---
title: "Data Wrangling"
author: "Prof. Eric A. Suess"
format: revealjs
---

## Data Wrangling

Today we will get started with Data Wrangling.  

Data Wrangling is the process of tidying into usable forms.

The R package that will be using from the [tidyverse](https://www.tidyverse.org/) is the [dplyr](https://dplyr.tidyverse.org/) package.


## The grammar of data wrangling

The 5 verbs of data wrangling

**select()**  # take a subset of columns

**filter()**  # take a subset of rows

**mutate()**  # add or modify existing columns

**arrange()**  # sort the rows

**summarize()**  # aggregate the data across rows

## RStudio Cheatsheet for dplyr

The RStudio [dplyr cheatsheet](https://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf) is very useful.

## Star Wars examples

```{r echo=TRUE, message=FALSE}
library(tidyverse)
data("starwars")
glimpse(starwars)
```

## Star Wars

```{r echo=TRUE}
starwars %>% select(name, species)
```

## Star Wars

```{r echo=TRUE}
starwars %>% 
  filter(species == "Droid")
```

## Star Wars

```{r echo=TRUE}
starwars %>% 
  select(name, ends_with("color"))
```

## Star Wars

```{r echo=TRUE}
starwars %>% 
  mutate(name, bmi = mass / ((height / 100)  ^ 2)) %>%
  select(name:mass, bmi)
```

## Star Wars

```{r echo=TRUE}
starwars %>% 
  arrange(desc(mass))
```

## Star Wars

```{r echo=TRUE}
starwars %>%
  group_by(species) %>%
  summarise(
    n = n(),
    mass = mean(mass, na.rm = TRUE)
  ) %>%
  filter(n > 1)
```

## Presidential examples

Try the code from the book in Section 4.1

```{r echo=TRUE}
presidential
```