nz/functionals.html)

---
# Equivalents

The following are equivalent

```r
map(mtcars, function(x) length(unique(x)))

lapply(mtcars, function(x) length(unique(x)))
```

--
{purrr} also allows  you to specify anonymous functions more succinctly using the formula interface

```r
map(mtcars, ~length(unique(.x)))
```

```
## $mpg
## [1] 25
## 
## $cyl
## [1] 3
## 
## $disp
## [1] 27
## 
## $hp
## [1] 22
## 
## $drat
## [1] 22
## 
## $wt
## [1] 29
## 
## $qsec
## [1] 30
## 
## $vs
## [1] 2
## 
## $am
## [1] 2
## 
## $gear
## [1] 3
## 
## $carb
## [1] 6
```

---
# Extracting elements

```r
l <- list(
  list(-1, x = 1, y = c(2), z = "a"),
  list(-2, x = 4, y = c(5, 6), z = "b"),
  list(-3, x = 8, y = c(9, 10, 11))
)
```

--
### Extract second element from each

```r
map(l, 2)
```

```
## [[1]]
## [1] 1
## 
## [[2]]
## [1] 4
## 
## [[3]]
## [1] 8
```

---
### Doesn't work for `lapply`

```r
lapply(l, 2)
```

```
## Error in match.fun(FUN): '2' is not a function, character or symbol
```

--
Instead, you have to apply an anoymous function

```r
lapply(l, function(x) x[[2]])
```

```
## [[1]]
## [1] 1
## 
## [[2]]
## [1] 4
## 
## [[3]]
## [1] 8
```

---
Alternatively the following is also the same

```r
lapply(l, `[[`, 2)
```

```
## [[1]]
## [1] 1
## 
## [[2]]
## [1] 4
## 
## [[3]]
## [1] 8
```

---
# Extract by name

```r
map(l, "y")
```

```
## [[1]]
## [1] 2
## 
## [[2]]
## [1] 5 6
## 
## [[3]]
## [1]  9 10 11
```

---
# Multiple arguments

```r
map(l, list("y", 1))
```

```
## [[1]]
## [1] 2
## 
## [[2]]
## [1] 5
## 
## [[3]]
## [1] 9
```

---
class:inverse-red middle

# {purrr} variants

---
# Return a vector

* `map_dbl`
* `map_int`
* `map_char`
* `map_lgl`

---

.pull-left[

```r
str(l)
```

```
## List of 3
##  $ :List of 4
##   ..$  : num -1
##   ..$ x: num 1
##   ..$ y: num 2
##   ..$ z: chr "a"
##  $ :List of 4
##   ..$  : num -2
##   ..$ x: num 4
##   ..$ y: num [1:2] 5 6
##   ..$ z: chr "b"
##  $ :List of 3
##   ..$  : num -3
##   ..$ x: num 8
##   ..$ y: num [1:3] 9 10 11
```
]

.pull-right[

```r
map_dbl(l, "x")
```

```
## [1] 1 4 8
```

```r
map_dbl(l, 1)
```

```
## [1] -1 -2 -3
```
]

---
# Type match

* Coercion will occur if you request a different type

```r
map_chr(l, "x")
```

```
## [1] "1.000000" "4.000000" "8.000000"
```

--
* You'll get an error if element doesn't exist

```r
map_chr(l, "z")
```

```
## Error: Result 3 must be a single string, not NULL of length 0
```

---
* Unless you set a default value

```r
map_chr(l, "z", .default = NA_character_)
```

```
## [1] "a" "b" NA
```

---
# Quick note: missing values
* In the prior case, specifying `NA` would work, instead of `NA_character_`

--
* Generally, I think it's better to specify the type.

--
* **General programming rule:** The more strict the better

--
* Because (base) R likes to be inconsistent, here are the `NA` types

.pull-left[

| Type | NA value|
|:-----|:-------:|
| character | NA\_character\_ |
| integer   | NA\_integer\_ |
| double    | NA\_real\_ |
| logical   | NA (see [here](https://stackoverflow.com/questions/19564748/why-is-there-no-na-logical)) |
]

.pull-right[

```r
typeof(NA)
```

```
## [1] "logical"
```
]

---
# Some examples
### Please follow along

```r
econ <- economics %>%
	mutate(year = lubridate::year(date))
econ
```

```
## # A tibble: 574 x 7
##    date           pce    pop psavert  uempmed unemploy  year
##    <date>       <dbl>  <dbl>   <dbl>    <dbl>    <dbl> <dbl>
##  1 1967-07-01 506.7   198712    12.6 4.5          2944  1967
##  2 1967-08-01 509.8   198911    12.6 4.7          2945  1967
##  3 1967-09-01 515.6   199113    11.9 4.600000     2958  1967
##  4 1967-10-01 512.2   199311    12.9 4.9          3143  1967
##  5 1967-11-01 517.4   199498    12.8 4.7          3066  1967
##  6 1967-12-01 525.1   199657    11.8 4.8          3018  1967
##  7 1968-01-01 530.9   199808    11.7 5.100000     2878  1968
##  8 1968-02-01 533.6   199920    12.3 4.5          3001  1968
##  9 1968-03-01 544.300 200056    11.7 4.100000     2877  1968
## 10 1968-04-01 544     200208    12.3 4.600000     2709  1968
## # … with 564 more rows
```

---
# by_year

```r
by_year <- split(econ, econ$year)
str(by_year)
```

```
## List of 49
##  $ 1967: tibble[,7] [6 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:6], format: "1967-07-01" "1967-08-01" ...
##   ..$ pce     : num [1:6] 507 510 516 512 517 ...
##   ..$ pop     : num [1:6] 198712 198911 199113 199311 199498 ...
##   ..$ psavert : num [1:6] 12.6 12.6 11.9 12.9 12.8 11.8
##   ..$ uempmed : num [1:6] 4.5 4.7 4.6 4.9 4.7 4.8
##   ..$ unemploy: num [1:6] 2944 2945 2958 3143 3066 ...
##   ..$ year    : num [1:6] 1967 1967 1967 1967 1967 ...
##  $ 1968: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1968-01-01" "1968-02-01" ...
##   ..$ pce     : num [1:12] 531 534 544 544 550 ...
##   ..$ pop     : num [1:12] 2e+05 2e+05 2e+05 2e+05 2e+05 ...
##   ..$ psavert : num [1:12] 11.7 12.3 11.7 12.3 12 11.7 10.7 10.5 10.6 10.8 ...
##   ..$ uempmed : num [1:12] 5.1 4.5 4.1 4.6 4.4 4.4 4.5 4.2 4.6 4.8 ...
##   ..$ unemploy: num [1:12] 2878 3001 2877 2709 2740 ...
##   ..$ year    : num [1:12] 1968 1968 1968 1968 1968 ...
##  $ 1969: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1969-01-01" "1969-02-01" ...
##   ..$ pce     : num [1:12] 584 589 589 594 600 ...
##   ..$ pop     : num [1:12] 201760 201881 202023 202161 202331 ...
##   ..$ psavert : num [1:12] 10.3 9.7 10.2 9.7 10.1 11.1 11.8 11.5 11.6 11.4 ...
##   ..$ uempmed : num [1:12] 4.4 4.9 4 4 4.2 4.4 4.4 4.4 4.7 4.5 ...
##   ..$ unemploy: num [1:12] 2718 2692 2712 2758 2713 ...
##   ..$ year    : num [1:12] 1969 1969 1969 1969 1969 ...
##  $ 1970: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1970-01-01" "1970-02-01" ...
##   ..$ pce     : num [1:12] 629 634 632 636 642 ...
##   ..$ pop     : num [1:12] 203849 204008 204156 204401 204607 ...
##   ..$ psavert : num [1:12] 11.8 11.7 12.4 13.3 12.4 12.3 13.5 13.4 12.9 13.1 ...
##   ..$ uempmed : num [1:12] 4.6 4.5 4.6 4.1 4.7 4.9 5.1 5.4 5.2 5.2 ...
##   ..$ unemploy: num [1:12] 3201 3453 3635 3797 3919 ...
##   ..$ year    : num [1:12] 1970 1970 1970 1970 1970 1970 1970 1970 1970 1970 ...
##  $ 1971: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1971-01-01" "1971-02-01" ...
##   ..$ pce     : num [1:12] 676 679 682 689 691 ...
##   ..$ pop     : num [1:12] 206466 206668 206855 207065 207260 ...
##   ..$ psavert : num [1:12] 13.3 13.3 13.5 13.2 13.6 14.7 13.8 13.6 13.3 13.3 ...
##   ..$ uempmed : num [1:12] 6.2 6.3 6.4 6.5 6.7 5.7 6.2 6.4 5.8 6.5 ...
##   ..$ unemploy: num [1:12] 4986 4903 4987 4959 4996 ...
##   ..$ year    : num [1:12] 1971 1971 1971 1971 1971 ...
##  $ 1972: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1972-01-01" "1972-02-01" ...
##   ..$ pce     : num [1:12] 732 736 749 752 758 ...
##   ..$ pop     : num [1:12] 208917 209061 209212 209386 209545 ...
##   ..$ psavert : num [1:12] 12.5 12.8 11.8 11.5 11.7 11.7 11.7 12 12.2 13 ...
##   ..$ uempmed : num [1:12] 6.2 6.6 6.6 6.7 6.6 5.4 6.1 6 5.6 5.7 ...
##   ..$ unemploy: num [1:12] 5019 4928 5038 4959 4922 ...
##   ..$ year    : num [1:12] 1972 1972 1972 1972 1972 ...
##  $ 1973: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1973-01-01" "1973-02-01" ...
##   ..$ pce     : num [1:12] 816 826 833 836 842 ...
##   ..$ pop     : num [1:12] 210985 211120 211254 211420 211577 ...
##   ..$ psavert : num [1:12] 12.4 12.5 12.7 13.2 13.2 13.6 13.2 13.9 13.1 14.4 ...
##   ..$ uempmed : num [1:12] 5.7 5.2 5.5 5 4.9 5 5.2 4.9 5.4 5.5 ...
##   ..$ unemploy: num [1:12] 4326 4452 4394 4459 4329 ...
##   ..$ year    : num [1:12] 1973 1973 1973 1973 1973 ...
##  $ 1974: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1974-01-01" "1974-02-01" ...
##   ..$ pce     : num [1:12] 884 890 901 911 922 ...
##   ..$ pop     : num [1:12] 212932 213074 213211 213361 213513 ...
##   ..$ psavert : num [1:12] 14.3 14.2 13.4 13.1 12.8 12.8 12.8 12.1 12.9 13.4 ...
##   ..$ uempmed : num [1:12] 5 5.1 4.8 5 4.6 5.3 5.7 5 5.3 5.5 ...
##   ..$ unemploy: num [1:12] 4644 4731 4634 4618 4705 ...
##   ..$ year    : num [1:12] 1974 1974 1974 1974 1974 ...
##  $ 1975: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1975-01-01" "1975-02-01" ...
##   ..$ pce     : num [1:12] 976 989 991 995 1019 ...
##   ..$ pop     : num [1:12] 214931 215065 215198 215353 215523 ...
##   ..$ psavert : num [1:12] 13.2 12.5 12.7 14.2 17.3 14.3 12.6 13 13 13.4 ...
##   ..$ uempmed : num [1:12] 6.3 7.1 7.2 8.7 9.4 8.8 8.6 9.2 9.2 8.6 ...
##   ..$ unemploy: num [1:12] 7501 7520 7978 8210 8433 ...
##   ..$ year    : num [1:12] 1975 1975 1975 1975 1975 ...
##  $ 1976: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1976-01-01" "1976-02-01" ...
##   ..$ pce     : num [1:12] 1107 1108 1115 1125 1123 ...
##   ..$ pop     : num [1:12] 217095 217249 217381 217528 217685 ...
##   ..$ psavert : num [1:12] 11.7 12.3 12.2 11.7 12.3 11.4 11.7 11.7 11.4 11.1 ...
##   ..$ uempmed : num [1:12] 9 8.2 8.7 8.2 8.3 7.8 7.7 7.9 7.8 7.7 ...
##   ..$ unemploy: num [1:12] 7534 7326 7230 7330 7053 ...
##   ..$ year    : num [1:12] 1976 1976 1976 1976 1976 ...
##  $ 1977: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1977-01-01" "1977-02-01" ...
##   ..$ pce     : num [1:12] 1215 1231 1238 1247 1257 ...
##   ..$ pop     : num [1:12] 219179 219344 219504 219684 219859 ...
##   ..$ psavert : num [1:12] 10.6 9.3 10.5 10.5 10.3 10.6 10.5 10.9 11.1 11 ...
##   ..$ uempmed : num [1:12] 7.5 7.2 7.2 7.3 7.9 6.2 7.1 7 6.7 6.9 ...
##   ..$ unemploy: num [1:12] 7280 7443 7307 7059 6911 ...
##   ..$ year    : num [1:12] 1977 1977 1977 1977 1977 ...
##  $ 1978: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1978-01-01" "1978-02-01" ...
##   ..$ pce     : num [1:12] 1330 1355 1378 1396 1412 ...
##   ..$ pop     : num [1:12] 221477 221629 221792 221991 222176 ...
##   ..$ psavert : num [1:12] 11.9 11.1 11 10.8 10.3 10 10.9 10.5 10.6 10.7 ...
##   ..$ uempmed : num [1:12] 6.5 6.7 6.2 6.1 5.7 6 5.8 5.8 5.6 5.9 ...
##   ..$ unemploy: num [1:12] 6489 6318 6337 6180 6127 ...
##   ..$ year    : num [1:12] 1978 1978 1978 1978 1978 ...
##  $ 1979: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1979-01-01" "1979-02-01" ...
##   ..$ pce     : num [1:12] 1502 1518 1531 1538 1559 ...
##   ..$ pop     : num [1:12] 223865 224053 224235 224438 224632 ...
##   ..$ psavert : num [1:12] 11.1 11.1 11.2 11 10.3 9.9 10.6 9.7 9.4 9.7 ...
##   ..$ uempmed : num [1:12] 5.9 5.9 5.9 5.4 5.6 5.6 5.9 4.8 5.5 5.5 ...
##   ..$ unemploy: num [1:12] 6109 6173 6109 6069 5840 ...
##   ..$ year    : num [1:12] 1979 1979 1979 1979 1979 ...
##  $ 1980: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1980-01-01" "1980-02-01" ...
##   ..$ pce     : num [1:12] 1697 1701 1708 1695 1700 ...
##   ..$ pop     : num [1:12] 226451 226656 226849 227061 227251 ...
##   ..$ psavert : num [1:12] 9.9 10.1 10.2 11.3 11.4 11.2 11.3 11.3 11.7 11.3 ...
##   ..$ uempmed : num [1:12] 5.3 5.8 6 5.8 5.7 6.4 7 7.5 7.7 7.5 ...
##   ..$ unemploy: num [1:12] 6683 6702 6729 7358 7984 ...
##   ..$ year    : num [1:12] 1980 1980 1980 1980 1980 1980 1980 1980 1980 1980 ...
##  $ 1981: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1981-01-01" "1981-02-01" ...
##   ..$ pce     : num [1:12] 1870 1884 1903 1904 1914 ...
##   ..$ pop     : num [1:12] 228937 229071 229224 229403 229575 ...
##   ..$ psavert : num [1:12] 10.9 10.8 10.8 10.9 11 10.8 12.3 12 12.4 13 ...
##   ..$ uempmed : num [1:12] 7.4 7.1 7.1 7.4 6.9 6.6 7.1 7.2 6.8 6.8 ...
##   ..$ unemploy: num [1:12] 8071 8051 7982 7869 8174 ...
##   ..$ year    : num [1:12] 1981 1981 1981 1981 1981 ...
##  $ 1982: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1982-01-01" "1982-02-01" ...
##   ..$ pce     : num [1:12] 1997 2021 2024 2026 2044 ...
##   ..$ pop     : num [1:12] 231157 231313 231470 231645 231809 ...
##   ..$ psavert : num [1:12] 12.7 12.1 12.2 12.9 12.3 12.3 12.5 12.6 11.8 11.3 ...
##   ..$ uempmed : num [1:12] 7.1 7.5 7.7 8.1 8.5 9.5 8.5 8.7 9.5 9.7 ...
##   ..$ unemploy: num [1:12] 9397 9705 9895 10244 10335 ...
##   ..$ year    : num [1:12] 1982 1982 1982 1982 1982 ...
##  $ 1983: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1983-01-01" "1983-02-01" ...
##   ..$ pce     : num [1:12] 2174 2177 2203 2226 2246 ...
##   ..$ pop     : num [1:12] 233322 233473 233613 233781 233922 ...
##   ..$ psavert : num [1:12] 11.1 11.1 10.6 10.3 9.9 9.1 9.6 9.2 9.6 9.7 ...
##   ..$ uempmed : num [1:12] 11.1 9.8 10.4 10.9 12.3 11.3 10.1 9.3 9.3 9.4 ...
##   ..$ unemploy: num [1:12] 11534 11545 11408 11268 11154 ...
##   ..$ year    : num [1:12] 1983 1983 1983 1983 1983 ...
##  $ 1984: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1984-01-01" "1984-02-01" ...
##   ..$ pce     : num [1:12] 2419 2404 2432 2458 2474 ...
##   ..$ pop     : num [1:12] 235385 235527 235675 235839 235993 ...
##   ..$ psavert : num [1:12] 10 11.7 11.5 11.5 11.1 11.1 11.6 11.8 11.8 11.7 ...
##   ..$ uempmed : num [1:12] 9.1 8.3 8.3 8.2 9.1 7.5 7.5 7.3 7.6 7.2 ...
##   ..$ unemploy: num [1:12] 9008 8791 8746 8762 8456 ...
##   ..$ year    : num [1:12] 1984 1984 1984 1984 1984 ...
##  $ 1985: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1985-01-01" "1985-02-01" ...
##   ..$ pce     : num [1:12] 2619 2641 2648 2660 2696 ...
##   ..$ pop     : num [1:12] 237468 237602 237732 237900 238074 ...
##   ..$ psavert : num [1:12] 10.3 9.1 8.7 9.9 11.1 9.6 9.1 8.2 7.3 9.1 ...
##   ..$ uempmed : num [1:12] 6.8 7.1 7.1 6.9 6.9 6.6 6.9 7.1 6.9 7.1 ...
##   ..$ unemploy: num [1:12] 8423 8321 8339 8395 8302 ...
##   ..$ year    : num [1:12] 1985 1985 1985 1985 1985 ...
##  $ 1986: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1986-01-01" "1986-02-01" ...
##   ..$ pce     : num [1:12] 2827 2820 2824 2835 2858 ...
##   ..$ pop     : num [1:12] 239638 239788 239928 240094 240271 ...
##   ..$ psavert : num [1:12] 8.6 9.3 9.9 9.7 9.3 9.4 9.3 9 7.2 8.4 ...
##   ..$ uempmed : num [1:12] 6.7 6.9 6.8 6.7 6.8 7 6.9 7.1 7.4 7 ...
##   ..$ unemploy: num [1:12] 7795 8402 8383 8364 8439 ...
##   ..$ year    : num [1:12] 1986 1986 1986 1986 1986 ...
##  $ 1987: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1987-01-01" "1987-02-01" ...
##   ..$ pce     : num [1:12] 2936 3002 3013 3039 3048 ...
##   ..$ pop     : num [1:12] 241784 241930 242079 242252 242423 ...
##   ..$ psavert : num [1:12] 9.7 8.5 8.5 4.5 8.2 7.7 7.5 7.2 7.6 8.3 ...
##   ..$ uempmed : num [1:12] 6.9 6.6 6.6 7.1 6.6 6.5 6.5 6.4 6 6.3 ...
##   ..$ unemploy: num [1:12] 7892 7865 7862 7542 7574 ...
##   ..$ year    : num [1:12] 1987 1987 1987 1987 1987 ...
##  $ 1988: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1988-01-01" "1988-02-01" ...
##   ..$ pce     : num [1:12] 3214 3221 3260 3263 3294 ...
##   ..$ pop     : num [1:12] 243981 244131 244279 244445 244610 ...
##   ..$ psavert : num [1:12] 8.1 8.6 8.2 8.8 8.4 8.4 8.6 8.4 8.9 8.6 ...
##   ..$ uempmed : num [1:12] 6.2 6.3 6.4 5.9 5.9 5.8 6.1 5.9 5.7 5.6 ...
##   ..$ unemploy: num [1:12] 6953 6929 6876 6601 6779 ...
##   ..$ year    : num [1:12] 1988 1988 1988 1988 1988 ...
##  $ 1989: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1989-01-01" "1989-02-01" ...
##   ..$ pce     : num [1:12] 3484 3488 3499 3543 3552 ...
##   ..$ pop     : num [1:12] 246224 246378 246530 246721 246906 ...
##   ..$ psavert : num [1:12] 8.5 9 9.5 8.4 8.1 8.2 8.2 7.6 8.1 8.5 ...
##   ..$ uempmed : num [1:12] 5.6 5.4 5.4 5.4 5.3 5.4 5.6 5 4.9 4.9 ...
##   ..$ unemploy: num [1:12] 6682 6359 6205 6468 6375 ...
##   ..$ year    : num [1:12] 1989 1989 1989 1989 1989 ...
##  $ 1990: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1990-01-01" "1990-02-01" ...
##   ..$ pce     : num [1:12] 3731 3728 3755 3770 3776 ...
##   ..$ pop     : num [1:12] 248659 248827 249012 249306 249565 ...
##   ..$ psavert : num [1:12] 8 8.6 8.3 8.8 8.7 8.6 8.7 8.1 8.1 7.8 ...
##   ..$ uempmed : num [1:12] 5.1 5.3 5.1 4.8 5.2 5.2 5.4 5.4 5.6 5.8 ...
##   ..$ unemploy: num [1:12] 6752 6651 6598 6797 6742 ...
##   ..$ year    : num [1:12] 1990 1990 1990 1990 1990 1990 1990 1990 1990 1990 ...
##  $ 1991: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1991-01-01" "1991-02-01" ...
##   ..$ pce     : num [1:12] 3841 3867 3913 3907 3933 ...
##   ..$ pop     : num [1:12] 251889 252135 252372 252643 252913 ...
##   ..$ psavert : num [1:12] 9.3 8.8 8 8.6 8.4 8.9 8.2 8.6 8.8 9.3 ...
##   ..$ uempmed : num [1:12] 6 6.2 6.7 6.6 6.4 6.9 7 7.3 6.8 7.2 ...
##   ..$ unemploy: num [1:12] 8015 8265 8586 8439 8736 ...
##   ..$ year    : num [1:12] 1991 1991 1991 1991 1991 ...
##  $ 1992: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1992-01-01" "1992-02-01" ...
##   ..$ pce     : num [1:12] 4085 4100 4117 4132 4158 ...
##   ..$ pop     : num [1:12] 255214 255448 255703 255992 256285 ...
##   ..$ psavert : num [1:12] 9.4 9.8 9.7 9.9 9.9 10.1 9.6 9.7 8.7 8 ...
##   ..$ uempmed : num [1:12] 8.1 8.2 8.3 8.5 8.8 8.7 8.6 8.8 8.6 9 ...
##   ..$ unemploy: num [1:12] 9283 9454 9460 9415 9744 ...
##   ..$ year    : num [1:12] 1992 1992 1992 1992 1992 ...
##  $ 1993: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1993-01-01" "1993-02-01" ...
##   ..$ pce     : num [1:12] 4341 4355 4352 4393 4422 ...
##   ..$ pop     : num [1:12] 258679 258919 259152 259414 259680 ...
##   ..$ psavert : num [1:12] 8.6 8.9 8.9 8.7 8.3 7.8 7.6 7.7 6.9 6.3 ...
##   ..$ uempmed : num [1:12] 8.6 8.5 8.5 8.4 8.1 8.3 8.2 8.2 8.3 8 ...
##   ..$ unemploy: num [1:12] 9325 9183 9056 9110 9149 ...
##   ..$ year    : num [1:12] 1993 1993 1993 1993 1993 ...
##  $ 1994: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1994-01-01" "1994-02-01" ...
##   ..$ pce     : num [1:12] 4585 4633 4646 4671 4670 ...
##   ..$ pop     : num [1:12] 261919 262123 262352 262631 262877 ...
##   ..$ psavert : num [1:12] 7.1 6.5 6.8 6.4 7.6 6.9 7 6.5 6.8 7.1 ...
##   ..$ uempmed : num [1:12] 8.6 9.2 9.3 9.1 9.2 9.3 9 8.9 9.2 10 ...
##   ..$ unemploy: num [1:12] 8630 8583 8470 8331 7915 ...
##   ..$ year    : num [1:12] 1994 1994 1994 1994 1994 ...
##  $ 1995: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1995-01-01" "1995-02-01" ...
##   ..$ pce     : num [1:12] 4851 4851 4885 4890 4933 ...
##   ..$ pop     : num [1:12] 265044 265270 265495 265755 265998 ...
##   ..$ psavert : num [1:12] 7.5 7.8 7.5 6.9 7.1 6.7 7.1 6.7 6.8 7.1 ...
##   ..$ uempmed : num [1:12] 8 8.1 8.3 8.3 9.1 7.9 8.5 8.3 7.9 8.2 ...
##   ..$ unemploy: num [1:12] 7375 7187 7153 7645 7430 ...
##   ..$ year    : num [1:12] 1995 1995 1995 1995 1995 ...
##  $ 1996: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1996-01-01" "1996-02-01" ...
##   ..$ pce     : num [1:12] 5086 5133 5173 5208 5224 ...
##   ..$ pop     : num [1:12] 268151 268364 268595 268853 269108 ...
##   ..$ psavert : num [1:12] 6.7 6.7 6.6 5.7 6.7 7.1 6.7 6.6 6.7 6.4 ...
##   ..$ uempmed : num [1:12] 8.3 7.8 8.3 8.6 8.6 8.3 8.3 8.4 8.5 8.3 ...
##   ..$ unemploy: num [1:12] 7491 7313 7318 7415 7423 ...
##   ..$ year    : num [1:12] 1996 1996 1996 1996 1996 ...
##  $ 1997: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1997-01-01" "1997-02-01" ...
##   ..$ pce     : num [1:12] 5411 5434 5454 5459 5460 ...
##   ..$ pop     : num [1:12] 271360 271585 271821 272083 272342 ...
##   ..$ psavert : num [1:12] 6.2 6.2 6.4 6.5 6.8 6.6 6.1 6 6.2 6.2 ...
##   ..$ uempmed : num [1:12] 7.8 8.1 7.9 8.3 8 8 8.3 7.8 8.2 7.7 ...
##   ..$ unemploy: num [1:12] 7158 7102 7000 6873 6655 ...
##   ..$ year    : num [1:12] 1997 1997 1997 1997 1997 ...
##  $ 1998: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1998-01-01" "1998-02-01" ...
##   ..$ pce     : num [1:12] 5690 5724 5750 5788 5838 ...
##   ..$ pop     : num [1:12] 274626 274838 275047 275304 275564 ...
##   ..$ psavert : num [1:12] 7.4 7.4 7.5 7.2 6.9 6.8 6.9 6.8 6.4 6.2 ...
##   ..$ uempmed : num [1:12] 7.4 7 6.8 6.7 6 6.9 6.7 6.8 6.7 5.8 ...
##   ..$ unemploy: num [1:12] 6368 6306 6422 5941 6047 ...
##   ..$ year    : num [1:12] 1998 1998 1998 1998 1998 ...
##  $ 1999: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1999-01-01" "1999-02-01" ...
##   ..$ pce     : num [1:12] 6073 6102 6133 6196 6226 ...
##   ..$ pop     : num [1:12] 277790 277992 278198 278451 278717 ...
##   ..$ psavert : num [1:12] 6.4 6.2 5.9 5.2 4.9 4.8 4.8 4.7 4.2 4.6 ...
##   ..$ uempmed : num [1:12] 6.9 6.8 6.8 6.2 6.5 6.3 5.8 6.5 6 6.1 ...
##   ..$ unemploy: num [1:12] 5976 6111 5783 6004 5796 ...
##   ..$ year    : num [1:12] 1999 1999 1999 1999 1999 ...
##  $ 2000: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2000-01-01" "2000-02-01" ...
##   ..$ pce     : num [1:12] 6535 6620 6686 6671 6708 ...
##   ..$ pop     : num [1:12] 280976 281190 281409 281653 281877 ...
##   ..$ psavert : num [1:12] 5.4 4.8 4.5 5 4.9 4.9 5.2 5.2 4.5 4.6 ...
##   ..$ uempmed : num [1:12] 5.8 6.1 6 6.1 5.8 5.7 6 6.3 5.2 6.1 ...
##   ..$ unemploy: num [1:12] 5708 5858 5733 5481 5758 ...
##   ..$ year    : num [1:12] 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 ...
##  $ 2001: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2001-01-01" "2001-02-01" ...
##   ..$ pce     : num [1:12] 6977 6996 6988 7001 7047 ...
##   ..$ pop     : num [1:12] 283920 284137 284350 284581 284810 ...
##   ..$ psavert : num [1:12] 4.8 4.9 5.3 5 4.5 4.5 5.6 6.8 7 3.4 ...
##   ..$ uempmed : num [1:12] 5.8 6.1 6.6 5.9 6.3 6 6.8 6.9 7.2 7.3 ...
##   ..$ unemploy: num [1:12] 6023 6089 6141 6271 6226 ...
##   ..$ year    : num [1:12] 2001 2001 2001 2001 2001 ...
##  $ 2002: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2002-01-01" "2002-02-01" ...
##   ..$ pce     : num [1:12] 7174 7218 7237 7305 7283 ...
##   ..$ pop     : num [1:12] 286788 286994 287190 287397 287623 ...
##   ..$ psavert : num [1:12] 6.1 5.8 5.9 5.8 6.5 6.4 5.5 5.4 5.7 5.7 ...
##   ..$ uempmed : num [1:12] 8.4 8.3 8.4 8.9 9.5 11 8.9 9 9.5 9.6 ...
##   ..$ unemploy: num [1:12] 8182 8215 8304 8599 8399 ...
##   ..$ year    : num [1:12] 2002 2002 2002 2002 2002 ...
##  $ 2003: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2003-01-01" "2003-02-01" ...
##   ..$ pce     : num [1:12] 7533 7536 7598 7621 7628 ...
##   ..$ pop     : num [1:12] 289518 289714 289911 290125 290346 ...
##   ..$ psavert : num [1:12] 5.5 5.6 5.3 5.3 5.8 5.6 6.3 6 5.2 5.3 ...
##   ..$ uempmed : num [1:12] 9.6 9.5 9.7 10.2 9.9 11.5 10.3 10.1 10.2 10.4 ...
##   ..$ unemploy: num [1:12] 8520 8618 8588 8842 8957 ...
##   ..$ year    : num [1:12] 2003 2003 2003 2003 2003 ...
##  $ 2004: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2004-01-01" "2004-02-01" ...
##   ..$ pce     : num [1:12] 7987 8020 8076 8089 8163 ...
##   ..$ pop     : num [1:12] 292192 292368 292561 292779 292997 ...
##   ..$ psavert : num [1:12] 5 5 4.9 5.3 5.3 5.8 5.3 5.2 4.6 4.5 ...
##   ..$ uempmed : num [1:12] 10.6 10.2 10.2 9.5 9.9 11 8.9 9.2 9.6 9.5 ...
##   ..$ unemploy: num [1:12] 8370 8167 8491 8170 8212 ...
##   ..$ year    : num [1:12] 2004 2004 2004 2004 2004 ...
##  $ 2005: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2005-01-01" "2005-02-01" ...
##   ..$ pce     : num [1:12] 8470 8529 8570 8646 8644 ...
##   ..$ pop     : num [1:12] 294914 295105 295287 295490 295704 ...
##   ..$ psavert : num [1:12] 3.7 3.4 3.6 3.1 3.5 2.9 2.2 2.7 2.7 3.1 ...
##   ..$ uempmed : num [1:12] 9.4 9.2 9.3 9 9.1 9 8.8 9.2 8.4 8.6 ...
##   ..$ unemploy: num [1:12] 7784 7980 7737 7672 7651 ...
##   ..$ year    : num [1:12] 2005 2005 2005 2005 2005 ...
##  $ 2006: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2006-01-01" "2006-02-01" ...
##   ..$ pce     : num [1:12] 9060 9090 9122 9175 9215 ...
##   ..$ pop     : num [1:12] 297647 297854 298060 298281 298496 ...
##   ..$ psavert : num [1:12] 4.2 4.2 4.2 4 3.8 4 3.4 3.6 3.6 3.6 ...
##   ..$ uempmed : num [1:12] 8.6 9.1 8.7 8.4 8.5 7.3 8 8.4 8 7.9 ...
##   ..$ unemploy: num [1:12] 7064 7184 7072 7120 6980 ...
##   ..$ year    : num [1:12] 2006 2006 2006 2006 2006 ...
##  $ 2007: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2007-01-01" "2007-02-01" ...
##   ..$ pce     : num [1:12] 9516 9547 9585 9616 9651 ...
##   ..$ pop     : num [1:12] 300574 300802 301021 301254 301483 ...
##   ..$ psavert : num [1:12] 3.7 4.1 4.4 4.2 4 3.8 3.7 3.4 3.5 3.4 ...
##   ..$ uempmed : num [1:12] 8.3 8.5 9.1 8.6 8.2 7.7 8.7 8.8 8.7 8.4 ...
##   ..$ unemploy: num [1:12] 7116 6927 6731 6850 6766 ...
##   ..$ year    : num [1:12] 2007 2007 2007 2007 2007 ...
##  $ 2008: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2008-01-01" "2008-02-01" ...
##   ..$ pce     : num [1:12] 9930 9913 9959 9997 10054 ...
##   ..$ pop     : num [1:12] 303506 303711 303907 304117 304323 ...
##   ..$ psavert : num [1:12] 3.7 4.1 4 3.4 7.8 5.5 4.4 3.8 4.7 5.5 ...
##   ..$ uempmed : num [1:12] 9 8.7 8.7 9.4 7.9 9 9.7 9.7 10.2 10.4 ...
##   ..$ unemploy: num [1:12] 7685 7497 7822 7637 8395 ...
##   ..$ year    : num [1:12] 2008 2008 2008 2008 2008 ...
##  $ 2009: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2009-01-01" "2009-02-01" ...
##   ..$ pce     : num [1:12] 9784 9766 9718 9725 9749 ...
##   ..$ pop     : num [1:12] 306208 306402 306588 306787 306984 ...
##   ..$ psavert : num [1:12] 6.2 5.5 5.9 6.8 8.2 6.7 6 4.9 5.9 5.4 ...
##   ..$ uempmed : num [1:12] 10.7 11.7 12.3 13.1 14.2 17.2 16 16.3 17.8 18.9 ...
##   ..$ unemploy: num [1:12] 12058 12898 13426 13853 14499 ...
##   ..$ year    : num [1:12] 2009 2009 2009 2009 2009 ...
##  $ 2010: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2010-01-01" "2010-02-01" ...
##   ..$ pce     : num [1:12] 10002 10031 10089 10113 10131 ...
##   ..$ pop     : num [1:12] 308833 309027 309212 309191 309369 ...
##   ..$ psavert : num [1:12] 6.1 5.8 5.7 6.4 7 6.9 6.8 6.9 6.7 6.6 ...
##   ..$ uempmed : num [1:12] 20 19.9 20.4 22.1 22.3 25.2 22.3 21 20.3 21.2 ...
##   ..$ unemploy: num [1:12] 15046 15113 15202 15325 14849 ...
##   ..$ year    : num [1:12] 2010 2010 2010 2010 2010 2010 2010 2010 2010 2010 ...
##  $ 2011: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2011-01-01" "2011-02-01" ...
##   ..$ pce     : num [1:12] 10436 10470 10550 10588 10612 ...
##   ..$ pop     : num [1:12] 310961 311113 311265 311436 311607 ...
##   ..$ psavert : num [1:12] 7.4 7.6 7 6.9 6.9 7.2 7.3 7.2 6.8 6.8 ...
##   ..$ uempmed : num [1:12] 21.5 21.1 21.5 20.9 21.6 22.4 22 22.4 22 20.6 ...
##   ..$ unemploy: num [1:12] 14013 13820 13737 13957 13855 ...
##   ..$ year    : num [1:12] 2011 2011 2011 2011 2011 ...
##  $ 2012: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2012-01-01" "2012-02-01" ...
##   ..$ pce     : num [1:12] 10862 10954 10952 10980 10969 ...
##   ..$ pop     : num [1:12] 313183 313339 313499 313667 313831 ...
##   ..$ psavert : num [1:12] 8 8 8.5 8.7 8.8 9.1 8.2 8 8.2 8.8 ...
##   ..$ uempmed : num [1:12] 20.8 19.7 19.2 19.1 19.9 20.4 17.5 18.4 18.8 19.9 ...
##   ..$ unemploy: num [1:12] 12797 12813 12713 12646 12660 ...
##   ..$ year    : num [1:12] 2012 2012 2012 2012 2012 ...
##  $ 2013: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2013-01-01" "2013-02-01" ...
##   ..$ pce     : num [1:12] 11203 11240 11227 11205 11245 ...
##   ..$ pop     : num [1:12] 315390 315520 315662 315818 315984 ...
##   ..$ psavert : num [1:12] 6.3 5.8 5.9 6.4 6.7 6.8 6.6 6.7 6.8 6.3 ...
##   ..$ uempmed : num [1:12] 15.8 17.2 17.6 17.1 17.1 17 16.2 16.5 16.5 16.3 ...
##   ..$ unemploy: num [1:12] 12471 11950 11689 11760 11654 ...
##   ..$ year    : num [1:12] 2013 2013 2013 2013 2013 ...
##  $ 2014: tibble[,7] [12 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2014-01-01" "2014-02-01" ...
##   ..$ pce     : num [1:12] 11512 11566 11643 11703 11748 ...
##   ..$ pop     : num [1:12] 317594 317754 317917 318089 318270 ...
##   ..$ psavert : num [1:12] 7.1 7.3 7.4 7.4 7.4 7.4 7.5 7.2 7.4 7.2 ...
##   ..$ uempmed : num [1:12] 15.4 15.9 15.8 15.7 14.6 13.8 13.1 12.9 13.4 13.6 ...
##   ..$ unemploy: num [1:12] 10202 10349 10380 9702 9859 ...
##   ..$ year    : num [1:12] 2014 2014 2014 2014 2014 ...
##  $ 2015: tibble[,7] [4 × 7] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:4], format: "2015-01-01" "2015-02-01" ...
##   ..$ pce     : num [1:4] 12046 12082 12158 12194
##   ..$ pop     : num [1:4] 319929 320075 320231 320402
##   ..$ psavert : num [1:4] 7.7 7.9 7.4 7.6
##   ..$ uempmed : num [1:4] 13.2 12.9 12 11.5
##   ..$ unemploy: num [1:4] 8903 8610 8504 8526
##   ..$ year    : num [1:4] 2015 2015 2015 2015
```

