08-Organize.Rmd

---
title: "Organize with List Columns"
output: html_notebook
---

<!-- This file by Charlotte Wickham is licensed under a Creative Commons Attribution 4.0 International License, adapted from the orignal work at https://github.com/rstudio/master-the-tidyverse by RStudio. -->

```{r setup}
library(tidyverse)
library(gapminder)
library(broom)

nz <- gapminder %>%
  filter(country == "New Zealand")
us <- gapminder %>%
  filter(country == "United States")
```

## Your turn 1

How has life expectancy changed over time?
Make a line plot of lifeExp vs. year grouped by country.  
Set alpha to 0.2, to see the results better.

```{r}
gapminder


```

## Quiz

How is a data frame/tibble similar to a list?

## Quiz

If one of the elements of a list can be another list,
can one of the columns of a data frame be another list?

## Your turn 2

Run this chunk:
```{r}
gapminder_nested <- gapminder %>%
  group_by(country) %>%
  nest()

fit_model <- function(df) lm(lifeExp ~ year, data = df)

gapminder_nested <- gapminder_nested %>% 
  mutate(model = map(data, fit_model))

get_rsq <- function(mod) glance(mod)$r.squared

gapminder_nested <- gapminder_nested %>% 
  mutate(r.squared = map_dbl(model, get_rsq))
```

Then filter `gapminder_nested` to find the countries with r.squared less than 0.5.  

```{r}

```

## Your Turn 3

Edit the code in the chunk provided to instead find and plot countries with a slope above 0.6 years/year.

```{r}
get_slope <- function(mod) {
  tidy(mod) %>% filter(term == "year") %>% pull(estimate)
}

# Add new column with r-sqaured
gapminder_nested <- gapminder_nested %>% 
  mutate(r.squared = map_dbl(model, get_rsq))

# filter out low r-squared countries
poor_fit <- gapminder_nested %>% 
  filter(r.squared < 0.5)

# unnest and plot result
unnest(poor_fit, data) %>%
  ggplot(aes(x = year, y = lifeExp)) + 
    geom_line(aes(color = country))
```

## Your Turn 4

**Challenge:**

1. Create your own copy of `gapminder_nested` and then add one more list column: `output` which contains the output of `augment()` for each model.


```{r}

```

# Take away