Overview of R and the tidyverse

# ggplot2 and the Tidyverse

**Optional lab**

]

---

# Plan for today

.box-6.medium.sp-after-half[Packages and data]

.box-1.medium.sp-after-half[Visualize data with ggplot2]

.box-2.medium.sp-after-half[Transform data with dplyr]

---

# Packages and data

---

---

---

# Using packages

```r
install.packages("name")
```

```r
library("name")
```

---

# The tidyverse

.pull-left[
.box-inv-6.small["The tidyverse is an opinionated collection of R packages designed for data science. All packages share an underlying design philosophy, grammar, and data structures."]

.pull-right[
<figure>
  <img src="img/01/tidyverse.png" alt="The tidyverse" title="The tidyverse" width="100%">
</figure>
]

---

# The tidyverse

???

From "Master the Tidyverse" by RStudio

---

# The tidyverse package

```r
library(tidyverse)
```
]

.box-inv-6[The tidyverse package is a shortcut for<br>installing and loading all the key tidyverse packages]

---

```r
install.packages("tidyverse")
```

```r
install.packages("ggplot2")
install.packages("dplyr")
install.packages("tidyr")
install.packages("readr")
install.packages("purrr")
install.packages("tibble")
install.packages("stringr")
install.packages("forcats")
install.packages("lubridate")
install.packages("hms")
install.packages("DBI")
install.packages("haven")
install.packages("httr")
install.packages("jsonlite")
install.packages("readxl")
install.packages("rvest")
install.packages("xml2")
install.packages("modelr")
install.packages("broom")
```
]
]

```r
library("tidyverse")
```

```r
library("ggplot2")
library("dplyr")
library("tidyr")
library("readr")
library("purrr")
library("tibble")
library("stringr")
library("forcats")
```
]
]

---

# Data frames and tibbles

.box-inv-6.medium[Data frames are the most common kind of data objects; used for rectangular data (like spreadsheets)]

.box-6.small[(You really won't notice a difference in this class)]

---

# Vectors

```r
c(1, 4, 2, 5, 7)
```

```r
neat_numbers <- c(1, 4, 2, 5, 7)
```

---

# Basic data types

<table>
  <tr>
    <td><b>Integer</b></td>
    <td>Whole numbers</td>
    <td><code class="remark-inline-code">c(1, 2, 3, 4)</code></td>
  </tr>
  <tr>
    <td><b>Double</b></td>
    <td>Numbers</td>
    <td><code class="remark-inline-code">c(1, 2.4, 3.14, 4)</code></td>
  </tr>
  <tr>
    <td><b>Character</b></td>
    <td>Text</td>
    <td><code class="remark-inline-code">c("1", "blue", "fun", "monster")</code></td>
  </tr>
  <tr>
    <td><b>Logical</b></td>
    <td>True or false</td>
    <td><code class="remark-inline-code">c(TRUE, FALSE, TRUE, FALSE)</code></td>
  </tr>
  <tr>
    <td><b>Factor</b></td>
    <td>Category</td>
    <td><code class="remark-inline-code">c("Strongly disagree", "Agree", "Neutral")</code></td>
  </tr>
</table>

---

# Packages for importing data

<table>
  <tr>
    <td><img src="img/01/readr.png" alt="readr" title="readr" width="150px"></td>
    <td>Work with plain text data</td>
    <td><code class="remark-inline-code">my_data <- read_csv("file.csv")</code></td>
  </tr>
  <tr>
    <td><img src="img/01/readxl.png" alt="readxl" title="readxl" width="150px"></td>
    <td>Work with Excel files</td>
    <td><code class="remark-inline-code">my_data <- read_excel("file.xlsx")</code></td>
  </tr>
  <tr>
    <td><img src="img/01/haven.png" alt="haven" title="haven" width="150px"></td>
    <td>Work with Stata, SPSS, and SAS data</td>
    <td><code class="remark-inline-code">my_data <- read_stata("file.dta")</code></td>
  </tr>
</table>

---

# Visualize data<br>with ggplot2

.class-info[
<figure>
  <img src="img/01/ggplot-logo.png" alt="ggplot" title="ggplot" width="15%">
</figure>
]

---

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

---

???