---
# Fit a simple model to each year
Notes: 
* We'll discuss a more elegant way to do this later

* This is not (statistically) the best way to approach this problem

* It's a good illustration, and in my experience there are lots of times where
this approach works well, even if this particular example is a bit artificial

---
class: inverse-orange
## What is the relation between personal consumption expenditures (`pce`) and the unemployment percentage over time?

--
**Problem:** We don't have the percentage. Let's compute!

### You try first!

---

```r
perc <- map(by_year, ~mutate(.x, percent = unemploy / pop))
str(perc)
```

```
## List of 49
##  $ 1967: tibble[,8] [6 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:6], format: "1967-07-01" "1967-08-01" ...
##   ..$ pce     : num [1:6] 507 510 516 512 517 ...
##   ..$ pop     : num [1:6] 198712 198911 199113 199311 199498 ...
##   ..$ psavert : num [1:6] 12.6 12.6 11.9 12.9 12.8 11.8
##   ..$ uempmed : num [1:6] 4.5 4.7 4.6 4.9 4.7 4.8
##   ..$ unemploy: num [1:6] 2944 2945 2958 3143 3066 ...
##   ..$ year    : num [1:6] 1967 1967 1967 1967 1967 ...
##   ..$ percent : num [1:6] 0.0148 0.0148 0.0149 0.0158 0.0154 ...
##  $ 1968: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1968-01-01" "1968-02-01" ...
##   ..$ pce     : num [1:12] 531 534 544 544 550 ...
##   ..$ pop     : num [1:12] 2e+05 2e+05 2e+05 2e+05 2e+05 ...
##   ..$ psavert : num [1:12] 11.7 12.3 11.7 12.3 12 11.7 10.7 10.5 10.6 10.8 ...
##   ..$ uempmed : num [1:12] 5.1 4.5 4.1 4.6 4.4 4.4 4.5 4.2 4.6 4.8 ...
##   ..$ unemploy: num [1:12] 2878 3001 2877 2709 2740 ...
##   ..$ year    : num [1:12] 1968 1968 1968 1968 1968 ...
##   ..$ percent : num [1:12] 0.0144 0.015 0.0144 0.0135 0.0137 ...
##  $ 1969: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1969-01-01" "1969-02-01" ...
##   ..$ pce     : num [1:12] 584 589 589 594 600 ...
##   ..$ pop     : num [1:12] 201760 201881 202023 202161 202331 ...
##   ..$ psavert : num [1:12] 10.3 9.7 10.2 9.7 10.1 11.1 11.8 11.5 11.6 11.4 ...
##   ..$ uempmed : num [1:12] 4.4 4.9 4 4 4.2 4.4 4.4 4.4 4.7 4.5 ...
##   ..$ unemploy: num [1:12] 2718 2692 2712 2758 2713 ...
##   ..$ year    : num [1:12] 1969 1969 1969 1969 1969 ...
##   ..$ percent : num [1:12] 0.0135 0.0133 0.0134 0.0136 0.0134 ...
##  $ 1970: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1970-01-01" "1970-02-01" ...
##   ..$ pce     : num [1:12] 629 634 632 636 642 ...
##   ..$ pop     : num [1:12] 203849 204008 204156 204401 204607 ...
##   ..$ psavert : num [1:12] 11.8 11.7 12.4 13.3 12.4 12.3 13.5 13.4 12.9 13.1 ...
##   ..$ uempmed : num [1:12] 4.6 4.5 4.6 4.1 4.7 4.9 5.1 5.4 5.2 5.2 ...
##   ..$ unemploy: num [1:12] 3201 3453 3635 3797 3919 ...
##   ..$ year    : num [1:12] 1970 1970 1970 1970 1970 1970 1970 1970 1970 1970 ...
##   ..$ percent : num [1:12] 0.0157 0.0169 0.0178 0.0186 0.0192 ...
##  $ 1971: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1971-01-01" "1971-02-01" ...
##   ..$ pce     : num [1:12] 676 679 682 689 691 ...
##   ..$ pop     : num [1:12] 206466 206668 206855 207065 207260 ...
##   ..$ psavert : num [1:12] 13.3 13.3 13.5 13.2 13.6 14.7 13.8 13.6 13.3 13.3 ...
##   ..$ uempmed : num [1:12] 6.2 6.3 6.4 6.5 6.7 5.7 6.2 6.4 5.8 6.5 ...
##   ..$ unemploy: num [1:12] 4986 4903 4987 4959 4996 ...
##   ..$ year    : num [1:12] 1971 1971 1971 1971 1971 ...
##   ..$ percent : num [1:12] 0.0241 0.0237 0.0241 0.0239 0.0241 ...
##  $ 1972: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1972-01-01" "1972-02-01" ...
##   ..$ pce     : num [1:12] 732 736 749 752 758 ...
##   ..$ pop     : num [1:12] 208917 209061 209212 209386 209545 ...
##   ..$ psavert : num [1:12] 12.5 12.8 11.8 11.5 11.7 11.7 11.7 12 12.2 13 ...
##   ..$ uempmed : num [1:12] 6.2 6.6 6.6 6.7 6.6 5.4 6.1 6 5.6 5.7 ...
##   ..$ unemploy: num [1:12] 5019 4928 5038 4959 4922 ...
##   ..$ year    : num [1:12] 1972 1972 1972 1972 1972 ...
##   ..$ percent : num [1:12] 0.024 0.0236 0.0241 0.0237 0.0235 ...
##  $ 1973: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1973-01-01" "1973-02-01" ...
##   ..$ pce     : num [1:12] 816 826 833 836 842 ...
##   ..$ pop     : num [1:12] 210985 211120 211254 211420 211577 ...
##   ..$ psavert : num [1:12] 12.4 12.5 12.7 13.2 13.2 13.6 13.2 13.9 13.1 14.4 ...
##   ..$ uempmed : num [1:12] 5.7 5.2 5.5 5 4.9 5 5.2 4.9 5.4 5.5 ...
##   ..$ unemploy: num [1:12] 4326 4452 4394 4459 4329 ...
##   ..$ year    : num [1:12] 1973 1973 1973 1973 1973 ...
##   ..$ percent : num [1:12] 0.0205 0.0211 0.0208 0.0211 0.0205 ...
##  $ 1974: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1974-01-01" "1974-02-01" ...
##   ..$ pce     : num [1:12] 884 890 901 911 922 ...
##   ..$ pop     : num [1:12] 212932 213074 213211 213361 213513 ...
##   ..$ psavert : num [1:12] 14.3 14.2 13.4 13.1 12.8 12.8 12.8 12.1 12.9 13.4 ...
##   ..$ uempmed : num [1:12] 5 5.1 4.8 5 4.6 5.3 5.7 5 5.3 5.5 ...
##   ..$ unemploy: num [1:12] 4644 4731 4634 4618 4705 ...
##   ..$ year    : num [1:12] 1974 1974 1974 1974 1974 ...
##   ..$ percent : num [1:12] 0.0218 0.0222 0.0217 0.0216 0.022 ...
##  $ 1975: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1975-01-01" "1975-02-01" ...
##   ..$ pce     : num [1:12] 976 989 991 995 1019 ...
##   ..$ pop     : num [1:12] 214931 215065 215198 215353 215523 ...
##   ..$ psavert : num [1:12] 13.2 12.5 12.7 14.2 17.3 14.3 12.6 13 13 13.4 ...
##   ..$ uempmed : num [1:12] 6.3 7.1 7.2 8.7 9.4 8.8 8.6 9.2 9.2 8.6 ...
##   ..$ unemploy: num [1:12] 7501 7520 7978 8210 8433 ...
##   ..$ year    : num [1:12] 1975 1975 1975 1975 1975 ...
##   ..$ percent : num [1:12] 0.0349 0.035 0.0371 0.0381 0.0391 ...
##  $ 1976: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1976-01-01" "1976-02-01" ...
##   ..$ pce     : num [1:12] 1107 1108 1115 1125 1123 ...
##   ..$ pop     : num [1:12] 217095 217249 217381 217528 217685 ...
##   ..$ psavert : num [1:12] 11.7 12.3 12.2 11.7 12.3 11.4 11.7 11.7 11.4 11.1 ...
##   ..$ uempmed : num [1:12] 9 8.2 8.7 8.2 8.3 7.8 7.7 7.9 7.8 7.7 ...
##   ..$ unemploy: num [1:12] 7534 7326 7230 7330 7053 ...
##   ..$ year    : num [1:12] 1976 1976 1976 1976 1976 ...
##   ..$ percent : num [1:12] 0.0347 0.0337 0.0333 0.0337 0.0324 ...
##  $ 1977: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1977-01-01" "1977-02-01" ...
##   ..$ pce     : num [1:12] 1215 1231 1238 1247 1257 ...
##   ..$ pop     : num [1:12] 219179 219344 219504 219684 219859 ...
##   ..$ psavert : num [1:12] 10.6 9.3 10.5 10.5 10.3 10.6 10.5 10.9 11.1 11 ...
##   ..$ uempmed : num [1:12] 7.5 7.2 7.2 7.3 7.9 6.2 7.1 7 6.7 6.9 ...
##   ..$ unemploy: num [1:12] 7280 7443 7307 7059 6911 ...
##   ..$ year    : num [1:12] 1977 1977 1977 1977 1977 ...
##   ..$ percent : num [1:12] 0.0332 0.0339 0.0333 0.0321 0.0314 ...
##  $ 1978: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1978-01-01" "1978-02-01" ...
##   ..$ pce     : num [1:12] 1330 1355 1378 1396 1412 ...
##   ..$ pop     : num [1:12] 221477 221629 221792 221991 222176 ...
##   ..$ psavert : num [1:12] 11.9 11.1 11 10.8 10.3 10 10.9 10.5 10.6 10.7 ...
##   ..$ uempmed : num [1:12] 6.5 6.7 6.2 6.1 5.7 6 5.8 5.8 5.6 5.9 ...
##   ..$ unemploy: num [1:12] 6489 6318 6337 6180 6127 ...
##   ..$ year    : num [1:12] 1978 1978 1978 1978 1978 ...
##   ..$ percent : num [1:12] 0.0293 0.0285 0.0286 0.0278 0.0276 ...
##  $ 1979: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1979-01-01" "1979-02-01" ...
##   ..$ pce     : num [1:12] 1502 1518 1531 1538 1559 ...
##   ..$ pop     : num [1:12] 223865 224053 224235 224438 224632 ...
##   ..$ psavert : num [1:12] 11.1 11.1 11.2 11 10.3 9.9 10.6 9.7 9.4 9.7 ...
##   ..$ uempmed : num [1:12] 5.9 5.9 5.9 5.4 5.6 5.6 5.9 4.8 5.5 5.5 ...
##   ..$ unemploy: num [1:12] 6109 6173 6109 6069 5840 ...
##   ..$ year    : num [1:12] 1979 1979 1979 1979 1979 ...
##   ..$ percent : num [1:12] 0.0273 0.0276 0.0272 0.027 0.026 ...
##  $ 1980: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1980-01-01" "1980-02-01" ...
##   ..$ pce     : num [1:12] 1697 1701 1708 1695 1700 ...
##   ..$ pop     : num [1:12] 226451 226656 226849 227061 227251 ...
##   ..$ psavert : num [1:12] 9.9 10.1 10.2 11.3 11.4 11.2 11.3 11.3 11.7 11.3 ...
##   ..$ uempmed : num [1:12] 5.3 5.8 6 5.8 5.7 6.4 7 7.5 7.7 7.5 ...
##   ..$ unemploy: num [1:12] 6683 6702 6729 7358 7984 ...
##   ..$ year    : num [1:12] 1980 1980 1980 1980 1980 1980 1980 1980 1980 1980 ...
##   ..$ percent : num [1:12] 0.0295 0.0296 0.0297 0.0324 0.0351 ...
##  $ 1981: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1981-01-01" "1981-02-01" ...
##   ..$ pce     : num [1:12] 1870 1884 1903 1904 1914 ...
##   ..$ pop     : num [1:12] 228937 229071 229224 229403 229575 ...
##   ..$ psavert : num [1:12] 10.9 10.8 10.8 10.9 11 10.8 12.3 12 12.4 13 ...
##   ..$ uempmed : num [1:12] 7.4 7.1 7.1 7.4 6.9 6.6 7.1 7.2 6.8 6.8 ...
##   ..$ unemploy: num [1:12] 8071 8051 7982 7869 8174 ...
##   ..$ year    : num [1:12] 1981 1981 1981 1981 1981 ...
##   ..$ percent : num [1:12] 0.0353 0.0351 0.0348 0.0343 0.0356 ...
##  $ 1982: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1982-01-01" "1982-02-01" ...
##   ..$ pce     : num [1:12] 1997 2021 2024 2026 2044 ...
##   ..$ pop     : num [1:12] 231157 231313 231470 231645 231809 ...
##   ..$ psavert : num [1:12] 12.7 12.1 12.2 12.9 12.3 12.3 12.5 12.6 11.8 11.3 ...
##   ..$ uempmed : num [1:12] 7.1 7.5 7.7 8.1 8.5 9.5 8.5 8.7 9.5 9.7 ...
##   ..$ unemploy: num [1:12] 9397 9705 9895 10244 10335 ...
##   ..$ year    : num [1:12] 1982 1982 1982 1982 1982 ...
##   ..$ percent : num [1:12] 0.0407 0.042 0.0427 0.0442 0.0446 ...
##  $ 1983: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1983-01-01" "1983-02-01" ...
##   ..$ pce     : num [1:12] 2174 2177 2203 2226 2246 ...
##   ..$ pop     : num [1:12] 233322 233473 233613 233781 233922 ...
##   ..$ psavert : num [1:12] 11.1 11.1 10.6 10.3 9.9 9.1 9.6 9.2 9.6 9.7 ...
##   ..$ uempmed : num [1:12] 11.1 9.8 10.4 10.9 12.3 11.3 10.1 9.3 9.3 9.4 ...
##   ..$ unemploy: num [1:12] 11534 11545 11408 11268 11154 ...
##   ..$ year    : num [1:12] 1983 1983 1983 1983 1983 ...
##   ..$ percent : num [1:12] 0.0494 0.0494 0.0488 0.0482 0.0477 ...
##  $ 1984: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1984-01-01" "1984-02-01" ...
##   ..$ pce     : num [1:12] 2419 2404 2432 2458 2474 ...
##   ..$ pop     : num [1:12] 235385 235527 235675 235839 235993 ...
##   ..$ psavert : num [1:12] 10 11.7 11.5 11.5 11.1 11.1 11.6 11.8 11.8 11.7 ...
##   ..$ uempmed : num [1:12] 9.1 8.3 8.3 8.2 9.1 7.5 7.5 7.3 7.6 7.2 ...
##   ..$ unemploy: num [1:12] 9008 8791 8746 8762 8456 ...
##   ..$ year    : num [1:12] 1984 1984 1984 1984 1984 ...
##   ..$ percent : num [1:12] 0.0383 0.0373 0.0371 0.0372 0.0358 ...
##  $ 1985: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1985-01-01" "1985-02-01" ...
##   ..$ pce     : num [1:12] 2619 2641 2648 2660 2696 ...
##   ..$ pop     : num [1:12] 237468 237602 237732 237900 238074 ...
##   ..$ psavert : num [1:12] 10.3 9.1 8.7 9.9 11.1 9.6 9.1 8.2 7.3 9.1 ...
##   ..$ uempmed : num [1:12] 6.8 7.1 7.1 6.9 6.9 6.6 6.9 7.1 6.9 7.1 ...
##   ..$ unemploy: num [1:12] 8423 8321 8339 8395 8302 ...
##   ..$ year    : num [1:12] 1985 1985 1985 1985 1985 ...
##   ..$ percent : num [1:12] 0.0355 0.035 0.0351 0.0353 0.0349 ...
##  $ 1986: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1986-01-01" "1986-02-01" ...
##   ..$ pce     : num [1:12] 2827 2820 2824 2835 2858 ...
##   ..$ pop     : num [1:12] 239638 239788 239928 240094 240271 ...
##   ..$ psavert : num [1:12] 8.6 9.3 9.9 9.7 9.3 9.4 9.3 9 7.2 8.4 ...
##   ..$ uempmed : num [1:12] 6.7 6.9 6.8 6.7 6.8 7 6.9 7.1 7.4 7 ...
##   ..$ unemploy: num [1:12] 7795 8402 8383 8364 8439 ...
##   ..$ year    : num [1:12] 1986 1986 1986 1986 1986 ...
##   ..$ percent : num [1:12] 0.0325 0.035 0.0349 0.0348 0.0351 ...
##  $ 1987: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1987-01-01" "1987-02-01" ...
##   ..$ pce     : num [1:12] 2936 3002 3013 3039 3048 ...
##   ..$ pop     : num [1:12] 241784 241930 242079 242252 242423 ...
##   ..$ psavert : num [1:12] 9.7 8.5 8.5 4.5 8.2 7.7 7.5 7.2 7.6 8.3 ...
##   ..$ uempmed : num [1:12] 6.9 6.6 6.6 7.1 6.6 6.5 6.5 6.4 6 6.3 ...
##   ..$ unemploy: num [1:12] 7892 7865 7862 7542 7574 ...
##   ..$ year    : num [1:12] 1987 1987 1987 1987 1987 ...
##   ..$ percent : num [1:12] 0.0326 0.0325 0.0325 0.0311 0.0312 ...
##  $ 1988: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1988-01-01" "1988-02-01" ...
##   ..$ pce     : num [1:12] 3214 3221 3260 3263 3294 ...
##   ..$ pop     : num [1:12] 243981 244131 244279 244445 244610 ...
##   ..$ psavert : num [1:12] 8.1 8.6 8.2 8.8 8.4 8.4 8.6 8.4 8.9 8.6 ...
##   ..$ uempmed : num [1:12] 6.2 6.3 6.4 5.9 5.9 5.8 6.1 5.9 5.7 5.6 ...
##   ..$ unemploy: num [1:12] 6953 6929 6876 6601 6779 ...
##   ..$ year    : num [1:12] 1988 1988 1988 1988 1988 ...
##   ..$ percent : num [1:12] 0.0285 0.0284 0.0281 0.027 0.0277 ...
##  $ 1989: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1989-01-01" "1989-02-01" ...
##   ..$ pce     : num [1:12] 3484 3488 3499 3543 3552 ...
##   ..$ pop     : num [1:12] 246224 246378 246530 246721 246906 ...
##   ..$ psavert : num [1:12] 8.5 9 9.5 8.4 8.1 8.2 8.2 7.6 8.1 8.5 ...
##   ..$ uempmed : num [1:12] 5.6 5.4 5.4 5.4 5.3 5.4 5.6 5 4.9 4.9 ...
##   ..$ unemploy: num [1:12] 6682 6359 6205 6468 6375 ...
##   ..$ year    : num [1:12] 1989 1989 1989 1989 1989 ...
##   ..$ percent : num [1:12] 0.0271 0.0258 0.0252 0.0262 0.0258 ...
##  $ 1990: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1990-01-01" "1990-02-01" ...
##   ..$ pce     : num [1:12] 3731 3728 3755 3770 3776 ...
##   ..$ pop     : num [1:12] 248659 248827 249012 249306 249565 ...
##   ..$ psavert : num [1:12] 8 8.6 8.3 8.8 8.7 8.6 8.7 8.1 8.1 7.8 ...
##   ..$ uempmed : num [1:12] 5.1 5.3 5.1 4.8 5.2 5.2 5.4 5.4 5.6 5.8 ...
##   ..$ unemploy: num [1:12] 6752 6651 6598 6797 6742 ...
##   ..$ year    : num [1:12] 1990 1990 1990 1990 1990 1990 1990 1990 1990 1990 ...
