Day 5

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# Day 5
## Data wrangling
### Michael W. Kearney📊 School of Journalism Informatics Institute University of Missouri
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<tr>
<th style="padding-right:75px!important">
<a href="https://twitter.com/kearneymw"> </a>
</th>
<th style="padding-left:75px!important">
<a href="https://github.com/mkearney"> </a>
</th>
</tr>
<tr style="background-color:#fff">
<th style="padding-right:75px!important">
<a href="https://twitter.com/kearneymw"> @kearneymw </a>
</th>
<th style="padding-left:75px!important">
<a href="https://github.com/mkearney"> @mkearney </a>
</th>
</tr>
</table>

---

Build course directory on your computer:

``` r
source(
  "https://raw.githubusercontent.com/mkearney/stat/master/R/build-course.R"
)
```

---
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## Agenda

---

## Agenda
+ Computing basics
+ Tidyverse
   - Visualizing
   - Transform
   - Tidy
   - Data types

---
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## Computing basics

---

## File/directory awareness
+ Every computer has a file/directory system
+ There's a default or home folder
   
   ```r
   ## use this to see your home folder
   normalizePath("~")
   #> [1] "/Users/kearneymw"
   ```
+ Files are organized like a tree
   - You can move from one branch to another
   - Moving from one folder to another is linear

---

## Bash shortcuts
+ Most popular conventions from bash/terminal found in R scripts
   - `..` to go back a folder or `../..` to go back two folders
   ``` sh
   ls ../tidyverse
   ls ../..
   ```
   - `~` as a shortcut for home, e.g., `~/R/stat`
   ``` sh
   ls ~/R/stat
   ```

---

## Don't fall asleep yet!
Why should you care?

+ Because you need to know where things are to interact with them!
+ Because you want to be able to replicate your work!

> **tl;dr**:
> Open your file browser.
> See how they're organized?
> Yeah? Good!

---

## Don't let these terms confuse you

The name or `basename()` of a file/folder:

+ **File** is **name**/location of a file
+ **Folder** is **name**/location of a file folder

The name or `dirname()` of a file/folder:

+ **Path** is name/**location** of a file
+ **Directory** is name/**location** of a file folder

---
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## Do unto <huge>future you</huge> as you would have future you do unto <huge> you</huge>.

---

## FutuRe you
Using scripts and writing clear code makes life easier

+ It's writing down point/click routines you don't have to memorize
+ Internet is full of scripts you can customize
+ With some notes and attention, future you will be very happy with current you!

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## Tidyverse

---

## Cheatsheets

+ Check out [Rstudio cheatsheets](https://www.rstudio.com/resources/cheatsheets/)

---

## Notebooks

1. [Visualize](../tidyverse/01-visualize.Rmd)
1. [Transform)](../tidyverse/02-transform.Rmd)
1. [Tidy](../tidyverse/03-tidy.Rmd)
1. [Data types](../tidyverse/04-data-types.Rmd)

---
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## Visualize

---

## Setup

```r
## load tidyverse
library(tidyverse)
```

```r
## preview data
print(mpg, n = 6)
```

| manufacturer | model | displ | year | cyl |   trans    | drv | cty | hwy | fl |  class  |
|:------------:|:-----:|:-----:|:----:|:---:|:----------:|:---:|:---:|:---:|:--:|:-------:|
|     audi     |  a4   |  1.8  | 1999 |  4  |  auto(l5)  |  f  | 18  | 29  | p  | compact |
|     audi     |  a4   |  1.8  | 1999 |  4  | manual(m5) |  f  | 21  | 29  | p  | compact |
|     audi     |  a4   |  2.0  | 2008 |  4  | manual(m6) |  f  | 20  | 31  | p  | compact |
|     audi     |  a4   |  2.0  | 2008 |  4  |  auto(av)  |  f  | 21  | 30  | p  | compact |
|     audi     |  a4   |  2.8  | 1999 |  6  |  auto(l5)  |  f  | 16  | 26  | p  | compact |
|     audi     |  a4   |  2.8  | 1999 |  6  | manual(m5) |  f  | 18  | 26  | p  | compact |

---

## Your Turn 1

```r
ggplot(data = mpg) +
  geom_point(mapping = aes(x = displ, y = hwy))
```

---

## Breakdown

1. "Initialize" a plot with `ggplot()`
1. Add layers with `geom_` functions

**Template**:

``` r
ggplot(data = <DATA>) +
 <GEOM_FUNCTION>(mapping = aes(<MAPPINGS>))

ggplot(data = mpg) +
  geom_point(mapping = aes(x = displ, y = hwy))
```

---

## Your Turn 2

In the next chunk, add color, size, alpha, and shape aesthetics to your graph. Experiment.

+ Do different things happen when you map aesthetics to discrete and continuous variables?
+ What happens when you use more than one aesthetic?

---

Inside of `aes()`: maps an aesthetic to a variable

```r
ggplot(mpg) + geom_point(aes(x = displ, y = hwy, color = class))
```

---

Outside of `aes()`: sets an aesthetic to a value

```r
ggplot(mpg) + geom_point(aes(x = displ, y = hwy), color = "blue")
```

## Geoms

## Geoms

The previous plots differ by geom.

```
ggplot(data = <DATA>) +
 <GEOM_FUNCTION>(mapping = aes(<MAPPINGS>))
```

---

## Your Turn 3

With your partner, decide how to replace this scatterplot with one that draws boxplots? Use the cheatsheet. Try your best guess.

``` r
ggplot(mpg) + geom_point(aes(class, hwy))
```

---

## Your Turn 4

With your partner, make the histogram of hwy below. Use the cheatsheet. Hint: do not supply a y variable.

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## [Transform](https://github.com/cwickham/data-science-in-tidyverse/blob/master/slides/02-Transform.pdf)

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## [Tidy](https://github.com/cwickham/data-science-in-tidyverse/blob/master/slides/03-Tidy.pdf)

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## [Data types](https://github.com/cwickham/data-science-in-tidyverse/blob/master/slides/05-Data-Types.pdf)