Source: [Wikipedia](https://en.wikipedia.org/wiki/File:National_Museum_in_Poznan_-_Przej%C5%9Bcie_przez_Berezyn%C4%99.JPG)

---

---

# Long distance!

.center[
<figure>
  <img src="img/01/napoleon-google-maps.png" alt="Moscow to Vilnius" title="Moscow to Vilnius" width="80%">
  <figcaption>Moscow to Vilnius</figcaption>
</figure>
]

---

# Very cold!

---

# Lots of people died!

---

???

Source: [Wikimedia Commons](https://upload.wikimedia.org/wikipedia/commons/2/29/Minard.png)

---

---

# Mapping data to aesthetics

.pull-left.center[

]

.box-inv-1.medium[Aesthetic]

.box-1.sp-after[Position, shape, color, etc.]

.box-inv-1.medium[Data]

]

---

# Mapping data to aesthetics

<table>
  <tr>
    <th class="cell-left">Data</th>
    <th class="cell-left">Aesthetic</th>
    <th class="cell-left">Graphic/Geometry</th>
  </tr>
  <tr>
    <td class="cell-left">Longitude</td>
    <td class="cell-left">Position (x-axis)&emsp;</td>
    <td class="cell-left">Point</td>
  </tr>
  <tr>
    <td class="cell-left">Latitude</td>
    <td class="cell-left">Position (y-axis)</td>
    <td class="cell-left">Point</td>
  </tr>
  <tr>
    <td class="cell-left">Army size</td>
    <td class="cell-left">Size</td>
    <td class="cell-left">Path</td>
  </tr>
  <tr>
    <td class="cell-left">Army direction&emsp;</td>
    <td class="cell-left">Color</td>
    <td class="cell-left">Path</td>
  </tr>
  <tr>
    <td class="cell-left">Date</td>
    <td class="cell-left">Position (x-axis)</td>
    <td class="cell-left">Line + text</td>
  </tr>
  <tr>
    <td class="cell-left">Temperature</td>
    <td class="cell-left">Position (y-axis)</td>
    <td class="cell-left">Line + text</td>
  </tr>
</table>

---

# Mapping data to aesthetics

<table>
  <tr>
    <th class="cell-left">Data</th>
    <th class="cell-left"><code class="remark-inline-code">aes()</code></th>
    <th class="cell-left"><code class="remark-inline-code">geom</code></th>
  </tr>
  <tr>
    <td class="cell-left">Longitude</td>
    <td class="cell-left"><code class="remark-inline-code">x</code></td>
    <td class="cell-left"><code class="remark-inline-code">geom_point()</code></td>
  </tr>
  <tr>
    <td class="cell-left">Latitude</td>
    <td class="cell-left"><code class="remark-inline-code">y</code></td>
    <td class="cell-left"><code class="remark-inline-code">geom_point()</code></td>
  </tr>
  <tr>
    <td class="cell-left">Army size</td>
    <td class="cell-left"><code class="remark-inline-code">size</code></td>
    <td class="cell-left"><code class="remark-inline-code">geom_path()</code></td>
  </tr>
  <tr>
    <td class="cell-left">Army direction&emsp;</td>
    <td class="cell-left"><code class="remark-inline-code">color</code>&emsp;</td>
    <td class="cell-left"><code class="remark-inline-code">geom_path()</code></td>
  </tr>
  <tr>
    <td class="cell-left">Date</td>
    <td class="cell-left"><code class="remark-inline-code">x</code></td>
    <td class="cell-left"><code class="remark-inline-code">geom_line() + geom_text()</code></td>
  </tr>
  <tr>
    <td class="cell-left">Temperature</td>
    <td class="cell-left"><code class="remark-inline-code">y</code></td>
    <td class="cell-left"><code class="remark-inline-code">geom_line() + geom_text()</code></td>
  </tr>
</table>

---

# `ggplot()` template

<code class ='r hljs remark-code'>ggplot(data = <b><span style='background-color:#CBB5FF'>DATA</span></b>) +<br>&nbsp;&nbsp;<b><span style='background-color:#FFDFD1'>GEOM_FUNCTION</span></b>(mapping = aes(<b><span style='background-color:#FFD0CF'>AESTHETIC MAPPINGS</span></b>))</code>

<code class ='r hljs remark-code'>ggplot(data = <b><span style='background-color:#CBB5FF'>troops</span></b>) +<br>&nbsp;&nbsp;<b><span style='background-color:#FFDFD1'>geom_path</span></b>(mapping = aes(<b><span style='background-color:#FFD0CF'>x = longitude</span></b>,<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<b><span style='background-color:#FFD0CF'>y = latitude</span></b>,<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<b><span style='background-color:#FFD0CF'>color = direction</span></b>,<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<b><span style='background-color:#FFD0CF'>size = survivors</span></b>))</code>