##   ..$ percent : num [1:12] 0.0272 0.0267 0.0265 0.0273 0.027 ...
##  $ 1991: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1991-01-01" "1991-02-01" ...
##   ..$ pce     : num [1:12] 3841 3867 3913 3907 3933 ...
##   ..$ pop     : num [1:12] 251889 252135 252372 252643 252913 ...
##   ..$ psavert : num [1:12] 9.3 8.8 8 8.6 8.4 8.9 8.2 8.6 8.8 9.3 ...
##   ..$ uempmed : num [1:12] 6 6.2 6.7 6.6 6.4 6.9 7 7.3 6.8 7.2 ...
##   ..$ unemploy: num [1:12] 8015 8265 8586 8439 8736 ...
##   ..$ year    : num [1:12] 1991 1991 1991 1991 1991 ...
##   ..$ percent : num [1:12] 0.0318 0.0328 0.034 0.0334 0.0345 ...
##  $ 1992: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1992-01-01" "1992-02-01" ...
##   ..$ pce     : num [1:12] 4085 4100 4117 4132 4158 ...
##   ..$ pop     : num [1:12] 255214 255448 255703 255992 256285 ...
##   ..$ psavert : num [1:12] 9.4 9.8 9.7 9.9 9.9 10.1 9.6 9.7 8.7 8 ...
##   ..$ uempmed : num [1:12] 8.1 8.2 8.3 8.5 8.8 8.7 8.6 8.8 8.6 9 ...
##   ..$ unemploy: num [1:12] 9283 9454 9460 9415 9744 ...
##   ..$ year    : num [1:12] 1992 1992 1992 1992 1992 ...
##   ..$ percent : num [1:12] 0.0364 0.037 0.037 0.0368 0.038 ...
##  $ 1993: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1993-01-01" "1993-02-01" ...
##   ..$ pce     : num [1:12] 4341 4355 4352 4393 4422 ...
##   ..$ pop     : num [1:12] 258679 258919 259152 259414 259680 ...
##   ..$ psavert : num [1:12] 8.6 8.9 8.9 8.7 8.3 7.8 7.6 7.7 6.9 6.3 ...
##   ..$ uempmed : num [1:12] 8.6 8.5 8.5 8.4 8.1 8.3 8.2 8.2 8.3 8 ...
##   ..$ unemploy: num [1:12] 9325 9183 9056 9110 9149 ...
##   ..$ year    : num [1:12] 1993 1993 1993 1993 1993 ...
##   ..$ percent : num [1:12] 0.036 0.0355 0.0349 0.0351 0.0352 ...
##  $ 1994: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1994-01-01" "1994-02-01" ...
##   ..$ pce     : num [1:12] 4585 4633 4646 4671 4670 ...
##   ..$ pop     : num [1:12] 261919 262123 262352 262631 262877 ...
##   ..$ psavert : num [1:12] 7.1 6.5 6.8 6.4 7.6 6.9 7 6.5 6.8 7.1 ...
##   ..$ uempmed : num [1:12] 8.6 9.2 9.3 9.1 9.2 9.3 9 8.9 9.2 10 ...
##   ..$ unemploy: num [1:12] 8630 8583 8470 8331 7915 ...
##   ..$ year    : num [1:12] 1994 1994 1994 1994 1994 ...
##   ..$ percent : num [1:12] 0.0329 0.0327 0.0323 0.0317 0.0301 ...
##  $ 1995: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1995-01-01" "1995-02-01" ...
##   ..$ pce     : num [1:12] 4851 4851 4885 4890 4933 ...
##   ..$ pop     : num [1:12] 265044 265270 265495 265755 265998 ...
##   ..$ psavert : num [1:12] 7.5 7.8 7.5 6.9 7.1 6.7 7.1 6.7 6.8 7.1 ...
##   ..$ uempmed : num [1:12] 8 8.1 8.3 8.3 9.1 7.9 8.5 8.3 7.9 8.2 ...
##   ..$ unemploy: num [1:12] 7375 7187 7153 7645 7430 ...
##   ..$ year    : num [1:12] 1995 1995 1995 1995 1995 ...
##   ..$ percent : num [1:12] 0.0278 0.0271 0.0269 0.0288 0.0279 ...
##  $ 1996: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1996-01-01" "1996-02-01" ...
##   ..$ pce     : num [1:12] 5086 5133 5173 5208 5224 ...
##   ..$ pop     : num [1:12] 268151 268364 268595 268853 269108 ...
##   ..$ psavert : num [1:12] 6.7 6.7 6.6 5.7 6.7 7.1 6.7 6.6 6.7 6.4 ...
##   ..$ uempmed : num [1:12] 8.3 7.8 8.3 8.6 8.6 8.3 8.3 8.4 8.5 8.3 ...
##   ..$ unemploy: num [1:12] 7491 7313 7318 7415 7423 ...
##   ..$ year    : num [1:12] 1996 1996 1996 1996 1996 ...
##   ..$ percent : num [1:12] 0.0279 0.0273 0.0272 0.0276 0.0276 ...
##  $ 1997: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1997-01-01" "1997-02-01" ...
##   ..$ pce     : num [1:12] 5411 5434 5454 5459 5460 ...
##   ..$ pop     : num [1:12] 271360 271585 271821 272083 272342 ...
##   ..$ psavert : num [1:12] 6.2 6.2 6.4 6.5 6.8 6.6 6.1 6 6.2 6.2 ...
##   ..$ uempmed : num [1:12] 7.8 8.1 7.9 8.3 8 8 8.3 7.8 8.2 7.7 ...
##   ..$ unemploy: num [1:12] 7158 7102 7000 6873 6655 ...
##   ..$ year    : num [1:12] 1997 1997 1997 1997 1997 ...
##   ..$ percent : num [1:12] 0.0264 0.0262 0.0258 0.0253 0.0244 ...
##  $ 1998: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1998-01-01" "1998-02-01" ...
##   ..$ pce     : num [1:12] 5690 5724 5750 5788 5838 ...
##   ..$ pop     : num [1:12] 274626 274838 275047 275304 275564 ...
##   ..$ psavert : num [1:12] 7.4 7.4 7.5 7.2 6.9 6.8 6.9 6.8 6.4 6.2 ...
##   ..$ uempmed : num [1:12] 7.4 7 6.8 6.7 6 6.9 6.7 6.8 6.7 5.8 ...
##   ..$ unemploy: num [1:12] 6368 6306 6422 5941 6047 ...
##   ..$ year    : num [1:12] 1998 1998 1998 1998 1998 ...
##   ..$ percent : num [1:12] 0.0232 0.0229 0.0233 0.0216 0.0219 ...
##  $ 1999: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "1999-01-01" "1999-02-01" ...
##   ..$ pce     : num [1:12] 6073 6102 6133 6196 6226 ...
##   ..$ pop     : num [1:12] 277790 277992 278198 278451 278717 ...
##   ..$ psavert : num [1:12] 6.4 6.2 5.9 5.2 4.9 4.8 4.8 4.7 4.2 4.6 ...
##   ..$ uempmed : num [1:12] 6.9 6.8 6.8 6.2 6.5 6.3 5.8 6.5 6 6.1 ...
##   ..$ unemploy: num [1:12] 5976 6111 5783 6004 5796 ...
##   ..$ year    : num [1:12] 1999 1999 1999 1999 1999 ...
##   ..$ percent : num [1:12] 0.0215 0.022 0.0208 0.0216 0.0208 ...
##  $ 2000: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2000-01-01" "2000-02-01" ...
##   ..$ pce     : num [1:12] 6535 6620 6686 6671 6708 ...
##   ..$ pop     : num [1:12] 280976 281190 281409 281653 281877 ...
##   ..$ psavert : num [1:12] 5.4 4.8 4.5 5 4.9 4.9 5.2 5.2 4.5 4.6 ...
##   ..$ uempmed : num [1:12] 5.8 6.1 6 6.1 5.8 5.7 6 6.3 5.2 6.1 ...
##   ..$ unemploy: num [1:12] 5708 5858 5733 5481 5758 ...
##   ..$ year    : num [1:12] 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 ...
##   ..$ percent : num [1:12] 0.0203 0.0208 0.0204 0.0195 0.0204 ...
##  $ 2001: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2001-01-01" "2001-02-01" ...
##   ..$ pce     : num [1:12] 6977 6996 6988 7001 7047 ...
##   ..$ pop     : num [1:12] 283920 284137 284350 284581 284810 ...
##   ..$ psavert : num [1:12] 4.8 4.9 5.3 5 4.5 4.5 5.6 6.8 7 3.4 ...
##   ..$ uempmed : num [1:12] 5.8 6.1 6.6 5.9 6.3 6 6.8 6.9 7.2 7.3 ...
##   ..$ unemploy: num [1:12] 6023 6089 6141 6271 6226 ...
##   ..$ year    : num [1:12] 2001 2001 2001 2001 2001 ...
##   ..$ percent : num [1:12] 0.0212 0.0214 0.0216 0.022 0.0219 ...
##  $ 2002: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2002-01-01" "2002-02-01" ...
##   ..$ pce     : num [1:12] 7174 7218 7237 7305 7283 ...
##   ..$ pop     : num [1:12] 286788 286994 287190 287397 287623 ...
##   ..$ psavert : num [1:12] 6.1 5.8 5.9 5.8 6.5 6.4 5.5 5.4 5.7 5.7 ...
##   ..$ uempmed : num [1:12] 8.4 8.3 8.4 8.9 9.5 11 8.9 9 9.5 9.6 ...
##   ..$ unemploy: num [1:12] 8182 8215 8304 8599 8399 ...
##   ..$ year    : num [1:12] 2002 2002 2002 2002 2002 ...
##   ..$ percent : num [1:12] 0.0285 0.0286 0.0289 0.0299 0.0292 ...
##  $ 2003: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2003-01-01" "2003-02-01" ...
##   ..$ pce     : num [1:12] 7533 7536 7598 7621 7628 ...
##   ..$ pop     : num [1:12] 289518 289714 289911 290125 290346 ...
##   ..$ psavert : num [1:12] 5.5 5.6 5.3 5.3 5.8 5.6 6.3 6 5.2 5.3 ...
##   ..$ uempmed : num [1:12] 9.6 9.5 9.7 10.2 9.9 11.5 10.3 10.1 10.2 10.4 ...
##   ..$ unemploy: num [1:12] 8520 8618 8588 8842 8957 ...
##   ..$ year    : num [1:12] 2003 2003 2003 2003 2003 ...
##   ..$ percent : num [1:12] 0.0294 0.0297 0.0296 0.0305 0.0308 ...
##  $ 2004: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2004-01-01" "2004-02-01" ...
##   ..$ pce     : num [1:12] 7987 8020 8076 8089 8163 ...
##   ..$ pop     : num [1:12] 292192 292368 292561 292779 292997 ...
##   ..$ psavert : num [1:12] 5 5 4.9 5.3 5.3 5.8 5.3 5.2 4.6 4.5 ...
##   ..$ uempmed : num [1:12] 10.6 10.2 10.2 9.5 9.9 11 8.9 9.2 9.6 9.5 ...
##   ..$ unemploy: num [1:12] 8370 8167 8491 8170 8212 ...
##   ..$ year    : num [1:12] 2004 2004 2004 2004 2004 ...
##   ..$ percent : num [1:12] 0.0286 0.0279 0.029 0.0279 0.028 ...
##  $ 2005: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2005-01-01" "2005-02-01" ...
##   ..$ pce     : num [1:12] 8470 8529 8570 8646 8644 ...
##   ..$ pop     : num [1:12] 294914 295105 295287 295490 295704 ...
##   ..$ psavert : num [1:12] 3.7 3.4 3.6 3.1 3.5 2.9 2.2 2.7 2.7 3.1 ...
##   ..$ uempmed : num [1:12] 9.4 9.2 9.3 9 9.1 9 8.8 9.2 8.4 8.6 ...
##   ..$ unemploy: num [1:12] 7784 7980 7737 7672 7651 ...
##   ..$ year    : num [1:12] 2005 2005 2005 2005 2005 ...
##   ..$ percent : num [1:12] 0.0264 0.027 0.0262 0.026 0.0259 ...
##  $ 2006: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2006-01-01" "2006-02-01" ...
##   ..$ pce     : num [1:12] 9060 9090 9122 9175 9215 ...
##   ..$ pop     : num [1:12] 297647 297854 298060 298281 298496 ...
##   ..$ psavert : num [1:12] 4.2 4.2 4.2 4 3.8 4 3.4 3.6 3.6 3.6 ...
##   ..$ uempmed : num [1:12] 8.6 9.1 8.7 8.4 8.5 7.3 8 8.4 8 7.9 ...
##   ..$ unemploy: num [1:12] 7064 7184 7072 7120 6980 ...
##   ..$ year    : num [1:12] 2006 2006 2006 2006 2006 ...
##   ..$ percent : num [1:12] 0.0237 0.0241 0.0237 0.0239 0.0234 ...
##  $ 2007: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2007-01-01" "2007-02-01" ...
##   ..$ pce     : num [1:12] 9516 9547 9585 9616 9651 ...
##   ..$ pop     : num [1:12] 300574 300802 301021 301254 301483 ...
##   ..$ psavert : num [1:12] 3.7 4.1 4.4 4.2 4 3.8 3.7 3.4 3.5 3.4 ...
##   ..$ uempmed : num [1:12] 8.3 8.5 9.1 8.6 8.2 7.7 8.7 8.8 8.7 8.4 ...
##   ..$ unemploy: num [1:12] 7116 6927 6731 6850 6766 ...
##   ..$ year    : num [1:12] 2007 2007 2007 2007 2007 ...
##   ..$ percent : num [1:12] 0.0237 0.023 0.0224 0.0227 0.0224 ...
##  $ 2008: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2008-01-01" "2008-02-01" ...
##   ..$ pce     : num [1:12] 9930 9913 9959 9997 10054 ...
##   ..$ pop     : num [1:12] 303506 303711 303907 304117 304323 ...
##   ..$ psavert : num [1:12] 3.7 4.1 4 3.4 7.8 5.5 4.4 3.8 4.7 5.5 ...
##   ..$ uempmed : num [1:12] 9 8.7 8.7 9.4 7.9 9 9.7 9.7 10.2 10.4 ...
##   ..$ unemploy: num [1:12] 7685 7497 7822 7637 8395 ...
##   ..$ year    : num [1:12] 2008 2008 2008 2008 2008 ...
##   ..$ percent : num [1:12] 0.0253 0.0247 0.0257 0.0251 0.0276 ...
##  $ 2009: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2009-01-01" "2009-02-01" ...
##   ..$ pce     : num [1:12] 9784 9766 9718 9725 9749 ...
##   ..$ pop     : num [1:12] 306208 306402 306588 306787 306984 ...
##   ..$ psavert : num [1:12] 6.2 5.5 5.9 6.8 8.2 6.7 6 4.9 5.9 5.4 ...
##   ..$ uempmed : num [1:12] 10.7 11.7 12.3 13.1 14.2 17.2 16 16.3 17.8 18.9 ...
##   ..$ unemploy: num [1:12] 12058 12898 13426 13853 14499 ...
##   ..$ year    : num [1:12] 2009 2009 2009 2009 2009 ...
##   ..$ percent : num [1:12] 0.0394 0.0421 0.0438 0.0452 0.0472 ...
##  $ 2010: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2010-01-01" "2010-02-01" ...
##   ..$ pce     : num [1:12] 10002 10031 10089 10113 10131 ...
##   ..$ pop     : num [1:12] 308833 309027 309212 309191 309369 ...
##   ..$ psavert : num [1:12] 6.1 5.8 5.7 6.4 7 6.9 6.8 6.9 6.7 6.6 ...
##   ..$ uempmed : num [1:12] 20 19.9 20.4 22.1 22.3 25.2 22.3 21 20.3 21.2 ...
##   ..$ unemploy: num [1:12] 15046 15113 15202 15325 14849 ...
##   ..$ year    : num [1:12] 2010 2010 2010 2010 2010 2010 2010 2010 2010 2010 ...
##   ..$ percent : num [1:12] 0.0487 0.0489 0.0492 0.0496 0.048 ...
##  $ 2011: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2011-01-01" "2011-02-01" ...
##   ..$ pce     : num [1:12] 10436 10470 10550 10588 10612 ...
##   ..$ pop     : num [1:12] 310961 311113 311265 311436 311607 ...
##   ..$ psavert : num [1:12] 7.4 7.6 7 6.9 6.9 7.2 7.3 7.2 6.8 6.8 ...
##   ..$ uempmed : num [1:12] 21.5 21.1 21.5 20.9 21.6 22.4 22 22.4 22 20.6 ...
##   ..$ unemploy: num [1:12] 14013 13820 13737 13957 13855 ...
##   ..$ year    : num [1:12] 2011 2011 2011 2011 2011 ...
##   ..$ percent : num [1:12] 0.0451 0.0444 0.0441 0.0448 0.0445 ...
##  $ 2012: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2012-01-01" "2012-02-01" ...
##   ..$ pce     : num [1:12] 10862 10954 10952 10980 10969 ...
##   ..$ pop     : num [1:12] 313183 313339 313499 313667 313831 ...
##   ..$ psavert : num [1:12] 8 8 8.5 8.7 8.8 9.1 8.2 8 8.2 8.8 ...
##   ..$ uempmed : num [1:12] 20.8 19.7 19.2 19.1 19.9 20.4 17.5 18.4 18.8 19.9 ...
##   ..$ unemploy: num [1:12] 12797 12813 12713 12646 12660 ...
##   ..$ year    : num [1:12] 2012 2012 2012 2012 2012 ...
##   ..$ percent : num [1:12] 0.0409 0.0409 0.0406 0.0403 0.0403 ...
##  $ 2013: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2013-01-01" "2013-02-01" ...
##   ..$ pce     : num [1:12] 11203 11240 11227 11205 11245 ...
##   ..$ pop     : num [1:12] 315390 315520 315662 315818 315984 ...
##   ..$ psavert : num [1:12] 6.3 5.8 5.9 6.4 6.7 6.8 6.6 6.7 6.8 6.3 ...
##   ..$ uempmed : num [1:12] 15.8 17.2 17.6 17.1 17.1 17 16.2 16.5 16.5 16.3 ...
##   ..$ unemploy: num [1:12] 12471 11950 11689 11760 11654 ...
##   ..$ year    : num [1:12] 2013 2013 2013 2013 2013 ...
##   ..$ percent : num [1:12] 0.0395 0.0379 0.037 0.0372 0.0369 ...
##  $ 2014: tibble[,8] [12 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:12], format: "2014-01-01" "2014-02-01" ...
##   ..$ pce     : num [1:12] 11512 11566 11643 11703 11748 ...
##   ..$ pop     : num [1:12] 317594 317754 317917 318089 318270 ...
##   ..$ psavert : num [1:12] 7.1 7.3 7.4 7.4 7.4 7.4 7.5 7.2 7.4 7.2 ...
##   ..$ uempmed : num [1:12] 15.4 15.9 15.8 15.7 14.6 13.8 13.1 12.9 13.4 13.6 ...
##   ..$ unemploy: num [1:12] 10202 10349 10380 9702 9859 ...
##   ..$ year    : num [1:12] 2014 2014 2014 2014 2014 ...
##   ..$ percent : num [1:12] 0.0321 0.0326 0.0327 0.0305 0.031 ...
##  $ 2015: tibble[,8] [4 × 8] (S3: tbl_df/tbl/data.frame)
##   ..$ date    : Date[1:4], format: "2015-01-01" "2015-02-01" ...
##   ..$ pce     : num [1:4] 12046 12082 12158 12194
##   ..$ pop     : num [1:4] 319929 320075 320231 320402
##   ..$ psavert : num [1:4] 7.7 7.9 7.4 7.6
##   ..$ uempmed : num [1:4] 13.2 12.9 12 11.5
##   ..$ unemploy: num [1:4] 8903 8610 8504 8526
##   ..$ year    : num [1:4] 2015 2015 2015 2015
##   ..$ percent : num [1:4] 0.0278 0.0269 0.0266 0.0266
```

