---
title: "Filter & Storms dataset"
subtitle: "Create subsets data" 
format: html
date: today
toc: true
toc-title: Outline
---

## Warm-up

1.  What's wrong with the following code

```{r}
library(tidyverse)
library(gapminder)
ggplot(gapminder,aes(x="year",y="pop")) + geom_point()
```

2. Create an R-script that does the following.
  i. Load the gapminder data
  ii. Create a variable where each value is a country in the gapminder data set, with *no repeats*.
  iii. Use `%in%` to see if the variable contains various countries of your choice.
  iv. Note how to execute the script using the keypad, one way to execute a script.
  
```{r}
#| eval: FALSE
source("my_script.R",echo = TRUE)
```

## The filter command

Below we make a subset of the data, whose `country` is China

```{r}
C <- filter(gapminder, 
       country == "China")
```

Do a `?filter` to learn how else to modify the 2nd parameter using `& , |` and more.

Use a filter to reduce the size of the data and then label points on a scatterplot using `geom_text_repel` 

```{r}
library(ggrepel)
hi_pop_countries <- filter(gapminder, 
                           pop > 500000000)
ggplot(hi_pop_countries, 
       aes(x = year, y = gdpPercap)) + 
       geom_point() + 
       geom_text_repel(aes(label = country))
```

Here's another filter and preview of boxplots & the `reorder` function.  
```{r}
hi_pop_countries <- filter(gapminder, 
                           pop > 50000000)
ggplot(hi_pop_countries, 
       aes(x = lifeExp, y = reorder(country,lifeExp))) + 
    geom_boxplot()
```

And here's a histogram:

```{r}
TCU <- filter(gapminder,country %in% c("Taiwan","China","United States"))

TCU |> ggplot(aes(x = lifeExp, fill = country)) + geom_histogram(bins = 10)
```

## Explore the storms dataset 

The `data()` command lists all dataset included with R and the Tidyverse.  Note that the *storms* data is in `dplyr`.   

Use filter and varioius geoms `geom_point(), geom_histogram(), geom_boxplot()`.  to compare storms across time.  

## Assignment 3

Complete these exercises from the text.  Append your answers to the quarto doc for Assignment 2.  Submit as a .html doc.  


1. <https://r4ds.hadley.nz/data-visualize.html#exercises>

2. <https://r4ds.hadley.nz/data-visualize#exercises-1>