---

<table>
 <thead>
  <tr>
   <th style="text-align:left;"> longitude </th>
   <th style="text-align:left;"> latitude </th>
   <th style="text-align:left;"> direction </th>
   <th style="text-align:left;"> survivors </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> 24 </td>
   <td style="text-align:left;"> 54.9 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> 340000 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 24.5 </td>
   <td style="text-align:left;"> 55 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> 340000 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
  </tr>
</tbody>
</table>

]

---

---

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

---

---

# Heavy cars with better mileage?

---

# Aesthetics

.box-inv-1.small[`color` (discrete)]

.box-inv-1.small[`color` (continuous)]

<img src="01_lab_files/figure-html/aes-color-continuous-1.png" width="100%" style="display: block; margin: auto;" />
]

.box-inv-1.small[`size`]

.box-inv-1.small[`fill`]

<img src="01_lab_files/figure-html/aes-fill-1.png" width="100%" style="display: block; margin: auto;" />
]

.box-inv-1.small[`shape`]

.box-inv-1.small[`alpha`]

<img src="01_lab_files/figure-html/aes-alpha-1.png" width="100%" style="display: block; margin: auto;" />
]

---

# Mapping columns to aesthetics

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

---

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

---

# ggplot playground

---

# How would you make this plot?

---

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

---

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

---

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

<img src="01_lab_files/figure-html/unnamed-chunk-16-1.png" width="100%" style="display: block; margin: auto;" />
]
]

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

<img src="01_lab_files/figure-html/unnamed-chunk-17-1.png" width="100%" style="display: block; margin: auto;" />
]
]

---

---

# What's the same? What's different?

.pull-left[
<img src="01_lab_files/figure-html/unnamed-chunk-18-1.png" width="100%" style="display: block; margin: auto;" />
]

.pull-right[
<img src="01_lab_files/figure-html/unnamed-chunk-19-1.png" width="100%" style="display: block; margin: auto;" />
]

---

# Geoms

---

# Possible geoms

<table>
  <tr>
    <th class="cell-left"></th>
    <th class="cell-left">Example geom</th>
    <th class="cell-left">What it makes</th>
  </tr>
  <tr>
    <td class="cell-left"><img src="img/01/geom_bar.png"></td>
    <td class="cell-left"><code class="remark-inline-code">geom_col()</code></td>
    <td class="cell-left">Bar charts</td>
  </tr>
  <tr>
    <td class="cell-left"><img src="img/01/geom_text.png"></td>
    <td class="cell-left"><code class="remark-inline-code">geom_text()</code></td>
    <td class="cell-left">Text</td>
  </tr>
  <tr>
    <td class="cell-left"><img src="img/01/geom_point.png"></td>
    <td class="cell-left"><code class="remark-inline-code">geom_point()</code></td>
    <td class="cell-left">Points</td>
  </tr>
  <tr>
    <td class="cell-left"><img src="img/01/geom_boxplot.png"></td>
    <td class="cell-left"><code class="remark-inline-code">geom_boxplot()</code>&emsp;</td>
    <td class="cell-left">Boxplots</td>
  </tr>
  <tr>
    <td class="cell-left"><img src="img/01/geom_sf.png"></td>
    <td class="cell-left"><code class="remark-inline-code">geom_sf()</code></td>
    <td class="cell-left">Maps</td>
  </tr>
</table>

---

# Possible geoms

.box-1[See [the **ggplot2** documentation](https://ggplot2.tidyverse.org/reference/index.html#section-layer-geoms) for<br>complete examples of all the different geom layers]

---

# Complex graphs!

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

---

# Complex graphs!

---

# Global vs. local

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

<img src="01_lab_files/figure-html/unnamed-chunk-22-1.png" width="60%" style="display: block; margin: auto;" />
]

---

# Global vs. local

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

<img src="01_lab_files/figure-html/unnamed-chunk-23-1.png" width="60%" style="display: block; margin: auto;" />
]

---

---

# So much more!

.box-inv-1[We sequentially add layers onto the foundational `ggplot()` plot to create complex figures]
]