---
# Fit the models

Fit a model of the form `lm(percent ~ pce)` to each year

### You try first!

```r
mods <- map(perc, ~lm(percent ~ pce, data = .x))
str(mods)
```

```
## List of 49
##  $ 1967:List of 12
##   ..$ coefficients : Named num [1:2] 8.40e-03 1.31e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:6] -0.000205 -0.000255 -0.000281 0.000677 0.000208 ...
##   .. ..- attr(*, "names")= chr [1:6] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:6] -0.037041 0.00019 -0.000261 0.000737 0.000208 ...
##   .. ..- attr(*, "names")= chr [1:6] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:6] 0.015 0.0151 0.0151 0.0151 0.0152 ...
##   .. ..- attr(*, "names")= chr [1:6] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:6, 1:2] -2.449 0.408 0.408 0.408 0.408 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:6] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.41 1.17
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 4
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b6b98e10> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	6 obs. of  2 variables:
##   .. ..$ percent: num [1:6] 0.0148 0.0148 0.0149 0.0158 0.0154 ...
##   .. ..$ pce    : num [1:6] 507 510 516 512 517 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b6b98e10> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1968:List of 12
##   ..$ coefficients : Named num [1:2] 0.027846 -0.000025
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.000186 0.000489 0.000126 -0.000732 -0.000443 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.048297 -0.001335 0.000117 -0.000743 -0.00041 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0146 0.0145 0.0143 0.0143 0.0141 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.33
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b6a9d3c0> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0144 0.015 0.0144 0.0135 0.0137 ...
##   .. ..$ pce    : num [1:12] 531 534 544 544 550 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b6a9d3c0> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1969:List of 12
##   ..$ coefficients : Named num [1:2] -0.005363 0.000032
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 1.52e-04 -1.51e-04 -6.82e-05 -9.87e-06 -4.49e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -4.84e-02 1.42e-03 -6.75e-05 -2.62e-05 -4.87e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0133 0.0135 0.0135 0.0137 0.0139 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.24
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b64b9c70> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0135 0.0133 0.0134 0.0136 0.0134 ...
##   .. ..$ pce    : num [1:12] 584 589 589 594 600 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b64b9c70> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1970:List of 12
##   ..$ coefficients : Named num [1:2] -0.118058 0.000214
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -5.71e-04 -4.81e-04 7.62e-04 7.42e-04 -4.76e-05 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -6.97e-02 8.58e-03 9.65e-04 9.19e-04 8.25e-05 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0163 0.0174 0.017 0.0178 0.0192 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.22
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b60ce188> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0157 0.0169 0.0178 0.0186 0.0192 ...
##   .. ..$ pce    : num [1:12] 629 634 632 636 642 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b60ce188> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1971:List of 12
##   ..$ coefficients : Named num [1:2] 1.59e-02 1.18e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 2.40e-04 -2.24e-04 1.30e-04 -1.10e-04 1.92e-05 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -8.38e-02 6.67e-04 1.25e-04 -1.41e-04 -2.11e-05 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0239 0.0239 0.024 0.0241 0.0241 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.27
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b5e059d0> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0241 0.0237 0.0241 0.0239 0.0241 ...
##   .. ..$ pce    : num [1:12] 676 679 682 689 691 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b5e059d0> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1972:List of 12
##   ..$ coefficients : Named num [1:2] 4.40e-02 -2.71e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -2.07e-04 -5.31e-04 3.30e-04 2.16e-05 -2.40e-05 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -8.05e-02 -2.19e-03 4.26e-04 1.02e-04 3.13e-05 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0242 0.0241 0.0238 0.0237 0.0235 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.29
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b5ce8448> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.024 0.0236 0.0241 0.0237 0.0235 ...
##   .. ..$ pce    : num [1:12] 732 736 749 752 758 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b5ce8448> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1973:List of 12
##   ..$ coefficients : Named num [1:2] 2.57e-02 -6.05e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.000273 0.000367 0.000121 0.00043 -0.000165 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.071281 -0.000404 0.000134 0.000458 -0.000106 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0208 0.0207 0.0207 0.0207 0.0206 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.24
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b5c182e0> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0205 0.0211 0.0208 0.0211 0.0205 ...
##   .. ..$ pce    : num [1:12] 816 826 833 836 842 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b5c182e0> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1974:List of 12
##   ..$ coefficients : Named num [1:2] -5.07e-02 8.05e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 0.001297 0.001272 -0.000139 -0.000986 -0.001528 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.08379 0.007552 -0.000576 -0.001349 -0.001799 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0205 0.0209 0.0219 0.0226 0.0236 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.32
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b5b967a8> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0218 0.0222 0.0217 0.0216 0.022 ...
##   .. ..$ pce    : num [1:12] 884 890 901 911 922 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b5b967a8> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1975:List of 12
##   ..$ coefficients : Named num [1:2] 3.85e-02 -1.64e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.001967 -0.001878 0.000231 0.001289 0.002333 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.127397 -0.000204 0.000931 0.001948 0.002767 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0369 0.0368 0.0368 0.0368 0.0368 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.23
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b5a09aa8> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0349 0.035 0.0371 0.0381 0.0391 ...
##   .. ..$ pce    : num [1:12] 976 989 991 995 1019 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b5a09aa8> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1976:List of 12
##   ..$ coefficients : Named num [1:2] 2.31e-02 9.41e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 1.15e-03 1.62e-04 -3.68e-04 -2.95e-05 -1.30e-03 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.117558 0.00106 -0.00061 -0.000278 -0.001548 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0336 0.0336 0.0336 0.0337 0.0337 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.27
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b580b190> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0347 0.0337 0.0333 0.0337 0.0324 ...
##   .. ..$ pce    : num [1:12] 1107 1108 1115 1125 1123 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b580b190> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1977:List of 12
##   ..$ coefficients : Named num [1:2] 7.45e-02 -3.37e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.000415 0.000852 0.000444 -0.000409 -0.000778 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.109618 -0.004303 0.000402 -0.000398 -0.000707 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0336 0.0331 0.0328 0.0325 0.0322 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.23
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b56decb8> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0332 0.0339 0.0333 0.0321 0.0314 ...
##   .. ..$ pce    : num [1:12] 1215 1231 1238 1247 1257 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b56decb8> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1978:List of 12
##   ..$ coefficients : Named num [1:2] 4.42e-02 -1.15e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 4.25e-04 -7.19e-05 2.51e-04 -2.64e-04 -3.46e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.096321 -0.00194 0.000174 -0.000356 -0.00045 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0289 0.0286 0.0283 0.0281 0.0279 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.28
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b5465260> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0293 0.0285 0.0286 0.0278 0.0276 ...
##   .. ..$ pce    : num [1:12] 1330 1355 1378 1396 1412 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b5465260> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1979:List of 12
##   ..$ coefficients : Named num [1:2] 1.93e-02 5.01e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 4.38e-04 6.24e-04 2.49e-04 9.64e-06 -1.14e-03 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -9.45e-02 9.45e-04 7.17e-05 -1.51e-04 -1.25e-03 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0269 0.0269 0.027 0.027 0.0271 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.26
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b5266640> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0273 0.0276 0.0272 0.027 0.026 ...
##   .. ..$ pce    : num [1:12] 1502 1518 1531 1538 1559 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b5266640> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1980:List of 12
##   ..$ coefficients : Named num [1:2] -7.45e-03 2.35e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -2.93e-03 -2.97e-03 -3.03e-03 1.61e-05 2.63e-03 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.11672 0.00441 -0.00206 0.00112 0.00368 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0324 0.0325 0.0327 0.0324 0.0325 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.2
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b505b2f8> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0295 0.0296 0.0297 0.0324 0.0351 ...
##   .. ..$ pce    : num [1:12] 1697 1701 1708 1695 1700 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b505b2f8> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1981:List of 12
##   ..$ coefficients : Named num [1:2] -2.49e-02 3.15e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 0.001276 0.00072 -0.000193 -0.00076 0.000246 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.124684 0.004009 -0.000524 -0.001087 -0.000055 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.034 0.0344 0.035 0.0351 0.0354 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.28
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c5ddc8f8> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0353 0.0351 0.0348 0.0343 0.0356 ...
##   .. ..$ pce    : num [1:12] 1870 1884 1903 1904 1914 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c5ddc8f8> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1982:List of 12
##   ..$ coefficients : Named num [1:2] -8.88e-02 6.52e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.000667 -0.000933 -0.00033 0.001001 0.000176 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -1.60e-01 1.16e-02 -6.76e-05 1.26e-03 3.63e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0413 0.0429 0.0431 0.0432 0.0444 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.19
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c5cffcf0> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0407 0.042 0.0427 0.0442 0.0446 ...
##   .. ..$ pce    : num [1:12] 1997 2021 2024 2026 2044 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c5cffcf0> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1983:List of 12
##   ..$ coefficients : Named num [1:2] 0.146101 -0.000044
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.000964 -0.000816 -0.000297 0.000108 0.00045 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.158172 -0.011088 0.000018 0.00038 0.000687 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0504 0.0503 0.0491 0.0481 0.0472 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.32
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c5c13498> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0494 0.0494 0.0488 0.0482 0.0477 ...
##   .. ..$ pce    : num [1:12] 2174 2177 2203 2226 2246 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c5c13498> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1984:List of 12
##   ..$ coefficients : Named num [1:2] 7.89e-02 -1.72e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 9.20e-04 -2.97e-04 -2.89e-05 4.58e-04 -5.71e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.125039 -0.003282 -0.00015 0.000287 -0.000774 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0373 0.0376 0.0371 0.0367 0.0364 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.38
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c5b71150> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0383 0.0373 0.0371 0.0372 0.0358 ...
##   .. ..$ pce    : num [1:12] 2419 2404 2432 2458 2474 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c5b71150> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1985:List of 12
##   ..$ coefficients : Named num [1:2] 5.37e-02 -6.93e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -5.19e-05 -3.49e-04 -2.39e-04 4.79e-05 -1.13e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.120795 -0.00147 -0.000172 0.000101 -0.000107 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0355 0.0354 0.0353 0.0352 0.035 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.24
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c5af17e0> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0355 0.035 0.0351 0.0353 0.0349 ...
##   .. ..$ pce    : num [1:12] 2619 2641 2648 2660 2696 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c5af17e0> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1986:List of 12
##   ..$ coefficients : Named num [1:2] 5.38e-02 -6.78e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.002143 0.000321 0.000244 0.00022 0.000657 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.118716 -0.001349 0.000567 0.000579 0.001088 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0347 0.0347 0.0347 0.0346 0.0345 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.27
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c5a958f8> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0325 0.035 0.0349 0.0348 0.0351 ...
##   .. ..$ pce    : num [1:12] 2827 2820 2824 2835 2858 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c5a958f8> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1987:List of 12
##   ..$ coefficients : Named num [1:2] 9.15e-02 -1.98e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.00069 0.000489 0.000687 -0.000152 0.000148 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -1.06e-01 -4.64e-03 7.68e-04 -1.16e-05 3.11e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0333 0.032 0.0318 0.0313 0.0311 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.18
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c59ef660> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0326 0.0325 0.0325 0.0311 0.0312 ...
##   .. ..$ pce    : num [1:12] 2936 3002 3013 3039 3048 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c59ef660> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1988:List of 12
##   ..$ coefficients : Named num [1:2] 5.12e-02 -7.17e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 0.000326 0.000265 0.000311 -0.000815 0.000114 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -9.47e-02 -1.95e-03 2.15e-04 -9.10e-04 3.56e-05 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0282 0.0281 0.0278 0.0278 0.0276 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.3
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c5971ba0> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0285 0.0284 0.0281 0.027 0.0277 ...
##   .. ..$ pce    : num [1:12] 3214 3221 3260 3263 3294 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c5971ba0> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1989:List of 12
##   ..$ coefficients : Named num [1:2] 1.05e-02 4.44e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 1.17e-03 -1.76e-04 -8.65e-04 -1.46e-05 -4.50e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.091384 0.000969 -0.00104 -0.000257 -0.000706 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.026 0.026 0.026 0.0262 0.0263 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.31
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c591be40> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0271 0.0258 0.0252 0.0262 0.0258 ...
##   .. ..$ pce    : num [1:12] 3484 3488 3499 3543 3552 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c591be40> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1990:List of 12
##   ..$ coefficients : Named num [1:2] -7.12e-02 2.61e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 9.66e-04 6.07e-04 -3.23e-04 4.93e-05 -3.51e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.097801 0.004826 -0.000597 -0.000201 -0.000592 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0262 0.0261 0.0268 0.0272 0.0274 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.34
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c58c8b00> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0272 0.0267 0.0265 0.0273 0.027 ...
##   .. ..$ pce    : num [1:12] 3731 3728 3755 3770 3776 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c58c8b00> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1991:List of 12
##   ..$ coefficients : Named num [1:2] -3.86e-02 1.84e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -3.86e-04 1.01e-04 4.89e-04 -2.06e-05 6.37e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -1.18e-01 3.31e-03 5.69e-04 5.51e-05 7.34e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0322 0.0327 0.0335 0.0334 0.0339 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.3
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c5838630> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0318 0.0328 0.034 0.0334 0.0345 ...
##   .. ..$ pce    : num [1:12] 3841 3867 3913 3907 3933 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4c5838630> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1992:List of 12
##   ..$ coefficients : Named num [1:2] 3.49e-02 6.09e-07
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.000987 -0.00036 -0.000385 -0.000611 0.000614 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.12966 0.000169 -0.000141 -0.000373 0.000841 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0374 0.0374 0.0374 0.0374 0.0374 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.26
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe5070ec858> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0364 0.037 0.037 0.0368 0.038 ...
##   .. ..$ pce    : num [1:12] 4085 4100 4117 4132 4158 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe5070ec858> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1993:List of 12
##   ..$ coefficients : Named num [1:2] 9.54e-02 -1.37e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 2.04e-04 -1.77e-04 -7.38e-04 -3.91e-06 5.08e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -1.19e-01 -3.68e-03 -7.35e-04 -2.76e-05 4.65e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0358 0.0356 0.0357 0.0351 0.0347 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.27
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4e55198f8> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.036 0.0355 0.0349 0.0351 0.0352 ...
##   .. ..$ pce    : num [1:12] 4341 4355 4352 4393 4422 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4e55198f8> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1994:List of 12
##   ..$ coefficients : Named num [1:2] 1.3e-01 -2.1e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.000201 0.000593 0.000415 0.000379 -0.001266 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.104941 -0.005787 0.000375 0.000387 -0.001262 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0332 0.0322 0.0319 0.0313 0.0314 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.21
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4e54b9a10> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0329 0.0327 0.0323 0.0317 0.0301 ...
##   .. ..$ pce    : num [1:12] 4585 4633 4646 4671 4670 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4e54b9a10> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1995:List of 12
##   ..$ coefficients : Named num [1:2] 2.40e-02 7.72e-07
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 0.000114 -0.000618 -0.000796 0.001025 0.000158 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.096293 0.000207 -0.000727 0.001086 0.00014 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0277 0.0277 0.0277 0.0277 0.0278 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.32
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4e5460200> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0278 0.0271 0.0269 0.0288 0.0279 ...
##   .. ..$ pce    : num [1:12] 4851 4851 4885 4890 4933 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4e5460200> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1996:List of 12
##   ..$ coefficients : Named num [1:2] 5.60e-02 -5.57e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 2.26e-04 -1.97e-04 2.33e-05 5.51e-04 6.43e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -9.29e-02 -1.62e-03 -3.18e-06 5.01e-04 5.82e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0277 0.0274 0.0272 0.027 0.0269 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.26
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4e53e2708> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0279 0.0273 0.0272 0.0276 0.0276 ...
##   .. ..$ pce    : num [1:12] 5086 5133 5173 5208 5224 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4e53e2708> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1997:List of 12
##   ..$ coefficients : Named num [1:2] 7.97e-02 -9.94e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 0.000463 0.000462 0.000265 -0.000176 -0.000991 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.085448 -0.003197 0.000112 -0.000324 -0.001139 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0259 0.0257 0.0255 0.0254 0.0254 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.23
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4e5393460> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0264 0.0262 0.0258 0.0253 0.0244 ...
##   .. ..$ pce    : num [1:12] 5411 5434 5454 5459 5460 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4e5393460> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1998:List of 12
##   ..$ coefficients : Named num [1:2] 3.59e-02 -2.28e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 0.000283 0.000117 0.000582 -0.0011 -0.000622 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.077862 -0.00093 0.00051 -0.001169 -0.000686 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0229 0.0228 0.0228 0.0227 0.0226 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.27
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4e5326820> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0232 0.0229 0.0233 0.0216 0.0219 ...
##   .. ..$ pce    : num [1:12] 5690 5724 5750 5788 5838 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4e5326820> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 1999:List of 12
##   ..$ coefficients : Named num [1:2] 3.92e-02 -2.89e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.000142 0.000412 -0.000693 0.000265 -0.000417 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.072946 -0.001374 -0.000735 0.000269 -0.00039 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0217 0.0216 0.0215 0.0213 0.0212 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.28
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4f57c6740> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0215 0.022 0.0208 0.0216 0.0208 ...
##   .. ..$ pce    : num [1:12] 6073 6102 6133 6196 6226 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4f57c6740> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 2000:List of 12
##   ..$ coefficients : Named num [1:2] 3.1e-02 -1.6e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.000188 0.000465 0.000111 -0.000825 0.000201 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.069765 -0.000669 0.000127 -0.000823 0.000239 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0205 0.0204 0.0203 0.0203 0.0202 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.22
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4f5780e30> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0203 0.0208 0.0204 0.0195 0.0204 ...
##   .. ..$ pce    : num [1:12] 6535 6620 6686 6671 6708 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4f5780e30> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 2001:List of 12
##   ..$ coefficients : Named num [1:2] -0.18813 0.00003
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -6.43e-05 -4.13e-04 -8.60e-06 3.15e-05 -1.52e-03 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -8.29e-02 7.69e-03 8.11e-05 1.04e-04 -1.51e-03 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0213 0.0218 0.0216 0.022 0.0234 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.2
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4f56f15d8> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0212 0.0214 0.0216 0.022 0.0219 ...
##   .. ..$ pce    : num [1:12] 6977 6996 6988 7001 7047 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4f56f15d8> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 2002:List of 12
##   ..$ coefficients : Named num [1:2] 1.43e-02 2.01e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -2.10e-04 -2.04e-04 4.85e-05 9.17e-04 2.44e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.100731 0.000692 0.00012 0.000964 0.000299 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0287 0.0288 0.0289 0.029 0.029 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.25
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4f538e5f8> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0285 0.0286 0.0289 0.0299 0.0292 ...
##   .. ..$ pce    : num [1:12] 7174 7218 7237 7305 7283 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4f538e5f8> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 2003:List of 12
##   ..$ coefficients : Named num [1:2] 4.03e-02 -1.31e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.000987 -0.000665 -0.000707 0.000176 0.000559 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.104501 -0.000616 -0.000427 0.00044 0.000817 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0304 0.0304 0.0303 0.0303 0.0303 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.31
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe50649d6d8> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0294 0.0297 0.0296 0.0305 0.0308 ...
##   .. ..$ pce    : num [1:12] 7533 7536 7598 7621 7628 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe50649d6d8> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 2004:List of 12
##   ..$ coefficients : Named num [1:2] 5.76e-02 -3.64e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 8.04e-05 -5.13e-04 7.80e-04 -2.92e-04 1.02e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -9.61e-02 -1.94e-03 8.30e-04 -2.52e-04 8.35e-05 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0286 0.0284 0.0282 0.0282 0.0279 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.27
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe51575aea8> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0286 0.0279 0.029 0.0279 0.028 ...
##   .. ..$ pce    : num [1:12] 7987 8020 8076 8089 8163 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe51575aea8> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 2005:List of 12
##   ..$ coefficients : Named num [1:2] 5.78e-02 -3.68e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -2.22e-04 6.42e-04 -4.89e-05 -6.86e-06 -1.03e-04 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -8.87e-02 -2.11e-03 -1.09e-04 5.32e-06 -9.24e-05 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0266 0.0264 0.0263 0.026 0.026 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.27
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe5055a8d98> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0264 0.027 0.0262 0.026 0.0259 ...
##   .. ..$ pce    : num [1:12] 8470 8529 8570 8646 8644 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe5055a8d98> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 2006:List of 12
##   ..$ coefficients : Named num [1:2] 5.46e-02 -3.37e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.000332 0.000157 -0.000128 0.000193 -0.000157 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -8.10e-02 -1.45e-03 -9.23e-05 2.50e-04 -8.33e-05 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0241 0.024 0.0239 0.0237 0.0235 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.29
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe515a21130> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0237 0.0241 0.0237 0.0239 0.0234 ...
##   .. ..$ pce    : num [1:12] 9060 9090 9122 9175 9215 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe515a21130> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 2007:List of 12
##   ..$ coefficients : Named num [1:2] -1.72e-02 4.19e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 0.001044 0.00027 -0.000558 -0.000309 -0.000754 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.081153 0.001834 -0.000797 -0.000546 -0.000988 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0226 0.0228 0.0229 0.023 0.0232 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.27
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe507751868> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0237 0.023 0.0224 0.0227 0.0224 ...
##   .. ..$ pce    : num [1:12] 9516 9547 9585 9616 9651 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe507751868> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 2008:List of 12
##   ..$ coefficients : Named num [1:2] 1.78e-01 -1.49e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.004727 -0.005612 -0.003871 -0.003938 -0.000612 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.101691 -0.005787 -0.002744 -0.003198 -0.000463 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.03 0.0303 0.0296 0.029 0.0282 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.14
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b70bd200> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0253 0.0247 0.0257 0.0251 0.0276 ...
##   .. ..$ pce    : num [1:12] 9930 9913 9959 9997 10054 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b70bd200> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 2009:List of 12
##   ..$ coefficients : Named num [1:2] -1.73e-01 2.23e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -5.82e-03 -2.70e-03 5.17e-05 1.27e-03 2.81e-03 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.16107 0.00727 0.00175 0.00295 0.0044 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0452 0.0448 0.0437 0.0439 0.0444 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.19
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4e57a0530> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0394 0.0421 0.0438 0.0452 0.0472 ...
##   .. ..$ pce    : num [1:12] 9784 9766 9718 9725 9749 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4e57a0530> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 2010:List of 12
##   ..$ coefficients : Named num [1:2] 1.07e-01 -5.84e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.000166 0.000189 0.000789 0.001329 -0.000132 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.165615 -0.002394 0.000802 0.001353 -0.000101 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0489 0.0487 0.0484 0.0482 0.0481 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.28
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4e5636230> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0487 0.0489 0.0492 0.0496 0.048 ...
##   .. ..$ pce    : num [1:12] 10002 10031 10089 10113 10131 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4e5636230> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 2011:List of 12
##   ..$ coefficients : Named num [1:2] 1.04e-01 -5.65e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.000141 -0.000588 -0.000423 0.000469 0.000255 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.152571 -0.002124 -0.000341 0.000509 0.000268 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0452 0.045 0.0446 0.0443 0.0442 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.33
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b72b1070> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0451 0.0444 0.0441 0.0448 0.0445 ...
##   .. ..$ pce    : num [1:12] 10436 10470 10550 10588 10612 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b72b1070> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 2012:List of 12
##   ..$ coefficients : Named num [1:2] 1.58e-01 -1.07e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.000475 0.000534 0.000176 0.000239 0.000144 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.137828 -0.003027 0.000234 0.000357 0.000238 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0413 0.0404 0.0404 0.0401 0.0402 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.07
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b7327c40> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0409 0.0409 0.0406 0.0403 0.0403 ...
##   .. ..$ pce    : num [1:12] 10862 10954 10952 10980 10969 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b7327c40> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 2013:List of 12
##   ..$ coefficients : Named num [1:2] 2.10e-01 -1.54e-05
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] 0.001561 0.000459 -0.000577 -0.000704 -0.000456 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.125478 -0.005544 -0.000944 -0.001076 -0.000819 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.038 0.0374 0.0376 0.0379 0.0373 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.14
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b73ebc80> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0395 0.0379 0.037 0.0372 0.0369 ...
##   .. ..$ pce    : num [1:12] 11203 11240 11227 11205 11245 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b73ebc80> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 2014:List of 12
##   ..$ coefficients : Named num [1:2] 1.32e-01 -8.59e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:12] -0.000692 0.000216 0.000957 -0.00068 0.000189 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ effects      : Named num [1:12] -0.104402 -0.005422 0.001061 -0.000549 0.000341 ...
##   .. ..- attr(*, "names")= chr [1:12] "(Intercept)" "pce" "" "" ...
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:12] 0.0328 0.0324 0.0317 0.0312 0.0308 ...
##   .. ..- attr(*, "names")= chr [1:12] "1" "2" "3" "4" ...
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:12, 1:2] -3.464 0.289 0.289 0.289 0.289 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:12] "1" "2" "3" "4" ...
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.29 1.3
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 10
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b745ae80> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	12 obs. of  2 variables:
##   .. ..$ percent: num [1:12] 0.0321 0.0326 0.0327 0.0305 0.031 ...
##   .. ..$ pce    : num [1:12] 11512 11566 11643 11703 11748 ...
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b745ae80> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
##  $ 2015:List of 12
##   ..$ coefficients : Named num [1:2] 1.18e-01 -7.48e-06
##   .. ..- attr(*, "names")= chr [1:2] "(Intercept)" "pce"
##   ..$ residuals    : Named num [1:4] 0.0003 -0.000356 -0.000132 0.000188
##   .. ..- attr(*, "names")= chr [1:4] "1" "2" "3" "4"
##   ..$ effects      : Named num [1:4] -0.053947 -0.000879 -0.000452 -0.000256
##   .. ..- attr(*, "names")= chr [1:4] "(Intercept)" "pce" "" ""
##   ..$ rank         : int 2
##   ..$ fitted.values: Named num [1:4] 0.0275 0.0273 0.0267 0.0264
##   .. ..- attr(*, "names")= chr [1:4] "1" "2" "3" "4"
##   ..$ assign       : int [1:2] 0 1
##   ..$ qr           :List of 5
##   .. ..$ qr   : num [1:4, 1:2] -2 0.5 0.5 0.5 -24240.2 ...
##   .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. ..$ : chr [1:4] "1" "2" "3" "4"
##   .. .. .. ..$ : chr [1:2] "(Intercept)" "pce"
##   .. .. ..- attr(*, "assign")= int [1:2] 0 1
##   .. ..$ qraux: num [1:2] 1.5 1.11
##   .. ..$ pivot: int [1:2] 1 2
##   .. ..$ tol  : num 1e-07
##   .. ..$ rank : int 2
##   .. ..- attr(*, "class")= chr "qr"
##   ..$ df.residual  : int 2
##   ..$ xlevels      : Named list()
##   ..$ call         : language lm(formula = percent ~ pce, data = .x)
##   ..$ terms        :Classes 'terms', 'formula'  language percent ~ pce
##   .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. ..$ : chr "pce"
##   .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. ..- attr(*, "order")= int 1
##   .. .. ..- attr(*, "intercept")= int 1
##   .. .. ..- attr(*, "response")= int 1
##   .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b74dbfb8> 
##   .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..$ model        :'data.frame':	4 obs. of  2 variables:
##   .. ..$ percent: num [1:4] 0.0278 0.0269 0.0266 0.0266
##   .. ..$ pce    : num [1:4] 12046 12082 12158 12194
##   .. ..- attr(*, "terms")=Classes 'terms', 'formula'  language percent ~ pce
##   .. .. .. ..- attr(*, "variables")= language list(percent, pce)
##   .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
##   .. .. .. .. ..- attr(*, "dimnames")=List of 2
##   .. .. .. .. .. ..$ : chr [1:2] "percent" "pce"
##   .. .. .. .. .. ..$ : chr "pce"
##   .. .. .. ..- attr(*, "term.labels")= chr "pce"
##   .. .. .. ..- attr(*, "order")= int 1
##   .. .. .. ..- attr(*, "intercept")= int 1
##   .. .. .. ..- attr(*, "response")= int 1
##   .. .. .. ..- attr(*, ".Environment")=<environment: 0x7fe4b74dbfb8> 
##   .. .. .. ..- attr(*, "predvars")= language list(percent, pce)
##   .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
##   .. .. .. .. ..- attr(*, "names")= chr [1:2] "percent" "pce"
##   ..- attr(*, "class")= chr "lm"
```

---
# Extract coefficients

### You try first

Hint: use `coef`. For example, see `coef(mods[[1]])`

```r
coefs <- map(mods, coef)
coefs[c(1:2, length(coefs))]
```

```
## $`1967`
##  (Intercept)          pce 
## 8.397192e-03 1.307101e-05 
## 
## $`1968`
##   (Intercept)           pce 
##  2.784626e-02 -2.496983e-05 
## 
## $`2015`
##   (Intercept)           pce 
##  1.176573e-01 -7.482080e-06
```

---
# Extract slopes
AKA - the coefficient that is not the intercept
### You try first

```r
slopes <- map_dbl(coefs, 2)
slopes
```

```
##          1967          1968          1969          1970          1971 
##  1.307101e-05 -2.496983e-05  3.201794e-05  2.136662e-04  1.177357e-05 
##          1972          1973          1974          1975          1976 
## -2.708060e-05 -6.047148e-06  8.050869e-05 -1.643992e-06  9.413733e-06 
##          1977          1978          1979          1980          1981 
## -3.366894e-05 -1.151756e-05  5.011539e-06  2.350410e-05  3.150845e-05 
##          1982          1983          1984          1985          1986 
##  6.516215e-05 -4.402208e-05 -1.718497e-05 -6.926535e-06 -6.782516e-06 
##          1987          1988          1989          1990          1991 
## -1.980421e-05 -7.174276e-06  4.436762e-06  2.611286e-05  1.842612e-05 
##          1992          1993          1994          1995          1996 
##  6.091330e-07 -1.371548e-05 -2.102375e-05  7.718004e-07 -5.567328e-06 
##          1997          1998          1999          2000          2001 
## -9.936855e-06 -2.283149e-06 -2.893646e-06 -1.601844e-06  3.001365e-05 
##          2002          2003          2004          2005          2006 
##  2.014789e-06 -1.306818e-06 -3.640025e-06 -3.679151e-06 -3.368536e-06 
##          2007          2008          2009          2010          2011 
##  4.187576e-06 -1.494605e-05  2.230078e-05 -5.844266e-06 -5.647401e-06 
##          2012          2013          2014          2015 
## -1.070319e-05 -1.536441e-05 -8.590683e-06 -7.482080e-06
```

---
# Plot

* I trust you can do this

```r
relation <- tibble(year = names(slopes),
                   slope = slopes)

ggplot(relation, aes(slope)) +
	geom_histogram(fill = "cornflowerblue",
	               color = "white")
```

![](w3p1_files/figure-html/plot-slopes-1.png)