---

# Putting it all together

.box-inv-1.medium[We can build a plot sequentially<br>to see how each grammatical layer<br>changes the appearance]

---

```r
*ggplot(data = mpg,
*      mapping = aes(x = displ,
*                    y = hwy,
*                    color = drv))
```
]

---

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

---

```r
ggplot(data = mpg,
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
  geom_point() +
* geom_smooth()
```
]

---

```r
ggplot(data = mpg,
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
  geom_point() +
* geom_smooth(method = "lm")
```
]

---

```r
ggplot(data = mpg,
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
  geom_point() +
  geom_smooth(method = "lm") +
* scale_color_viridis_d()
```
]

---

```r
ggplot(data = mpg,
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
  geom_point() +
  geom_smooth(method = "lm") +
  scale_color_viridis_d() +
* facet_wrap(vars(drv), ncol = 1)
```
]

---

```r
ggplot(data = mpg,
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
  geom_point() +
  geom_smooth(method = "lm") +
  scale_color_viridis_d() +
  facet_wrap(vars(drv), ncol = 1) +
* labs(x = "Displacement", y = "Highway MPG",
*      color = "Drive",
*      title = "Heavier cars get lower mileage",
*      subtitle = "Displacement indicates weight(?)",
*      caption = "I know nothing about cars")
```
]

---

```r
ggplot(data = mpg,
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
  geom_point() +
  geom_smooth(method = "lm") +
  scale_color_viridis_d() +
  facet_wrap(vars(drv), ncol = 1) +
  labs(x = "Displacement", y = "Highway MPG",
       color = "Drive", 
       title = "Heavier cars get lower mileage",
       subtitle = "Displacement indicates weight(?)",
       caption = "I know nothing about cars") +
* theme_bw()
```
]

---

```r
ggplot(data = mpg, 
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
  geom_point() +
  geom_smooth(method = "lm") +
  scale_color_viridis_d() +
  facet_wrap(vars(drv), ncol = 1) +
  labs(x = "Displacement", y = "Highway MPG",
       color = "Drive", 
       title = "Heavier cars get lower mileage",
       subtitle = "Displacement indicates weight(?)",
       caption = "I know nothing about cars") +
  theme_bw() +
* theme(legend.position = "bottom",
*       plot.title = element_text(face = "bold"))
```
]

---

```r
ggplot(data = mpg, 
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
  geom_point() +
  geom_smooth(method = "lm") + 
  scale_color_viridis_d() +
  facet_wrap(vars(drv), ncol = 1) +
  labs(x = "Displacement", y = "Highway MPG",
       color = "Drive", 
       title = "Heavier cars get lower mileage",
       subtitle = "Displacement indicates weight(?)",
       caption = "I know nothing about cars") +
  theme_bw() +
  theme(legend.position = "bottom",
        plot.title = element_text(face = "bold"))
```
]

---

# Transform data<br>with dplyr

.class-info[
<figure>
  <img src="img/01/dplyr.png" alt="dplyr" title="dplyr" width="15%">
</figure>
]

---

```r
gapminder
```

```
## # A tibble: 1,704 x 6
##    country     continent  year lifeExp      pop gdpPercap
##    <fct>       <fct>     <int>   <dbl>    <int>     <dbl>
##  1 Afghanistan Asia       1952    28.8  8425333      779.
##  2 Afghanistan Asia       1957    30.3  9240934      821.
##  3 Afghanistan Asia       1962    32.0 10267083      853.
##  4 Afghanistan Asia       1967    34.0 11537966      836.
##  5 Afghanistan Asia       1972    36.1 13079460      740.
##  6 Afghanistan Asia       1977    38.4 14880372      786.
##  7 Afghanistan Asia       1982    39.9 12881816      978.
##  8 Afghanistan Asia       1987    40.8 13867957      852.
##  9 Afghanistan Asia       1992    41.7 16317921      649.
## 10 Afghanistan Asia       1997    41.8 22227415      635.
## # … with 1,694 more rows
```
]

---

# The tidyverse

???

From "Master the Tidyverse" by RStudio

---

# The tidyverse

.center[
<figure>
  <img src="img/01/tidyverse.png" alt="The tidyverse" title="The tidyverse" width="50%">
</figure>
]

---

# dplyr: verbs for manipulating data

<table>
  <tr>
    <td>Extract rows with <code>filter()</code></td>
    <td><img src="img/01/filter.png" alt="filter" title="filter" height="80px"></td>
  </tr>
  <tr>
    <td>Extract columns with <code>select()</code></td>
    <td><img src="img/01/select.png" alt="select" title="select" height="80px"></td>
  </tr>
  <tr>
    <td>Arrange/sort rows with <code>arrange()</code></td>
    <td><img src="img/01/arrange.png" alt="arrange" title="arrange" height="80px"></td>
  </tr>
  <tr>
    <td>Make new columns with <code>mutate()</code></td>
    <td><img src="img/01/mutate.png" alt="mutate" title="mutate" height="80px"></td>
  </tr>
  <tr>
    <td>Make group summaries with<br><code>group_by() %>% summarize()</code></td>
    <td><img src="img/01/summarize.png" alt="summarize" title="summarize" height="80px"></td>
  </tr>
</table>

---

# `filter()`

---

# `filter()`

<code class ='r hljs remark-code'>filter(.data = <b><span style='background-color:#FFDFD1'>DATA</span></b>, <b><span style='background-color:#FFD0CF'>...</span></b>)</code>
]

.pull-right[
- <b><span style="background: #FFDFD1">`DATA`</span></b> = Data frame to transform
- <b><span style="background: #FFD0CF">`...`</span></b> = One or more tests <br>.small[`filter()` returns each row for which the test is TRUE]
]

---

<code class ='r hljs remark-code'>filter(.data = <b><span style='background-color:#FFDFD1'>gapminder</span></b>, <b><span style='background-color:#FFD0CF'>country == "Denmark"</span></b>)</code>

.pull-left[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> country </th>
   <th style="text-align:left;"> continent </th>
   <th style="text-align:left;"> year </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1952 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1957 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1962 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1967 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1972 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
  </tr>
</tbody>
</table>
]

.pull-right[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> country </th>
   <th style="text-align:left;"> continent </th>
   <th style="text-align:right;"> year </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Denmark </td>
   <td style="text-align:left;"> Europe </td>
   <td style="text-align:right;"> 1952 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Denmark </td>
   <td style="text-align:left;"> Europe </td>
   <td style="text-align:right;"> 1957 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Denmark </td>
   <td style="text-align:left;"> Europe </td>
   <td style="text-align:right;"> 1962 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Denmark </td>
   <td style="text-align:left;"> Europe </td>
   <td style="text-align:right;"> 1967 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Denmark </td>
   <td style="text-align:left;"> Europe </td>
   <td style="text-align:right;"> 1972 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Denmark </td>
   <td style="text-align:left;"> Europe </td>
   <td style="text-align:right;"> 1977 </td>
  </tr>
</tbody>
</table>
]

---

# `filter()`

<code class ='r hljs remark-code'>filter(.data = <b><span style='background-color:#FFDFD1'>gapminder</span></b>, <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<b><span style='background-color:#FFD0CF'>country == "Denmark"</span></b>)</code>
]

---

# Logical tests

<table>
  <tr>
    <th class="cell-center">Test</th>
    <th class="cell-left">Meaning</th>
    <th class="cell-center">Test</th>
    <th class="cell-left">Meaning</th>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">x < y</code></td>
    <td class="cell-left">Less than</td>
    <td class="cell-center"><code class="remark-inline-code">x %in% y</code></td>
    <td class="cell-left">In (group membership)</td>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">x > y</code></td>
    <td class="cell-left">Greater than</td>
    <td class="cell-center"><code class="remark-inline-code">is.na(x)</code></td>
    <td class="cell-left">Is missing</td>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">==</code></td>
    <td class="cell-left">Equal to</td>
    <td class="cell-center"><code class="remark-inline-code">!is.na(x)</code></td>
    <td class="cell-left">Is not missing</td>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">x <= y</code></td>
    <td class="cell-left">Less than or equal to</td>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">x >= y</code></td>
    <td class="cell-left">Greater than or equal to</td>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">x != y</code></td>
    <td class="cell-left">Not equal to</td>
  </tr>
</table>

---

# Your turn #1: Filtering

1. The data for Canada
2. All data for countries in Oceania
3. Rows where the life expectancy is greater than 82

---

```r
filter(gapminder, country == "Canada")
```
]

```r
filter(gapminder, continent == "Oceania")
```
]

```r
filter(gapminder, lifeExp > 82)
```
]