---
# Piping
We could also have done the previous in a pipeline.

```r
by_year %>%
	map(~mutate(.x, percent = unemploy / pop))
```

```
## $`1967`
## # A tibble: 6 x 8
##   date         pce    pop psavert  uempmed unemploy  year    percent
##   <date>     <dbl>  <dbl>   <dbl>    <dbl>    <dbl> <dbl>      <dbl>
## 1 1967-07-01 506.7 198712    12.6 4.5          2944  1967 0.01481541
## 2 1967-08-01 509.8 198911    12.6 4.7          2945  1967 0.01480562
## 3 1967-09-01 515.6 199113    11.9 4.600000     2958  1967 0.01485589
## 4 1967-10-01 512.2 199311    12.9 4.9          3143  1967 0.01576933
## 5 1967-11-01 517.4 199498    12.8 4.7          3066  1967 0.01536858
## 6 1967-12-01 525.1 199657    11.8 4.8          3018  1967 0.01511592
## 
## $`1968`
## # A tibble: 12 x 8
##    date           pce    pop psavert  uempmed unemploy  year    percent
##    <date>       <dbl>  <dbl>   <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 1968-01-01 530.9   199808    11.7 5.100000     2878  1968 0.01440383
##  2 1968-02-01 533.6   199920    12.3 4.5          3001  1968 0.01501100
##  3 1968-03-01 544.300 200056    11.7 4.100000     2877  1968 0.01438097
##  4 1968-04-01 544     200208    12.3 4.600000     2709  1968 0.01353093
##  5 1968-05-01 549.800 200361    12   4.4          2740  1968 0.01367532
##  6 1968-06-01 556.300 200536    11.7 4.4          2938  1968 0.01465074
##  7 1968-07-01 563.2   200706    10.7 4.5          2883  1968 0.01436429
##  8 1968-08-01 567     200898    10.5 4.2          2768  1968 0.01377814
##  9 1968-09-01 568.2   201095    10.6 4.600000     2686  1968 0.01335687
## 10 1968-10-01 571.6   201290    10.8 4.8          2689  1968 0.01335884
## 11 1968-11-01 576.7   201466    10.6 4.4          2715  1968 0.01347622
## 12 1968-12-01 576.5   201621    11.1 4.4          2685  1968 0.01331707
## 
## $`1969`
## # A tibble: 12 x 8
##    date           pce    pop   psavert  uempmed unemploy  year    percent
##    <date>       <dbl>  <dbl>     <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 1969-01-01 583.5   201760 10.3      4.4          2718  1969 0.01347145
##  2 1969-02-01 588.7   201881  9.700000 4.9          2692  1969 0.01333459
##  3 1969-03-01 588.9   202023 10.200    4            2712  1969 0.01342421
##  4 1969-04-01 593.9   202161  9.700000 4            2758  1969 0.01364259
##  5 1969-05-01 600.300 202331 10.1      4.2          2713  1969 0.01340872
##  6 1969-06-01 600.9   202507 11.1      4.4          2816  1969 0.01390569
##  7 1969-07-01 602.7   202677 11.8      4.4          2868  1969 0.01415059
##  8 1969-08-01 609.9   202877 11.5      4.4          2856  1969 0.01407750
##  9 1969-09-01 613.2   203090 11.6      4.7          3040  1969 0.01496873
## 10 1969-10-01 618.5   203302 11.4      4.5          3049  1969 0.01499739
## 11 1969-11-01 620.5   203500 11.6      4.8          2856  1969 0.01403440
## 12 1969-12-01 622.800 203675 11.8      4.600000     2884  1969 0.01415981
## 
## $`1970`
## # A tibble: 12 x 8
##    date           pce    pop psavert  uempmed unemploy  year    percent
##    <date>       <dbl>  <dbl>   <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 1970-01-01 628.7   203849    11.8 4.600000     3201  1970 0.01570280
##  2 1970-02-01 634     204008    11.7 4.5          3453  1970 0.01692581
##  3 1970-03-01 632.300 204156    12.4 4.600000     3635  1970 0.01780501
##  4 1970-04-01 636     204401    13.3 4.100000     3797  1970 0.01857623
##  5 1970-05-01 642.4   204607    12.4 4.7          3919  1970 0.01915379
##  6 1970-06-01 646.300 204830    12.3 4.9          4071  1970 0.01987502
##  7 1970-07-01 648.5   205052    13.5 5.100000     4175  1970 0.02036069
##  8 1970-08-01 652.9   205295    13.4 5.4          4256  1970 0.02073114
##  9 1970-09-01 659.1   205540    12.9 5.2          4456  1970 0.02167948
## 10 1970-10-01 658.3   205788    13.1 5.2          4591  1970 0.02230937
## 11 1970-11-01 656.6   206024    13.6 5.6          4898  1970 0.02377393
## 12 1970-12-01 665.6   206238    13.2 5.9          5076  1970 0.02461234
## 
## $`1971`
## # A tibble: 12 x 8
##    date         pce    pop psavert uempmed unemploy  year    percent
##    <date>     <dbl>  <dbl>   <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 1971-01-01 676.1 206466    13.3     6.2     4986  1971 0.02414925
##  2 1971-02-01 679.4 206668    13.3     6.3     4903  1971 0.02372404
##  3 1971-03-01 682   206855    13.5     6.4     4987  1971 0.02410868
##  4 1971-04-01 688.8 207065    13.2     6.5     4959  1971 0.02394900
##  5 1971-05-01 691.1 207260    13.6     6.7     4996  1971 0.02410499
##  6 1971-06-01 699.8 207462    14.7     5.7     4949  1971 0.02385497
##  7 1971-07-01 698.9 207661    13.8     6.2     5035  1971 0.02424625
##  8 1971-08-01 704.9 207881    13.6     6.4     5134  1971 0.02469682
##  9 1971-09-01 713   208114    13.3     5.8     5042  1971 0.02422711
## 10 1971-10-01 715.8 208345    13.3     6.5     4954  1971 0.02377787
## 11 1971-11-01 720.9 208555    13.1     6.4     5161  1971 0.02474647
## 12 1971-12-01 728.4 208740    13       6.2     5154  1971 0.02469100
## 
## $`1972`
## # A tibble: 12 x 8
##    date         pce    pop psavert uempmed unemploy  year    percent
##    <date>     <dbl>  <dbl>   <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 1972-01-01 731.5 208917    12.5     6.2     5019  1972 0.02402389
##  2 1972-02-01 736.2 209061    12.8     6.6     4928  1972 0.02357207
##  3 1972-03-01 749.2 209212    11.8     6.6     5038  1972 0.02408084
##  4 1972-04-01 752.5 209386    11.5     6.7     4959  1972 0.02368353
##  5 1972-05-01 758   209545    11.7     6.6     4922  1972 0.02348899
##  6 1972-06-01 761.6 209725    11.7     5.4     4923  1972 0.02347360
##  7 1972-07-01 769.9 209896    11.7     6.1     4913  1972 0.02340683
##  8 1972-08-01 776.3 210075    12       6       4939  1972 0.02351065
##  9 1972-09-01 781.1 210278    12.2     5.6     4849  1972 0.02305995
## 10 1972-10-01 794.9 210479    13       5.7     4875  1972 0.02316146
## 11 1972-11-01 800.5 210656    13.6     5.7     4602  1972 0.02184604
## 12 1972-12-01 806.1 210821    13.7     6.1     4543  1972 0.02154909
## 
## $`1973`
## # A tibble: 12 x 8
##    date         pce    pop psavert  uempmed unemploy  year    percent
##    <date>     <dbl>  <dbl>   <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 1973-01-01 816.5 210985    12.4 5.7          4326  1973 0.02050383
##  2 1973-02-01 825.8 211120    12.5 5.2          4452  1973 0.02108753
##  3 1973-03-01 832.8 211254    12.7 5.5          4394  1973 0.02079961
##  4 1973-04-01 835.7 211420    13.2 5            4459  1973 0.02109072
##  5 1973-05-01 841.6 211577    13.2 4.9          4329  1973 0.02046064
##  6 1973-06-01 844.3 211746    13.6 5            4363  1973 0.02060488
##  7 1973-07-01 854.1 211909    13.2 5.2          4305  1973 0.02031532
##  8 1973-08-01 853.3 212092    13.9 4.9          4305  1973 0.02029780
##  9 1973-09-01 869.2 212289    13.1 5.4          4350  1973 0.02049093
## 10 1973-10-01 868.2 212475    14.4 5.5          4144  1973 0.01950347
## 11 1973-11-01 876.9 212634    14.4 5.100000     4396  1973 0.02067402
## 12 1973-12-01 876.6 212785    14.8 4.7          4489  1973 0.02109641
## 
## $`1974`
## # A tibble: 12 x 8
##    date         pce    pop psavert  uempmed unemploy  year    percent
##    <date>     <dbl>  <dbl>   <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 1974-01-01 884.5 212932    14.3 5            4644  1974 0.02180978
##  2 1974-02-01 889.7 213074    14.2 5.100000     4731  1974 0.02220355
##  3 1974-03-01 901.4 213211    13.4 4.8          4634  1974 0.02173434
##  4 1974-04-01 910.8 213361    13.1 5            4618  1974 0.02164407
##  5 1974-05-01 922.4 213513    12.8 4.600000     4705  1974 0.02203613
##  6 1974-06-01 928   213686    12.8 5.3          4927  1974 0.02305720
##  7 1974-07-01 937.9 213854    12.8 5.7          5063  1974 0.02367503
##  8 1974-08-01 954.8 214042    12.1 5            5022  1974 0.02346268
##  9 1974-09-01 955.1 214246    12.9 5.3          5437  1974 0.02537737
## 10 1974-10-01 959.2 214451    13.4 5.5          5523  1974 0.02575413
## 11 1974-11-01 956.2 214625    13.8 5.2          6140  1974 0.02860804
## 12 1974-12-01 961.8 214782    14   5.7          6636  1974 0.03089644
## 
## $`1975`
## # A tibble: 12 x 8
##    date            pce    pop psavert  uempmed unemploy  year    percent
##    <date>        <dbl>  <dbl>   <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 1975-01-01  975.6   214931    13.2 6.3          7501  1975 0.03489957
##  2 1975-02-01  989.4   215065    12.5 7.1          7520  1975 0.03496617
##  3 1975-03-01  990.6   215198    12.7 7.2          7978  1975 0.03707284
##  4 1975-04-01  995     215353    14.2 8.700000     8210  1975 0.03812345
##  5 1975-05-01 1018.9   215523    17.3 9.4          8433  1975 0.03912807
##  6 1975-06-01 1026.8   215768    14.3 8.8          8220  1975 0.03809647
##  7 1975-07-01 1039.8   215973    12.6 8.6          8127  1975 0.03762970
##  8 1975-08-01 1047     216195    13   9.200000     7928  1975 0.03667060
##  9 1975-09-01 1054.8   216393    13   9.200000     7923  1975 0.03661394
## 10 1975-10-01 1060.9   216587    13.4 8.6          7897  1975 0.03646110
## 11 1975-11-01 1075.8   216771    12.7 9.5          7794  1975 0.03595499
## 12 1975-12-01 1092.100 216931    12   9            7744  1975 0.03569799
## 
## $`1976`
## # A tibble: 12 x 8
##    date            pce    pop psavert  uempmed unemploy  year    percent
##    <date>        <dbl>  <dbl>   <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 1976-01-01 1107.100 217095    11.7 9            7534  1976 0.03470370
##  2 1976-02-01 1107.7   217249    12.3 8.200000     7326  1976 0.03372167
##  3 1976-03-01 1114.9   217381    12.2 8.700000     7230  1976 0.03325958
##  4 1976-04-01 1125.4   217528    11.7 8.200000     7330  1976 0.03369681
##  5 1976-05-01 1122.7   217685    12.3 8.3          7053  1976 0.03240003
##  6 1976-06-01 1140.5   217861    11.4 7.8          7322  1976 0.03360859
##  7 1976-07-01 1149.600 218035    11.7 7.7          7490  1976 0.03435228
##  8 1976-08-01 1158     218233    11.7 7.9          7518  1976 0.03444942
##  9 1976-09-01 1168.8   218440    11.4 7.8          7380  1976 0.03378502
## 10 1976-10-01 1176.8   218644    11.1 7.7          7430  1976 0.03398218
## 11 1976-11-01 1189     218834    11.4 8.4          7620  1976 0.03482091
## 12 1976-12-01 1211.5   219006    10.6 8            7545  1976 0.03445111
## 
## $`1977`
## # A tibble: 12 x 8
##    date            pce    pop psavert uempmed unemploy  year    percent
##    <date>        <dbl>  <dbl>   <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 1977-01-01 1215     219179    10.6     7.5     7280  1977 0.03321486
##  2 1977-02-01 1231.3   219344     9.3     7.2     7443  1977 0.03393300
##  3 1977-03-01 1238.3   219504    10.5     7.2     7307  1977 0.03328869
##  4 1977-04-01 1247.3   219684    10.5     7.3     7059  1977 0.03213252
##  5 1977-05-01 1257.100 219859    10.3     7.9     6911  1977 0.03143378
##  6 1977-06-01 1263.600 220046    10.6     6.2     7134  1977 0.03242049
##  7 1977-07-01 1280.5   220239    10.5     7.1     6829  1977 0.03100722
##  8 1977-08-01 1285.7   220458    10.9     7       6925  1977 0.03141188
##  9 1977-09-01 1294.5   220688    11.1     6.7     6751  1977 0.03059070
## 10 1977-10-01 1311.4   220904    11       6.9     6763  1977 0.03061511
## 11 1977-11-01 1327     221109    11.2     7       6815  1977 0.03082190
## 12 1977-12-01 1336     221303    11.4     6.8     6386  1977 0.02885636
## 
## $`1978`
## # A tibble: 12 x 8
##    date          pce    pop psavert uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>   <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 1978-01-01 1329.5 221477    11.9     6.5     6489  1978 0.02929875
##  2 1978-02-01 1355.1 221629    11.1     6.7     6318  1978 0.02850710
##  3 1978-03-01 1377.5 221792    11       6.2     6337  1978 0.02857182
##  4 1978-04-01 1396.4 221991    10.8     6.1     6180  1978 0.02783897
##  5 1978-05-01 1412   222176    10.3     5.7     6127  1978 0.02757724
##  6 1978-06-01 1425.8 222379    10       6       6028  1978 0.02710688
##  7 1978-07-01 1426.8 222585    10.9     5.8     6309  1978 0.02834423
##  8 1978-08-01 1447   222805    10.5     5.8     6080  1978 0.02728844
##  9 1978-09-01 1452.9 223053    10.6     5.6     6125  1978 0.02745984
## 10 1978-10-01 1466.9 223271    10.7     5.9     5947  1978 0.02663579
## 11 1978-11-01 1480.6 223477    10.5     5.5     6077  1978 0.02719295
## 12 1978-12-01 1496.5 223670    10.4     5.6     6228  1978 0.02784459
## 
## $`1979`
## # A tibble: 12 x 8
##    date          pce    pop   psavert uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>     <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 1979-01-01 1502.4 223865 11.1          5.9     6109  1979 0.02728877
##  2 1979-02-01 1517.8 224053 11.1          5.9     6173  1979 0.02755152
##  3 1979-03-01 1531.2 224235 11.2          5.9     6109  1979 0.02724374
##  4 1979-04-01 1538.4 224438 11            5.4     6069  1979 0.02704088
##  5 1979-05-01 1558.8 224632 10.3          5.6     5840  1979 0.02599808
##  6 1979-06-01 1575.7 224843  9.9          5.6     5959  1979 0.02650294
##  7 1979-07-01 1586.1 225055 10.6          5.9     5996  1979 0.02664238
##  8 1979-08-01 1615.6 225295  9.700000     4.8     6320  1979 0.02805211
##  9 1979-09-01 1633.9 225547  9.4          5.5     6190  1979 0.02744439
## 10 1979-10-01 1641.6 225801  9.700000     5.5     6296  1979 0.02788296
## 11 1979-11-01 1657.3 226027  9.700000     5.3     6238  1979 0.02759847
## 12 1979-12-01 1666.3 226243 10.1          5.7     6325  1979 0.02795667
## 
## $`1980`
## # A tibble: 12 x 8
##    date          pce    pop psavert uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>   <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 1980-01-01 1697.3 226451   9.9       5.3     6683  1980 0.02951190
##  2 1980-02-01 1701.4 226656  10.1       5.8     6702  1980 0.02956904
##  3 1980-03-01 1708.2 226849  10.200     6       6729  1980 0.02966290
##  4 1980-04-01 1695.2 227061  11.3       5.8     7358  1980 0.03240539
##  5 1980-05-01 1700.1 227251  11.4       5.7     7984  1980 0.03513296
##  6 1980-06-01 1718.8 227522  11.2       6.4     8098  1980 0.03559216
##  7 1980-07-01 1747.1 227726  11.3       7       8363  1980 0.03672396
##  8 1980-08-01 1763.8 227953  11.3       7.5     8281  1980 0.03632766
##  9 1980-09-01 1780.5 228186  11.7       7.7     8021  1980 0.03515115
## 10 1980-10-01 1817.1 228417  11.3       7.5     8088  1980 0.03540892
## 11 1980-11-01 1826.8 228612  11.6       7.7     8023  1980 0.03509440
## 12 1980-12-01 1851.7 228779  11.4       7.5     7718  1980 0.03373561
## 
## $`1981`
## # A tibble: 12 x 8
##    date          pce    pop psavert uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>   <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 1981-01-01 1870   228937    10.9     7.4     8071  1981 0.03525424
##  2 1981-02-01 1884.2 229071    10.8     7.1     8051  1981 0.03514631
##  3 1981-03-01 1902.9 229224    10.8     7.1     7982  1981 0.03482183
##  4 1981-04-01 1904.4 229403    10.9     7.4     7869  1981 0.03430208
##  5 1981-05-01 1913.8 229575    11       6.9     8174  1981 0.03560492
##  6 1981-06-01 1934.5 229761    10.8     6.6     8098  1981 0.03524532
##  7 1981-07-01 1942.1 229966    12.3     7.1     7863  1981 0.03419201
##  8 1981-08-01 1966.6 230187    12       7.2     8036  1981 0.03491075
##  9 1981-09-01 1965.5 230412    12.4     6.8     8230  1981 0.03571863
## 10 1981-10-01 1963.9 230641    13       6.8     8646  1981 0.03748683
## 11 1981-11-01 1970.6 230822    13.2     6.9     9029  1981 0.03911672
## 12 1981-12-01 1988.8 230989    12.5     6.9     9267  1981 0.04011879
## 
## $`1982`
## # A tibble: 12 x 8
##    date            pce    pop psavert   uempmed unemploy  year    percent
##    <date>        <dbl>  <dbl>   <dbl>     <dbl>    <dbl> <dbl>      <dbl>
##  1 1982-01-01 1997.1   231157    12.7  7.1          9397  1982 0.04065202
##  2 1982-02-01 2021.2   231313    12.1  7.5          9705  1982 0.04195614
##  3 1982-03-01 2024.1   231470    12.2  7.7          9895  1982 0.04274852
##  4 1982-04-01 2026.3   231645    12.9  8.1         10244  1982 0.04422284
##  5 1982-05-01 2044.5   231809    12.3  8.5         10335  1982 0.04458412
##  6 1982-06-01 2048.1   231992    12.3  9.5         10538  1982 0.04542398
##  7 1982-07-01 2072.200 232188    12.5  8.5         10849  1982 0.04672507
##  8 1982-08-01 2080.1   232392    12.6  8.700000    10881  1982 0.04682175
##  9 1982-09-01 2104.6   232599    11.8  9.5         11217  1982 0.04822463
## 10 1982-10-01 2125.8   232816    11.3  9.700000    11529  1982 0.04951979
## 11 1982-11-01 2149.3   232993    10.9 10           11938  1982 0.05123759
## 12 1982-12-01 2161.6   233160    10.9 10.200       12051  1982 0.05168554
## 
## $`1983`
## # A tibble: 12 x 8
##    date          pce    pop   psavert   uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>     <dbl>     <dbl>    <dbl> <dbl>      <dbl>
##  1 1983-01-01 2174   233322 11.1      11.1         11534  1983 0.04943383
##  2 1983-02-01 2177   233473 11.1       9.8         11545  1983 0.04944897
##  3 1983-03-01 2202.8 233613 10.6      10.4         11408  1983 0.04883290
##  4 1983-04-01 2226.4 233781 10.3      10.9         11268  1983 0.04819896
##  5 1983-05-01 2245.9 233922  9.9      12.3         11154  1983 0.04768256
##  6 1983-06-01 2276   234118  9.1      11.3         11246  1983 0.04803561
##  7 1983-07-01 2304.4 234307  9.6      10.1         10548  1983 0.04501786
##  8 1983-08-01 2320.4 234501  9.200000  9.3         10623  1983 0.04530045
##  9 1983-09-01 2334.9 234701  9.6       9.3         10282  1983 0.04380893
## 10 1983-10-01 2357.6 234907  9.700000  9.4          9887  1983 0.04208900
## 11 1983-11-01 2366.3 235078 10.3       9.3          9499  1983 0.04040786
## 12 1983-12-01 2393.6 235235 10.1       8.700000     9331  1983 0.03966672
## 
## $`1984`
## # A tibble: 12 x 8
##    date            pce    pop psavert  uempmed unemploy  year    percent
##    <date>        <dbl>  <dbl>   <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 1984-01-01 2419.4   235385    10   9.1          9008  1984 0.03826922
##  2 1984-02-01 2403.5   235527    11.7 8.3          8791  1984 0.03732481
##  3 1984-03-01 2431.6   235675    11.5 8.3          8746  1984 0.03711043
##  4 1984-04-01 2457.5   235839    11.5 8.200000     8762  1984 0.03715246
##  5 1984-05-01 2474.5   235993    11.1 9.1          8456  1984 0.03583157
##  6 1984-06-01 2495.6   236160    11.1 7.5          8226  1984 0.03483232
##  7 1984-07-01 2494.6   236348    11.6 7.5          8537  1984 0.03612047
##  8 1984-08-01 2512.200 236549    11.8 7.3          8519  1984 0.03601368
##  9 1984-09-01 2533.8   236760    11.8 7.6          8367  1984 0.03533958
## 10 1984-10-01 2531.3   236976    11.7 7.2          8381  1984 0.03536645
## 11 1984-11-01 2571.4   237159    10.9 7.2          8198  1984 0.03456753
## 12 1984-12-01 2582.6   237316    11.2 7.3          8358  1984 0.03521886
## 
## $`1985`
## # A tibble: 12 x 8
##    date          pce    pop   psavert uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>     <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 1985-01-01 2618.8 237468 10.3          6.8     8423  1985 0.03547004
##  2 1985-02-01 2640.8 237602  9.1          7.1     8321  1985 0.03502075
##  3 1985-03-01 2648.5 237732  8.700000     7.1     8339  1985 0.03507731
##  4 1985-04-01 2659.5 237900  9.9          6.9     8395  1985 0.03528794
##  5 1985-05-01 2696.4 238074 11.1          6.9     8302  1985 0.03487151
##  6 1985-06-01 2689.4 238270  9.6          6.6     8460  1985 0.03550594
##  7 1985-07-01 2715.7 238466  9.1          6.9     8513  1985 0.03569901
##  8 1985-08-01 2752.1 238679  8.200000     7.1     8196  1985 0.03433901
##  9 1985-09-01 2794.7 238898  7.3          6.9     8248  1985 0.03452519
## 10 1985-10-01 2755.8 239113  9.1          7.1     8298  1985 0.03470326
## 11 1985-11-01 2771.1 239307  9            7       8128  1985 0.03396474
## 12 1985-12-01 2811.3 239477  8.6          6.8     8138  1985 0.03398239
## 
## $`1986`
## # A tibble: 12 x 8
##    date          pce    pop  psavert uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>    <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 1986-01-01 2827.1 239638 8.6          6.7     7795  1986 0.03252823
##  2 1986-02-01 2820.2 239788 9.3          6.9     8402  1986 0.03503928
##  3 1986-03-01 2823.6 239928 9.9          6.8     8383  1986 0.03493965
##  4 1986-04-01 2835.2 240094 9.700000     6.7     8364  1986 0.03483636
##  5 1986-05-01 2857.5 240271 9.3          6.8     8439  1986 0.03512284
##  6 1986-06-01 2861.7 240459 9.4          7       8508  1986 0.03538233
##  7 1986-07-01 2881.2 240651 9.3          6.9     8319  1986 0.03456873
##  8 1986-08-01 2898.6 240854 9            7.1     8135  1986 0.03377565
##  9 1986-09-01 2971.8 241068 7.2          7.4     8310  1986 0.03447160
## 10 1986-10-01 2932.9 241274 8.4          7       8243  1986 0.03416448
## 11 1986-11-01 2928.4 241467 8.8          7.1     8159  1986 0.03378930
## 12 1986-12-01 2997.1 241620 7            7.1     7883  1986 0.03262561
## 
## $`1987`
## # A tibble: 12 x 8
##    date          pce    pop  psavert uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>    <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 1987-01-01 2935.5 241784 9.700000     6.9     7892  1987 0.03264070
##  2 1987-02-01 3001.7 241930 8.5          6.6     7865  1987 0.03250940
##  3 1987-03-01 3013.3 242079 8.5          6.6     7862  1987 0.03247700
##  4 1987-04-01 3038.8 242252 4.5          7.1     7542  1987 0.03113287
##  5 1987-05-01 3048.4 242423 8.200000     6.6     7574  1987 0.03124291
##  6 1987-06-01 3072.8 242608 7.7          6.5     7398  1987 0.03049364
##  7 1987-07-01 3094.7 242804 7.5          6.5     7268  1987 0.02993361
##  8 1987-08-01 3130.8 243012 7.2          6.4     7261  1987 0.02987918
##  9 1987-09-01 3126.5 243223 7.6          6       7102  1987 0.02919954
## 10 1987-10-01 3134.5 243446 8.3          6.3     7227  1987 0.02968625
## 11 1987-11-01 3144.2 243639 8.5          6.2     7035  1987 0.02887469
## 12 1987-12-01 3174.1 243809 8.700000     6       6936  1987 0.02844850
## 
## $`1988`
## # A tibble: 12 x 8
##    date          pce    pop  psavert uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>    <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 1988-01-01 3213.7 243981 8.1          6.2     6953  1988 0.02849812
##  2 1988-02-01 3221.4 244131 8.6          6.3     6929  1988 0.02838230
##  3 1988-03-01 3260.5 244279 8.200000     6.4     6876  1988 0.02814814
##  4 1988-04-01 3263   244445 8.8          5.9     6601  1988 0.02700403
##  5 1988-05-01 3293.6 244610 8.4          5.9     6779  1988 0.02771350
##  6 1988-06-01 3318.5 244806 8.4          5.8     6546  1988 0.02673954
##  7 1988-07-01 3342.7 245021 8.6          6.1     6605  1988 0.02695687
##  8 1988-08-01 3368   245240 8.4          5.9     6843  1988 0.02790328
##  9 1988-09-01 3375   245464 8.9          5.7     6604  1988 0.02690415
## 10 1988-10-01 3413.7 245693 8.6          5.6     6568  1988 0.02673255
## 11 1988-11-01 3430.2 245884 8.4          5.7     6537  1988 0.02658571
## 12 1988-12-01 3459.7 246056 8.3          5.9     6518  1988 0.02648990
## 
## $`1989`
## # A tibble: 12 x 8
##    date          pce    pop  psavert uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>    <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 1989-01-01 3483.7 246224 8.5          5.6     6682  1989 0.02713789
##  2 1989-02-01 3488   246378 9            5.4     6359  1989 0.02580993
##  3 1989-03-01 3498.8 246530 9.5          5.4     6205  1989 0.02516935
##  4 1989-04-01 3543   246721 8.4          5.4     6468  1989 0.02621585
##  5 1989-05-01 3551.8 246906 8.1          5.3     6375  1989 0.02581954
##  6 1989-06-01 3566.6 247114 8.200000     5.4     6577  1989 0.02661525
##  7 1989-07-01 3585.7 247342 8.200000     5.6     6495  1989 0.02625919
##  8 1989-08-01 3620.6 247573 7.6          5       6511  1989 0.02629931
##  9 1989-09-01 3621.9 247816 8.1          4.9     6590  1989 0.02659231
## 10 1989-10-01 3633.6 248067 8.5          4.9     6630  1989 0.02672665
## 11 1989-11-01 3643.3 248281 8.6          4.8     6725  1989 0.02708625
## 12 1989-12-01 3684.2 248479 7.8          4.9     6667  1989 0.02683124
## 
## $`1990`
## # A tibble: 12 x 8
##    date          pce    pop  psavert  uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>    <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 1990-01-01 3730.7 248659 8        5.100000     6752  1990 0.02715365
##  2 1990-02-01 3728.2 248827 8.6      5.3          6651  1990 0.02672941
##  3 1990-03-01 3754.9 249012 8.3      5.100000     6598  1990 0.02649672
##  4 1990-04-01 3770   249306 8.8      4.8          6797  1990 0.02726368
##  5 1990-05-01 3775.8 249565 8.700000 5.2          6742  1990 0.02701501
##  6 1990-06-01 3804.5 249849 8.6      5.2          6590  1990 0.02637593
##  7 1990-07-01 3821.7 250132 8.700000 5.4          6922  1990 0.02767339
##  8 1990-08-01 3848.3 250439 8.1      5.4          7188  1990 0.02870160
##  9 1990-09-01 3870.1 250751 8.1      5.6          7368  1990 0.02938373
## 10 1990-10-01 3870.6 251057 7.8      5.8          7459  1990 0.02971038
## 11 1990-11-01 3871.9 251346 7.9      5.7          7764  1990 0.03088969
## 12 1990-12-01 3861.3 251626 8.8      5.9          7901  1990 0.03139978
## 
## $`1991`
## # A tibble: 12 x 8
##    date          pce    pop  psavert uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>    <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 1991-01-01 3841   251889 9.3          6       8015  1991 0.03181957
##  2 1991-02-01 3866.7 252135 8.8          6.2     8265  1991 0.03278006
##  3 1991-03-01 3913   252372 8            6.7     8586  1991 0.03402121
##  4 1991-04-01 3907.1 252643 8.6          6.6     8439  1991 0.03340286
##  5 1991-05-01 3933.2 252913 8.4          6.4     8736  1991 0.03454152
##  6 1991-06-01 3940.5 253207 8.9          6.9     8692  1991 0.03432764
##  7 1991-07-01 3966   253493 8.200000     7       8586  1991 0.03387076
##  8 1991-08-01 3969.1 253807 8.6          7.3     8666  1991 0.03414405
##  9 1991-09-01 3984.7 254126 8.8          6.8     8722  1991 0.03432156
## 10 1991-10-01 3976   254435 9.3          7.2     8842  1991 0.03475151
## 11 1991-11-01 4003.6 254718 9            7.5     8931  1991 0.03506230
## 12 1991-12-01 4020.5 254964 9.700000     7.8     9198  1991 0.03607568
## 
## $`1992`
## # A tibble: 12 x 8
##    date            pce    pop   psavert  uempmed unemploy  year    percent
##    <date>        <dbl>  <dbl>     <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 1992-01-01 4084.7   255214  9.4      8.1          9283  1992 0.03637340
##  2 1992-02-01 4099.5   255448  9.8      8.200000     9454  1992 0.03700949
##  3 1992-03-01 4117     255703  9.700000 8.3          9460  1992 0.03699605
##  4 1992-04-01 4131.5   255992  9.9      8.5          9415  1992 0.03677849
##  5 1992-05-01 4158.400 256285  9.9      8.8          9744  1992 0.03802017
##  6 1992-06-01 4177.1   256589 10.1      8.700000    10040  1992 0.03912872
##  7 1992-07-01 4204.8   256894  9.6      8.6          9850  1992 0.03834266
##  8 1992-08-01 4220.900 257232  9.700000 8.8          9787  1992 0.03804737
##  9 1992-09-01 4255.3   257548  8.700000 8.6          9781  1992 0.03797739
## 10 1992-10-01 4284.7   257861  8        9            9398  1992 0.03644599
## 11 1992-11-01 4300.5   258147  8        9            9565  1992 0.03705253
## 12 1992-12-01 4336.400 258413 10.6      9.3          9557  1992 0.03698343
## 
## $`1993`
## # A tibble: 12 x 8
##    date            pce    pop  psavert  uempmed unemploy  year    percent
##    <date>        <dbl>  <dbl>    <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 1993-01-01 4340.7   258679 8.6      8.6          9325  1993 0.03604854
##  2 1993-02-01 4355.3   258919 8.9      8.5          9183  1993 0.03546669
##  3 1993-03-01 4352.5   259152 8.9      8.5          9056  1993 0.03494474
##  4 1993-04-01 4393.400 259414 8.700000 8.4          9110  1993 0.03511761
##  5 1993-05-01 4422.400 259680 8.3      8.1          9149  1993 0.03523182
##  6 1993-06-01 4440     259963 7.8      8.3          9121  1993 0.03508576
##  7 1993-07-01 4468.900 260255 7.6      8.200000     8930  1993 0.03431250
##  8 1993-08-01 4481.1   260566 7.7      8.200000     8763  1993 0.03363063
##  9 1993-09-01 4511.5   260867 6.9      8.3          8714  1993 0.03340400
## 10 1993-10-01 4532.8   261163 6.3      8            8750  1993 0.03350398
## 11 1993-11-01 4554.1   261425 6.3      8.3          8542  1993 0.03267476
## 12 1993-12-01 4571.1   261674 9.1      8.3          8477  1993 0.03239527
## 
## $`1994`
## # A tibble: 12 x 8
##    date            pce    pop psavert   uempmed unemploy  year    percent
##    <date>        <dbl>  <dbl>   <dbl>     <dbl>    <dbl> <dbl>      <dbl>
##  1 1994-01-01 4585.1   261919     7.1  8.6          8630  1994 0.03294912
##  2 1994-02-01 4632.6   262123     6.5  9.200000     8583  1994 0.03274417
##  3 1994-03-01 4646     262352     6.8  9.3          8470  1994 0.03228487
##  4 1994-04-01 4671.1   262631     6.4  9.1          8331  1994 0.03172131
##  5 1994-05-01 4669.5   262877     7.6  9.200000     7915  1994 0.03010914
##  6 1994-06-01 4708.900 263152     6.9  9.3          7927  1994 0.03012327
##  7 1994-07-01 4720.6   263436     7    9            7946  1994 0.03016292
##  8 1994-08-01 4762.6   263724     6.5  8.9          7933  1994 0.03008069
##  9 1994-09-01 4775     264017     6.8  9.200000     7734  1994 0.02929357
## 10 1994-10-01 4812.900 264301     7.1 10            7632  1994 0.02887617
## 11 1994-11-01 4825.6   264559     7    9            7375  1994 0.02787658
## 12 1994-12-01 4841.6   264804     7.2  8.700000     7230  1994 0.02730321
## 
## $`1995`
## # A tibble: 12 x 8
##    date            pce    pop psavert  uempmed unemploy  year    percent
##    <date>        <dbl>  <dbl>   <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 1995-01-01 4851.2   265044     7.5 8            7375  1995 0.02782557
##  2 1995-02-01 4850.8   265270     7.8 8.1          7187  1995 0.02709315
##  3 1995-03-01 4885.400 265495     7.5 8.3          7153  1995 0.02694213
##  4 1995-04-01 4890.2   265755     6.9 8.3          7645  1995 0.02876710
##  5 1995-05-01 4933.1   265998     7.1 9.1          7430  1995 0.02793254
##  6 1995-06-01 4977.5   266270     6.7 7.9          7427  1995 0.02789274
##  7 1995-07-01 4970.2   266557     7.1 8.5          7527  1995 0.02823786
##  8 1995-08-01 5005.3   266843     6.7 8.3          7484  1995 0.02804645
##  9 1995-09-01 5020.5   267152     6.8 7.9          7478  1995 0.02799156
## 10 1995-10-01 5013.900 267456     7.1 8.200000     7328  1995 0.02739890
## 11 1995-11-01 5055.6   267715     6.6 8            7426  1995 0.02773845
## 12 1995-12-01 5097.5   267943     6.1 8.3          7423  1995 0.02770365
## 
## $`1996`
## # A tibble: 12 x 8
##    date          pce    pop psavert uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>   <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 1996-01-01 5085.7 268151     6.7     8.3     7491  1996 0.02793575
##  2 1996-02-01 5132.8 268364     6.7     7.8     7313  1996 0.02725030
##  3 1996-03-01 5173.3 268595     6.6     8.3     7318  1996 0.02724548
##  4 1996-04-01 5208   268853     5.7     8.6     7415  1996 0.02758013
##  5 1996-05-01 5223.8 269108     6.7     8.6     7423  1996 0.02758372
##  6 1996-06-01 5229.8 269386     7.1     8.3     7095  1996 0.02633767
##  7 1996-07-01 5251.9 269667     6.7     8.3     7337  1996 0.02720763
##  8 1996-08-01 5275   269976     6.6     8.4     6882  1996 0.02549115
##  9 1996-09-01 5296.6 270284     6.7     8.5     6979  1996 0.02582099
## 10 1996-10-01 5328.5 270581     6.4     8.3     7031  1996 0.02598483
## 11 1996-11-01 5351.2 270878     6.4     7.7     7236  1996 0.02671313
## 12 1996-12-01 5378.6 271125     6.4     7.8     7253  1996 0.02675150
## 
## $`1997`
## # A tibble: 12 x 8
##    date          pce    pop psavert  uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>   <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 1997-01-01 5411.1 271360     6.2 7.8          7158  1997 0.02637824
##  2 1997-02-01 5434   271585     6.2 8.1          7102  1997 0.02615019
##  3 1997-03-01 5454.2 271821     6.4 7.9          7000  1997 0.02575224
##  4 1997-04-01 5459.3 272083     6.5 8.3          6873  1997 0.02526067
##  5 1997-05-01 5460.2 272342     6.8 8            6655  1997 0.02443619
##  6 1997-06-01 5494.2 272622     6.6 8            6799  1997 0.02493929
##  7 1997-07-01 5548.8 272912     6.1 8.3          6655  1997 0.02438515
##  8 1997-08-01 5587   273237     6   7.8          6608  1997 0.02418413
##  9 1997-09-01 5601.7 273553     6.2 8.200000     6656  1997 0.02433167
## 10 1997-10-01 5637.7 273852     6.2 7.7          6454  1997 0.02356747
## 11 1997-11-01 5661.1 274126     6.4 7.6          6308  1997 0.02301132
## 12 1997-12-01 5692.1 274372     6.4 7.5          6476  1997 0.02360299
## 
## $`1998`
## # A tibble: 12 x 8
##    date          pce    pop psavert uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>   <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 1998-01-01 5689.9 274626     7.4     7.4     6368  1998 0.02318790
##  2 1998-02-01 5723.8 274838     7.4     7       6306  1998 0.02294443
##  3 1998-03-01 5750.3 275047     7.5     6.8     6422  1998 0.02334874
##  4 1998-04-01 5788.1 275304     7.2     6.7     5941  1998 0.02157978
##  5 1998-05-01 5837.9 275564     6.9     6       6047  1998 0.02194409
##  6 1998-06-01 5871.7 275836     6.8     6.9     6212  1998 0.02252063
##  7 1998-07-01 5890   276115     6.9     6.7     6259  1998 0.02266809
##  8 1998-08-01 5925   276418     6.8     6.8     6179  1998 0.02235383
##  9 1998-09-01 5965.6 276714     6.4     6.7     6300  1998 0.02276719
## 10 1998-10-01 5998.8 277003     6.2     5.8     6280  1998 0.02267123
## 11 1998-11-01 6015.4 277277     6.3     6.6     6100  1998 0.02199966
## 12 1998-12-01 6070.5 277526     5.8     6.8     6032  1998 0.02173490
## 
## $`1999`
## # A tibble: 12 x 8
##    date          pce    pop  psavert uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>    <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 1999-01-01 6072.9 277790 6.4          6.9     5976  1999 0.02151265
##  2 1999-02-01 6101.8 277992 6.2          6.8     6111  1999 0.02198265
##  3 1999-03-01 6132.9 278198 5.9          6.8     5783  1999 0.02078735
##  4 1999-04-01 6196.2 278451 5.2          6.2     6004  1999 0.02156214
##  5 1999-05-01 6225.7 278717 4.9          6.5     5796  1999 0.02079529
##  6 1999-06-01 6254   279001 4.8          6.3     5951  1999 0.02132967
##  7 1999-07-01 6281.5 279295 4.8          5.8     6025  1999 0.02157217
##  8 1999-08-01 6326.5 279602 4.7          6.5     5838  1999 0.02087968
##  9 1999-09-01 6378.8 279903 4.2          6       5915  1999 0.02113232
## 10 1999-10-01 6402.1 280203 4.600000     6.1     5778  1999 0.02062076
## 11 1999-11-01 6437.9 280471 4.8          6.2     5716  1999 0.02038000
## 12 1999-12-01 6538.7 280716 4.4          5.8     5653  1999 0.02013779
## 
## $`2000`
## # A tibble: 12 x 8
##    date          pce    pop  psavert uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>    <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 2000-01-01 6535.3 280976 5.4          5.8     5708  2000 0.02031490
##  2 2000-02-01 6619.7 281190 4.8          6.1     5858  2000 0.02083289
##  3 2000-03-01 6685.8 281409 4.5          6       5733  2000 0.02037248
##  4 2000-04-01 6671.1 281653 5            6.1     5481  2000 0.01946012
##  5 2000-05-01 6707.6 281877 4.9          5.8     5758  2000 0.02042735
##  6 2000-06-01 6743.9 282126 4.9          5.7     5651  2000 0.02003006
##  7 2000-07-01 6764.1 282385 5.2          6       5747  2000 0.02035165
##  8 2000-08-01 6799.1 282653 5.2          6.3     5853  2000 0.02070737
##  9 2000-09-01 6882.9 282932 4.5          5.2     5625  2000 0.01988110
## 10 2000-10-01 6888.2 283201 4.600000     6.1     5534  2000 0.01954089
## 11 2000-11-01 6902.4 283453 4.5          6.1     5639  2000 0.01989395
## 12 2000-12-01 6945.7 283696 4.2          6       5634  2000 0.01985929
## 
## $`2001`
## # A tibble: 12 x 8
##    date          pce    pop  psavert  uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>    <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 2001-01-01 6977   283920 4.8      5.8          6023  2001 0.02121372
##  2 2001-02-01 6995.8 284137 4.9      6.1          6089  2001 0.02142980
##  3 2001-03-01 6987.9 284350 5.3      6.6          6141  2001 0.02159662
##  4 2001-04-01 7001.2 284581 5        5.9          6271  2001 0.02203591
##  5 2001-05-01 7047.1 284810 4.5      6.3          6226  2001 0.02186019
##  6 2001-06-01 7060.7 285062 4.5      6            6484  2001 0.02274593
##  7 2001-07-01 7072.2 285309 5.6      6.8          6583  2001 0.02307323
##  8 2001-08-01 7108.9 285570 6.8      6.9          7042  2001 0.02465945
##  9 2001-09-01 7012.8 285843 7        7.2          7142  2001 0.02498574
## 10 2001-10-01 7208.4 286098 3.4      7.3          7694  2001 0.02689288
## 11 2001-11-01 7167.9 286341 4.100000 7.7          8003  2001 0.02794919
## 12 2001-12-01 7147.7 286570 4.5      8.200000     8258  2001 0.02881669
## 
## $`2002`
## # A tibble: 12 x 8
##    date          pce    pop psavert uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>   <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 2002-01-01 7174.3 286788     6.1     8.4     8182  2002 0.02852979
##  2 2002-02-01 7218.3 286994     5.8     8.3     8215  2002 0.02862429
##  3 2002-03-01 7237.2 287190     5.9     8.4     8304  2002 0.02891466
##  4 2002-04-01 7305.4 287397     5.8     8.9     8599  2002 0.02992028
##  5 2002-05-01 7282.7 287623     6.5     9.5     8399  2002 0.02920142
##  6 2002-06-01 7318.2 287864     6.4    11       8393  2002 0.02915613
##  7 2002-07-01 7380.4 288105     5.5     8.9     8390  2002 0.02912133
##  8 2002-08-01 7401.5 288360     5.4     9       8304  2002 0.02879734
##  9 2002-09-01 7391   288618     5.7     9.5     8251  2002 0.02858796
## 10 2002-10-01 7430.7 288870     5.7     9.6     8307  2002 0.02875688
## 11 2002-11-01 7459.7 289106     5.7     9.3     8520  2002 0.02947016
## 12 2002-12-01 7512.8 289313     5.5     9.6     8640  2002 0.02986385
## 
## $`2003`
## # A tibble: 12 x 8
##    date          pce    pop psavert   uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>   <dbl>     <dbl>    <dbl> <dbl>      <dbl>
##  1 2003-01-01 7533.1 289518     5.5  9.6          8520  2003 0.02942822
##  2 2003-02-01 7535.9 289714     5.6  9.5          8618  2003 0.02974658
##  3 2003-03-01 7598.4 289911     5.3  9.700000     8588  2003 0.02962288
##  4 2003-04-01 7621   290125     5.3 10.200        8842  2003 0.03047652
##  5 2003-05-01 7628.1 290346     5.8  9.9          8957  2003 0.03084940
##  6 2003-06-01 7678.6 290584     5.6 11.5          9266  2003 0.03188751
##  7 2003-07-01 7738.2 290820     6.3 10.3          9011  2003 0.03098480
##  8 2003-08-01 7834.5 291072     6   10.1          8896  2003 0.03056288
##  9 2003-09-01 7835   291321     5.2 10.200        8921  2003 0.03062258
## 10 2003-10-01 7845.7 291574     5.3 10.4          8732  2003 0.02994780
## 11 2003-11-01 7899.6 291807     5.4 10.3          8576  2003 0.02938929
## 12 2003-12-01 7929.2 292008     5.4 10.4          8317  2003 0.02848210
## 
## $`2004`
## # A tibble: 12 x 8
##    date          pce    pop  psavert   uempmed unemploy  year    percent
##    <date>      <dbl>  <dbl>    <dbl>     <dbl>    <dbl> <dbl>      <dbl>
##  1 2004-01-01 7987.4 292192 5        10.6          8370  2004 0.02864555
##  2 2004-02-01 8019.8 292368 5        10.200        8167  2004 0.02793397
##  3 2004-03-01 8076   292561 4.9      10.200        8491  2004 0.02902301
##  4 2004-04-01 8088.6 292779 5.3       9.5          8170  2004 0.02790501
##  5 2004-05-01 8163.2 292997 5.3       9.9          8212  2004 0.02802759
##  6 2004-06-01 8147.2 293223 5.8      11            8286  2004 0.02825836
##  7 2004-07-01 8218.9 293463 5.3       8.9          8136  2004 0.02772411
##  8 2004-08-01 8253.1 293719 5.2       9.200000     7990  2004 0.02720287
##  9 2004-09-01 8321.1 293971 4.600000  9.6          7927  2004 0.02696524
## 10 2004-10-01 8374.6 294230 4.5       9.5          8061  2004 0.02739693
## 11 2004-11-01 8420.6 294466 4.100000  9.700000     7932  2004 0.02693690
## 12 2004-12-01 8481.5 294694 6.9       9.5          7934  2004 0.02692284
## 
## $`2005`
## # A tibble: 12 x 8
##    date            pce    pop psavert  uempmed unemploy  year    percent
##    <date>        <dbl>  <dbl>   <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 2005-01-01 8470.2   294914     3.7 9.4          7784  2005 0.02639414
##  2 2005-02-01 8529.2   295105     3.4 9.200000     7980  2005 0.02704122
##  3 2005-03-01 8569.5   295287     3.6 9.3          7737  2005 0.02620163
##  4 2005-04-01 8645.6   295490     3.1 9            7672  2005 0.02596365
##  5 2005-05-01 8643.9   295704     3.5 9.1          7651  2005 0.02587385
##  6 2005-06-01 8724.800 295936     2.9 9            7524  2005 0.02542442
##  7 2005-07-01 8829.5   296186     2.2 8.8          7406  2005 0.02500456
##  8 2005-08-01 8832.4   296440     2.7 9.200000     7345  2005 0.02477736
##  9 2005-09-01 8885.800 296707     2.7 8.4          7553  2005 0.02545609
## 10 2005-10-01 8926.6   296972     3.1 8.6          7453  2005 0.02509664
## 11 2005-11-01 8938.5   297207     3.5 8.5          7566  2005 0.02545700
## 12 2005-12-01 8969.6   297431     3.7 8.700000     7279  2005 0.02447290
## 
## $`2006`
## # A tibble: 12 x 8
##    date            pce    pop psavert  uempmed unemploy  year    percent
##    <date>        <dbl>  <dbl>   <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 2006-01-01 9059.800 297647     4.2 8.6          7064  2006 0.02373281
##  2 2006-02-01 9090.1   297854     4.2 9.1          7184  2006 0.02411920
##  3 2006-03-01 9122.1   298060     4.2 8.700000     7072  2006 0.02372677
##  4 2006-04-01 9174.800 298281     4   8.4          7120  2006 0.02387011
##  5 2006-05-01 9215.1   298496     3.8 8.5          6980  2006 0.02338390
##  6 2006-06-01 9240.800 298739     4   7.3          7001  2006 0.02343517
##  7 2006-07-01 9322.6   298996     3.4 8            7175  2006 0.02399698
##  8 2006-08-01 9321.800 299263     3.6 8.4          7091  2006 0.02369488
##  9 2006-09-01 9354.7   299554     3.6 8            6847  2006 0.02285731
## 10 2006-10-01 9373.2   299835     3.6 7.9          6727  2006 0.02243567
## 11 2006-11-01 9380.2   300094     3.9 8.3          6872  2006 0.02289949
## 12 2006-12-01 9469     300340     3.7 7.5          6762  2006 0.02251448
## 
## $`2007`
## # A tibble: 12 x 8
##    date            pce    pop  psavert  uempmed unemploy  year    percent
##    <date>        <dbl>  <dbl>    <dbl>    <dbl>    <dbl> <dbl>      <dbl>
##  1 2007-01-01 9516.300 300574 3.7      8.3          7116  2007 0.02367470
##  2 2007-02-01 9546.800 300802 4.100000 8.5          6927  2007 0.02302844
##  3 2007-03-01 9585.1   301021 4.4      9.1          6731  2007 0.02236057
##  4 2007-04-01 9615.7   301254 4.2      8.6          6850  2007 0.02273829
##  5 2007-05-01 9651.300 301483 4        8.200000     6766  2007 0.02244239
##  6 2007-06-01 9667.300 301739 3.8      7.7          6979  2007 0.02312926
##  7 2007-07-01 9709.6   302004 3.7      8.700000     7149  2007 0.02367187
##  8 2007-08-01 9753.9   302267 3.4      8.8          7067  2007 0.02337999
##  9 2007-09-01 9797.9   302546 3.5      8.700000     7170  2007 0.02369888
## 10 2007-10-01 9827     302807 3.4      8.4          7237  2007 0.02389971
## 11 2007-11-01 9897.800 303054 3.1      8.6          7240  2007 0.02389013
## 12 2007-12-01 9908.4   303287 3.6      8.4          7645  2007 0.02520715
## 
## $`2008`
## # A tibble: 12 x 8
##    date             pce    pop  psavert   uempmed unemploy  year    percent
##    <date>         <dbl>  <dbl>    <dbl>     <dbl>    <dbl> <dbl>      <dbl>
##  1 2008-01-01  9930     303506 3.7       9            7685  2008 0.02532075
##  2 2008-02-01  9913.4   303711 4.100000  8.700000     7497  2008 0.02468465
##  3 2008-03-01  9959.4   303907 4         8.700000     7822  2008 0.02573814
##  4 2008-04-01  9996.800 304117 3.4       9.4          7637  2008 0.02511205
##  5 2008-05-01 10053.8   304323 7.8       7.9          8395  2008 0.02758582
##  6 2008-06-01 10107.9   304556 5.5       9            8575  2008 0.02815574
##  7 2008-07-01 10104.7   304798 4.4       9.700000     8937  2008 0.02932106
##  8 2008-08-01 10094.7   305045 3.8       9.700000     9438  2008 0.03093970
##  9 2008-09-01 10043.5   305309 4.7      10.200        9494  2008 0.03109636
## 10 2008-10-01  9960.300 305554 5.5      10.4         10074  2008 0.03296962
## 11 2008-11-01  9820.800 305786 6.4       9.8         10538  2008 0.03446201
## 12 2008-12-01  9730.7   306004 6.4      10.5         11286  2008 0.03688187
## 
## $`2009`
## # A tibble: 12 x 8
##    date            pce    pop  psavert uempmed unemploy  year    percent
##    <date>        <dbl>  <dbl>    <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 2009-01-01 9783.800 306208 6.2       10.7      12058  2009 0.03937846
##  2 2009-02-01 9766     306402 5.5       11.7      12898  2009 0.04209503
##  3 2009-03-01 9718.5   306588 5.9       12.3      13426  2009 0.04379167
##  4 2009-04-01 9724.800 306787 6.8       13.1      13853  2009 0.04515511
##  5 2009-05-01 9748.9   306984 8.200000  14.2      14499  2009 0.04723047
##  6 2009-06-01 9806.9   307206 6.7       17.2      14707  2009 0.04787341
##  7 2009-07-01 9841.7   307439 6         16        14601  2009 0.04749235
##  8 2009-08-01 9961     307685 4.9       16.3      14814  2009 0.04814664
##  9 2009-09-01 9883.4   307946 5.9       17.8      15009  2009 0.04873906
## 10 2009-10-01 9931.9   308189 5.4       18.900    15352  2009 0.04981359
## 11 2009-11-01 9940.5   308418 5.9       19.8      15219  2009 0.04934537
## 12 2009-12-01 9998.9   308633 5.9       20.1      15098  2009 0.04891894
## 
## $`2010`
## # A tibble: 12 x 8
##    date           pce      pop psavert uempmed unemploy  year    percent
##    <date>       <dbl>    <dbl>   <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 2010-01-01 10001.8 308833       6.1  20        15046  2010 0.04871889
##  2 2010-02-01 10030.6 309027       5.8  19.900    15113  2010 0.04890511
##  3 2010-03-01 10089.1 309212       5.7  20.400    15202  2010 0.04916368
##  4 2010-04-01 10112.9 309191.2     6.4  22.1      15325  2010 0.04956480
##  5 2010-05-01 10131   309369.1     7    22.3      14849  2010 0.04799769
##  6 2010-06-01 10151.4 309548.5     6.9  25.2      14474  2010 0.04675842
##  7 2010-07-01 10184.7 309745.7     6.8  22.3      14512  2010 0.04685134
##  8 2010-08-01 10228.2 309957.8     6.9  21        14648  2010 0.04725805
##  9 2010-09-01 10249   310176.5     6.7  20.3      14579  2010 0.04700228
## 10 2010-10-01 10304.7 310400.0     6.6  21.2      14516  2010 0.04676547
## 11 2010-11-01 10354.7 310595.8     6.6  21        15081  2010 0.04855507
## 12 2010-12-01 10392.1 310781.7     7.1  21.9      14348  2010 0.04616745
## 
## $`2011`
## # A tibble: 12 x 8
##    date           pce      pop psavert uempmed unemploy  year    percent
##    <date>       <dbl>    <dbl>   <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 2011-01-01 10435.5 310960.7     7.4    21.5    14013  2011 0.04506357
##  2 2011-02-01 10470.1 311113.4     7.6    21.1    13820  2011 0.04442111
##  3 2011-03-01 10550.5 311265.4     7      21.5    13737  2011 0.04413276
##  4 2011-04-01 10587.6 311436.2     6.9    20.9    13957  2011 0.04481495
##  5 2011-05-01 10612   311607.1     6.9    21.6    13855  2011 0.04446305
##  6 2011-06-01 10636.8 311791.2     7.2    22.4    13962  2011 0.04477996
##  7 2011-07-01 10677.5 311997.0     7.3    22      13763  2011 0.04411260
##  8 2011-08-01 10700.6 312205.4     7.2    22.4    13818  2011 0.04425933
##  9 2011-09-01 10738.1 312429.1     6.8    22      13948  2011 0.04464373
## 10 2011-10-01 10753.1 312644.2     6.8    20.6    13594  2011 0.04348074
## 11 2011-11-01 10759.5 312829.5     7      20.8    13302  2011 0.04252156
## 12 2011-12-01 10772.2 313009.7     7.8    20.5    13093  2011 0.04182937
## 
## $`2012`
## # A tibble: 12 x 8
##    date           pce      pop   psavert uempmed unemploy  year    percent
##    <date>       <dbl>    <dbl>     <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 2012-01-01 10862.1 313183.2  8         20.8      12797  2012 0.04086107
##  2 2012-02-01 10953.5 313339.0  8         19.7      12813  2012 0.04089182
##  3 2012-03-01 10951.8 313499.4  8.5       19.2      12713  2012 0.04055192
##  4 2012-04-01 10979.7 313667.1  8.700000  19.1      12646  2012 0.04031663
##  5 2012-05-01 10968.6 313830.5  8.8       19.900    12660  2012 0.04034024
##  6 2012-06-01 10946.3 314017.6  9.1       20.400    12692  2012 0.04041812
##  7 2012-07-01 10977.2 314210.8  8.200000  17.5      12656  2012 0.04027869
##  8 2012-08-01 11004.1 314422.3  8         18.400    12471  2012 0.03966321
##  9 2012-09-01 11061.5 314646.7  8.200000  18.8      12115  2012 0.03850350
## 10 2012-10-01 11099.8 314854.0  8.8       19.900    12124  2012 0.03850674
## 11 2012-11-01 11136.8 315053.9  9.700000  18.6      12005  2012 0.03810460
## 12 2012-12-01 11140.5 315232.8 12         17.7      12298  2012 0.03901244
## 
## $`2013`
## # A tibble: 12 x 8
##    date           pce      pop psavert uempmed unemploy  year    percent
##    <date>       <dbl>    <dbl>   <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 2013-01-01 11202.8 315389.6     6.3    15.8    12471  2013 0.03954157
##  2 2013-02-01 11239.6 315520.1     5.8    17.2    11950  2013 0.03787397
##  3 2013-03-01 11227.1 315662.2     5.9    17.6    11689  2013 0.03703009
##  4 2013-04-01 11205.4 315817.9     6.4    17.1    11760  2013 0.03723665
##  5 2013-05-01 11244.6 315983.7     6.7    17.1    11654  2013 0.03688165
##  6 2013-06-01 11268.8 316171.0     6.8    17      11751  2013 0.03716659
##  7 2013-07-01 11296.7 316358.8     6.6    16.2    11335  2013 0.03582957
##  8 2013-08-01 11329.2 316580.3     6.7    16.5    11279  2013 0.03562761
##  9 2013-09-01 11366.9 316806.1     6.8    16.5    11270  2013 0.03557381
## 10 2013-10-01 11419.8 317022.3     6.3    16.3    11136  2013 0.03512687
## 11 2013-11-01 11487.6 317228.0     6.2    17.1    10787  2013 0.03400393
## 12 2013-12-01 11517.9 317411.6     6.4    17.3    10404  2013 0.03277764
## 
## $`2014`
## # A tibble: 12 x 8
##    date           pce      pop psavert uempmed unemploy  year    percent
##    <date>       <dbl>    <dbl>   <dbl>   <dbl>    <dbl> <dbl>      <dbl>
##  1 2014-01-01 11512.5 317593.9     7.1    15.4    10202  2014 0.03212278
##  2 2014-02-01 11566.2 317753.9     7.3    15.9    10349  2014 0.03256923
##  3 2014-03-01 11643   317917.2     7.4    15.8    10380  2014 0.03265001
##  4 2014-04-01 11702.6 318089.2     7.4    15.7     9702  2014 0.03050088
##  5 2014-05-01 11748.4 318269.5     7.4    14.6     9859  2014 0.03097689
##  6 2014-06-01 11817   318464.2     7.4    13.8     9460  2014 0.02970507
##  7 2014-07-01 11860.5 318662.4     7.5    13.1     9608  2014 0.03015103
##  8 2014-08-01 11944.3 318893.8     7.2    12.9     9599  2014 0.03010093
##  9 2014-09-01 11957.4 319125.3     7.4    13.4     9262  2014 0.02902308
## 10 2014-10-01 12023   319353.7     7.2    13.6     8990  2014 0.02815060
## 11 2014-11-01 12051.4 319564.2     7.3    13       9090  2014 0.02844499
## 12 2014-12-01 12062   319746.2     7.6    12.9     8717  2014 0.02726225
## 
## $`2015`
## # A tibble: 4 x 8
##   date           pce      pop psavert uempmed unemploy  year    percent
##   <date>       <dbl>    <dbl>   <dbl>   <dbl>    <dbl> <dbl>      <dbl>
## 1 2015-01-01 12046   319928.6     7.7    13.2     8903  2015 0.02782808
## 2 2015-02-01 12082.4 320074.5     7.9    12.9     8610  2015 0.02689999
## 3 2015-03-01 12158.3 320230.8     7.4    12       8504  2015 0.02655585
## 4 2015-04-01 12193.8 320402.3     7.6    11.5     8526  2015 0.02661030
```