---

# Common mistakes

<code class ='r hljs remark-code'>filter(gapminder, <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;country <b><span style='color:#FF4136'>=</span></b> "Canada")</code>

<code class ='r hljs remark-code'>filter(gapminder, <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;country <b><span style='color:#2ECC40'>==</span></b> "Canada")</code>
]

<code class ='r hljs remark-code'>filter(gapminder, <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;country == <b><span style='color:#FF4136'>Canada</span></b>)</code>

<code class ='r hljs remark-code'>filter(gapminder, <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;country == <b><span style='color:#2ECC40'>"Canada"</span></b>)</code>
]

---

# `filter()` with multiple conditions

<code class ='r hljs remark-code'>filter(<b><span style='background-color:#FFDFD1'>gapminder</span></b>, <b><span style='background-color:#FFD0CF'>country == "Denmark", year > 2000</span></b>)</code>

---

<code class ='r hljs remark-code'>filter(<b><span style='background-color:#FFDFD1'>gapminder</span></b>, <b><span style='background-color:#FFD0CF'>country == "Denmark", year > 2000</span></b>)</code>

---

# Boolean operators

<table>
  <tr>
    <th class="cell-center">Operator</th>
    <th class="cell-center">Meaning</th>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">a & b</code></td>
    <td class="cell-center">and</td>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">a | b</code></td>
    <td class="cell-center">or</td>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">!a</code></td>
    <td class="cell-center">not</td>
  </tr>
</table>

---

# Default is "and"

<code class ='r hljs remark-code'>filter(<b><span style='background-color:#FFDFD1'>gapminder</span></b>, <b><span style='background-color:#FFD0CF'>country == "Denmark", year > 2000</span></b>)</code>

<code class ='r hljs remark-code'>filter(<b><span style='background-color:#FFDFD1'>gapminder</span></b>, <b><span style='background-color:#FFD0CF'>country == "Denmark" & year > 2000</span></b>)</code>

---

# Your turn #2: Filtering

1. Canada before 1970
2. Countries where life expectancy in 2007 is below 50
3. Countries where life expectancy in 2007 is below 50 and are not in Africa

---

```r
filter(gapminder, country == "Canada", year < 1970)
```

```r
filter(gapminder, year == 2007, lifeExp < 50)
```

```r
filter(gapminder, year == 2007, lifeExp < 50, 
       continent != "Africa")
```

---

# Common mistakes

<code class ='r hljs remark-code'>filter(gapminder, <b><span style='color:#FF4136'>1960 &lt; year &lt; 1980</span></b>)</code>
]

<code class ='r hljs remark-code'>filter(gapminder, <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<b><span style='color:#2ECC40'>year > 1960, year &lt; 1980</span></b>)</code>
]
]

<code class ='r hljs remark-code'>filter(gapminder, <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<b><span style='color:#FF4136'>country == "Mexico", <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;country == "Canada", <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;country == "United States"</span></b>)</code>
]

<code class ='r hljs remark-code'>filter(gapminder, <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<b><span style='color:#2ECC40'>country %in% c("Mexico", "Canada", <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;"United States")</span></b>)</code>
]
]

---

# Common syntax

<code class ='r hljs remark-code'><b><span style='background-color:#EFB3FF'>VERB</span></b>(<b><span style='background-color:#FFDFD1'>DATA</span></b>, <b><span style='background-color:#FFD0CF'>...</span></b>)</code>
]

.pull-right[
- <b><span style="background: #EFB3FF">`VERB`</span></b> = dplyr function/verb
- <b><span style="background: #FFDFD1">`DATA`</span></b> = Data frame to transform
- <b><span style="background: #FFD0CF">`...`</span></b> = Stuff the verb does
]

---

# `mutate()`

<code class ='r hljs remark-code'>mutate(<b><span style='background-color:#FFDFD1'>.data</span></b>, <b><span style='background-color:#FFD0CF'>...</span></b>)</code>
]

.pull-right[
- <b><span style="background: #FFDFD1">`DATA`</span></b> = Data frame to transform
- <b><span style="background: #FFD0CF">`...`</span></b> = Columns to make
]

---

<code class ='r hljs remark-code'>mutate(<b><span style='background-color:#FFDFD1'>gapminder</span></b>, <b><span style='background-color:#FFD0CF'>gdp = gdpPercap * pop</span></b>)</code>