---

```r
by_year %>%
	map(~mutate(.x, percent = unemploy / pop)) %>%
	map(~lm(percent ~ pce, data = .x))
```

```
## $`1967`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   8.397e-03    1.307e-05  
## 
## 
## $`1968`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   2.785e-02   -2.497e-05  
## 
## 
## $`1969`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##  -5.363e-03    3.202e-05  
## 
## 
## $`1970`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##  -0.1180578    0.0002137  
## 
## 
## $`1971`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   1.595e-02    1.177e-05  
## 
## 
## $`1972`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   4.404e-02   -2.708e-05  
## 
## 
## $`1973`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   2.571e-02   -6.047e-06  
## 
## 
## $`1974`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##  -5.070e-02    8.051e-05  
## 
## 
## $`1975`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   3.847e-02   -1.644e-06  
## 
## 
## $`1976`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   2.313e-02    9.414e-06  
## 
## 
## $`1977`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   7.454e-02   -3.367e-05  
## 
## 
## $`1978`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   4.419e-02   -1.152e-05  
## 
## 
## $`1979`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   1.932e-02    5.012e-06  
## 
## 
## $`1980`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##  -0.0074548    0.0000235  
## 
## 
## $`1981`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##  -2.494e-02    3.151e-05  
## 
## 
## $`1982`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##  -8.882e-02    6.516e-05  
## 
## 
## $`1983`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   1.461e-01   -4.402e-05  
## 
## 
## $`1984`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   7.893e-02   -1.718e-05  
## 
## 
## $`1985`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   5.366e-02   -6.927e-06  
## 
## 
## $`1986`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   5.385e-02   -6.783e-06  
## 
## 
## $`1987`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   0.0914664   -0.0000198  
## 
## 
## $`1988`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   5.123e-02   -7.174e-06  
## 
## 
## $`1989`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   1.051e-02    4.437e-06  
## 
## 
## $`1990`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##  -7.123e-02    2.611e-05  
## 
## 
## $`1991`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##  -3.857e-02    1.843e-05  
## 
## 
## $`1992`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   3.487e-02    6.091e-07  
## 
## 
## $`1993`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   9.538e-02   -1.372e-05  
## 
## 
## $`1994`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   1.295e-01   -2.102e-05  
## 
## 
## $`1995`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   2.397e-02    7.718e-07  
## 
## 
## $`1996`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   5.602e-02   -5.567e-06  
## 
## 
## $`1997`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   7.968e-02   -9.937e-06  
## 
## 
## $`1998`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   3.590e-02   -2.283e-06  
## 
## 
## $`1999`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   3.923e-02   -2.894e-06  
## 
## 
## $`2000`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   3.097e-02   -1.602e-06  
## 
## 
## $`2001`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##  -1.881e-01    3.001e-05  
## 
## 
## $`2002`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   1.428e-02    2.015e-06  
## 
## 
## $`2003`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   4.026e-02   -1.307e-06  
## 
## 
## $`2004`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   5.764e-02   -3.640e-06  
## 
## 
## $`2005`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   5.778e-02   -3.679e-06  
## 
## 
## $`2006`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   5.458e-02   -3.369e-06  
## 
## 
## $`2007`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##  -1.722e-02    4.188e-06  
## 
## 
## $`2008`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   1.785e-01   -1.495e-05  
## 
## 
## $`2009`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   -1.73e-01     2.23e-05  
## 
## 
## $`2010`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   1.073e-01   -5.844e-06  
## 
## 
## $`2011`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   1.041e-01   -5.647e-06  
## 
## 
## $`2012`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   0.1575956   -0.0000107  
## 
## 
## $`2013`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   2.101e-01   -1.536e-05  
## 
## 
## $`2014`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   1.317e-01   -8.591e-06  
## 
## 
## $`2015`
## 
## Call:
## lm(formula = percent ~ pce, data = .x)
## 
## Coefficients:
## (Intercept)          pce  
##   1.177e-01   -7.482e-06
```