.pull-left.small[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> country </th>
   <th style="text-align:left;"> year </th>
   <th style="text-align:left;"> gdpPercap </th>
   <th style="text-align:left;"> pop </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> 1952 </td>
   <td style="text-align:left;"> 779.4453145 </td>
   <td style="text-align:left;"> 8425333 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> 1957 </td>
   <td style="text-align:left;"> 820.8530296 </td>
   <td style="text-align:left;"> 9240934 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> 1962 </td>
   <td style="text-align:left;"> 853.10071 </td>
   <td style="text-align:left;"> 10267083 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> 1967 </td>
   <td style="text-align:left;"> 836.1971382 </td>
   <td style="text-align:left;"> 11537966 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> 1972 </td>
   <td style="text-align:left;"> 739.9811058 </td>
   <td style="text-align:left;"> 13079460 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
  </tr>
</tbody>
</table>
]

.pull-right.small[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> country </th>
   <th style="text-align:right;"> year </th>
   <th style="text-align:left;"> … </th>
   <th style="text-align:right;"> gdp </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1952 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 6567086330 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1957 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 7585448670 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1962 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 8758855797 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1967 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 9648014150 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1972 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 9678553274 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1977 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 11697659231 </td>
  </tr>
</tbody>
</table>
]

---

<code class ='r hljs remark-code'>mutate(<b><span style='background-color:#FFDFD1'>gapminder</span></b>, <b><span style='background-color:#FFD0CF'>gdp = gdpPercap * pop,</span></b><br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<b><span style='background-color:#FFD0CF'>pop_mil = round(pop / 1000000)</span></b>)</code>

.pull-right.small[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> country </th>
   <th style="text-align:right;"> year </th>
   <th style="text-align:left;"> … </th>
   <th style="text-align:right;"> gdp </th>
   <th style="text-align:right;"> pop_mil </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1952 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 6567086330 </td>
   <td style="text-align:right;"> 8 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1957 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 7585448670 </td>
   <td style="text-align:right;"> 9 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1962 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 8758855797 </td>
   <td style="text-align:right;"> 10 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1967 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 9648014150 </td>
   <td style="text-align:right;"> 12 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1972 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 9678553274 </td>
   <td style="text-align:right;"> 13 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1977 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 11697659231 </td>
   <td style="text-align:right;"> 15 </td>
  </tr>
</tbody>
</table>
]

---

# `ifelse()`

<code class ='r hljs remark-code'>ifelse(<b><span style='background-color:#FFC0DC'>TEST</span></b>, <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<b><span style='background-color:#FFDFD1'>VALUE_IF_TRUE</span></b>, <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<b><span style='background-color:#CBB5FF'>VALUE_IF_FALSE</span></b>)</code>
]

.pull-right[
- <b><span style="background: #FFC0DC">`TEST`</span></b> = A logical test
- <b><span style="background: #FFDFD1">`VALUE_IF_TRUE`</span></b> = What happens if test is true
- <b><span style="background: #CBB5FF">`VALUE_IF_FALSE`</span></b> = What happens if test is false
]

---

<code class ='r hljs remark-code'>mutate(gapminder, <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;after_1960 = ifelse(<b><span style='background-color:#FFC0DC'>year > 1960</span></b>, <b><span style='background-color:#FFDFD1'>TRUE</span></b>, <b><span style='background-color:#CBB5FF'>FALSE</span></b>))</code>

<code class ='r hljs remark-code'>mutate(gapminder, <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;after_1960 = ifelse(<b><span style='background-color:#FFC0DC'>year > 1960</span></b>, <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<b><span style='background-color:#FFDFD1'>"After 1960"</span></b>, <br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<b><span style='background-color:#CBB5FF'>"Before 1960"</span></b>))</code>

---

# Your turn #3: Mutating

1. Add an `africa` column that is TRUE if the country is on the African continent
2. Add a column for logged GDP per capita (hint: use `log()`)
3. Add an `africa_asia` column that says “Africa or Asia” if the country is in Africa or Asia, and “Not Africa or Asia” if it’s not

---

```r
mutate(gapminder, africa = ifelse(continent == "Africa", 
                                  TRUE, FALSE))
```

```r
mutate(gapminder, log_gdpPercap = log(gdpPercap))
```

```r
mutate(gapminder, 
       africa_asia = 
         ifelse(continent %in% c("Africa", "Asia"), 
                "Africa or Asia", 
                "Not Africa or Asia"))
```

---