---

```r
by_year %>%
	map(~mutate(.x, percent = unemploy / pop)) %>%
	map(~lm(percent ~ pce, data = .x)) %>%
	map(coef)
```

```
## $`1967`
##  (Intercept)          pce 
## 8.397192e-03 1.307101e-05 
## 
## $`1968`
##   (Intercept)           pce 
##  2.784626e-02 -2.496983e-05 
## 
## $`1969`
##   (Intercept)           pce 
## -5.362991e-03  3.201794e-05 
## 
## $`1970`
##   (Intercept)           pce 
## -0.1180577869  0.0002136662 
## 
## $`1971`
##  (Intercept)          pce 
## 1.594909e-02 1.177357e-05 
## 
## $`1972`
##   (Intercept)           pce 
##  0.0440400392 -0.0000270806 
## 
## $`1973`
##   (Intercept)           pce 
##  2.571465e-02 -6.047148e-06 
## 
## $`1974`
##   (Intercept)           pce 
## -5.069693e-02  8.050869e-05 
## 
## $`1975`
##   (Intercept)           pce 
##  3.847047e-02 -1.643992e-06 
## 
## $`1976`
##  (Intercept)          pce 
## 2.313211e-02 9.413733e-06 
## 
## $`1977`
##   (Intercept)           pce 
##  7.453726e-02 -3.366894e-05 
## 
## $`1978`
##   (Intercept)           pce 
##  4.418640e-02 -1.151756e-05 
## 
## $`1979`
##  (Intercept)          pce 
## 1.932149e-02 5.011539e-06 
## 
## $`1980`
##   (Intercept)           pce 
## -0.0074548418  0.0000235041 
## 
## $`1981`
##   (Intercept)           pce 
## -2.494231e-02  3.150845e-05 
## 
## $`1982`
##   (Intercept)           pce 
## -8.881640e-02  6.516215e-05 
## 
## $`1983`
##   (Intercept)           pce 
##  1.461015e-01 -4.402208e-05 
## 
## $`1984`
##   (Intercept)           pce 
##  7.892629e-02 -1.718497e-05 
## 
## $`1985`
##   (Intercept)           pce 
##  5.366118e-02 -6.926535e-06 
## 
## $`1986`
##   (Intercept)           pce 
##  5.384654e-02 -6.782516e-06 
## 
## $`1987`
##   (Intercept)           pce 
##  9.146640e-02 -1.980421e-05 
## 
## $`1988`
##   (Intercept)           pce 
##  5.122852e-02 -7.174276e-06 
## 
## $`1989`
##  (Intercept)          pce 
## 1.051097e-02 4.436762e-06 
## 
## $`1990`
##   (Intercept)           pce 
## -7.123114e-02  2.611286e-05 
## 
## $`1991`
##   (Intercept)           pce 
## -3.856927e-02  1.842612e-05 
## 
## $`1992`
##  (Intercept)          pce 
## 3.487276e-02 6.091330e-07 
## 
## $`1993`
##   (Intercept)           pce 
##  9.537911e-02 -1.371548e-05 
## 
## $`1994`
##   (Intercept)           pce 
##  1.295460e-01 -2.102375e-05 
## 
## $`1995`
##  (Intercept)          pce 
## 2.396737e-02 7.718004e-07 
## 
## $`1996`
##   (Intercept)           pce 
##  5.602360e-02 -5.567328e-06 
## 
## $`1997`
##   (Intercept)           pce 
##  7.968484e-02 -9.936855e-06 
## 
## $`1998`
##   (Intercept)           pce 
##  3.589534e-02 -2.283149e-06 
## 
## $`1999`
##   (Intercept)           pce 
##  3.922715e-02 -2.893646e-06 
## 
## $`2000`
##   (Intercept)           pce 
##  3.097125e-02 -1.601844e-06 
## 
## $`2001`
##   (Intercept)           pce 
## -1.881272e-01  3.001365e-05 
## 
## $`2002`
##  (Intercept)          pce 
## 1.428471e-02 2.014789e-06 
## 
## $`2003`
##   (Intercept)           pce 
##  4.025941e-02 -1.306818e-06 
## 
## $`2004`
##   (Intercept)           pce 
##  5.763951e-02 -3.640025e-06 
## 
## $`2005`
##   (Intercept)           pce 
##  5.777898e-02 -3.679151e-06 
## 
## $`2006`
##   (Intercept)           pce 
##  5.458272e-02 -3.368536e-06 
## 
## $`2007`
##   (Intercept)           pce 
## -1.721961e-02  4.187576e-06 
## 
## $`2008`
##   (Intercept)           pce 
##  1.784624e-01 -1.494605e-05 
## 
## $`2009`
##   (Intercept)           pce 
## -1.729902e-01  2.230078e-05 
## 
## $`2010`
##   (Intercept)           pce 
##  1.073378e-01 -5.844266e-06 
## 
## $`2011`
##   (Intercept)           pce 
##  1.041383e-01 -5.647401e-06 
## 
## $`2012`
##   (Intercept)           pce 
##  1.575956e-01 -1.070319e-05 
## 
## $`2013`
##   (Intercept)           pce 
##  2.101046e-01 -1.536441e-05 
## 
## $`2014`
##   (Intercept)           pce 
##  1.317146e-01 -8.590683e-06 
## 
## $`2015`
##   (Intercept)           pce 
##  1.176573e-01 -7.482080e-06
```

---

```r
slopes <- by_year %>%
	map(~mutate(.x, percent = unemploy / pop)) %>%
	map(~lm(percent ~ pce, data = .x)) %>%
	map(coef) %>%
	map_dbl(2)
slopes
```

---
class: inverse-blue middle
# More Practice 
## If any time remains

---
# Practice
* Compute the standard deviation of every mtcars column.
* Copy and run the following code to obtain 50 bootstrap samples

```r
bootstrap <- function(df) {
  df[sample(nrow(df), replace = TRUE), , drop = FALSE]
}
samples <- map(1:50, ~bootstrap(mtcars))
```

* Fit the following model to each bootstrap sample: `mpg ~ disp`
* Extract `$R^2$` and plot the distribution

---
class: inverse-green middle
# Next time
## Lab 2