Data Viz with ggplot2

class: center, middle

# More Graphing with `ggplot2`
<img src="img/hero_wall_pink.png" width="800px"/>

## Kelly McConville

.large[Math 241 | Week 2 | Spring 2021]

---

# Announcements

* Lab 1 due on Gradescope on Monday!
    + Colored pencils outside my office (end of 3rd floor of Library).

* Lab 2 posted in the shared folder on the RStudio Server.
    + Due next Thursday by 8:30am on Gradescope.

*  Make sure to add your GitHub username to [this sheet](https://docs.google.com/spreadsheets/d/1nvM8jJDUvp8H5iYF59aKNdnJlqy_aW18R6d6DBUPeSU/edit?usp=sharing).

* If you have group member preferences for the mini-projects, fill out [this form](https://forms.gle/6UHStiAh4ZvKXej1A) by Friday, Feb 5th.

---

## Goals for Today

* Reproducible workflow

* `reprex`
    + A productive way to ask for help and to give help

* More `ggplot2`
    + Additional geoms
    + Scale
    + Color
    + Themes

* Context
    + Take a sad graph and make it better...

* Not discussed: Visualizing spatial data with maps
    + Will cover later in the course!

---

## Reproducible Workflow

* One where if you shared your data and work with someone else, they could reproduce your results.

* Not the same as **replication**: Where someone collects new data following your same design to see if they get the same results.

* `RMarkdown` documents allow us to include our R code, output, and narrative in the same place. 
    + Load the **raw** data.
    + Be transparent about all the analysis steps.
    + Even if you don't showcase the `R` code in the output file, it is contained in the `Rmd` file.

---

## Creating `repr`oducible `ex`amples with `reprex`

Why do I need to learn to create reproducible technical examples?

So you can participate on Stack Overflow, R help mailing lists, or our class Slack channel or in a GitHub Issue!

* More on GitHub next week!

---

## What is wrong with this question?

I am trying to create a plot and I can't get the bars to do what I want them to.  Help?!

---

## What is wrong with this coding question?

I want to do the following but it isn't working:

thing <- read.csv("long/file/path/thing.csv")

ggplot(thing, aes(x = that)) + geom_bar() + scale_x_discrete(c("thing1", "thing2", "thing3"))

Help?!

---

## What is wrong with this coding question?

I want to reorder the bars of my plot but can't get it working.  Help!

```r
library(tidyverse)

mtcars <- mtcars %>%
  group_by(cyl) %>%
  mutate(mean_mpg = mean(mpg)) %>%
  ungroup() %>%
  mutate(heavy = case_when(wt < mean(wt) ~ "no",
                           wt >= mean(wt) ~ "yes"))

mtcars %>%
  ggplot(mapping = aes(x = factor(cyl))) +
  geom_bar()

mtcars %>%
  count(heavy)
```

```
## # A tibble: 2 x 2
##   heavy     n
##   <chr> <int>
## 1 no       16
## 2 yes      16
```

---

## What is wrong with this coding question?

I want to reorder the bars of my plot but can't get it working.  Help!

```r
rm(list = ls())

library(tidyverse)

mtcars %>%
  ggplot(mapping = aes(x = factor(cyl))) +
  geom_bar()
```

---

## [What makes a good coding question?](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example)

* It uses a **minimal** dataset to reproduce the issue.

* It includes the **shortest** amount of  **runnable** code necessary to reproduce the issue.

* It includes any necessary information on the used packages, R version, system, etc.

* For random processes, it uses `set.seed(insert #)` for reproducibility.

* It doesn't wreak havoc on other people's computers.

* It includes code **and output** so that others don't have to run it!

---

## Minimal Dataset

Create a toy data frame.

```r
dat <- data.frame(animal = c("cat", "dog", "mouse"), 
                  weight = c(5, 10, 0.5))
dat
```

```
##   animal weight
## 1    cat    5.0
## 2    dog   10.0
## 3  mouse    0.5
```

Use a built-in dataset or a dataset from a particular package.

```r
library(help = "datasets")
?mtcars
```

---

# [`datapasta`](https://cran.r-project.org/web/packages/datapasta/vignettes/datapasta-in-the-cloud.html)

If you really want to use a specific dataset, you can use `datapasta` to create a dataframe.

* But don't use a large dataset in your `reprex`.

**Steps**:

* Install `datapasta`.    
* Grab [some data](https://www.nytimes.com/interactive/2017/05/25/sunday-review/opinion-pell-table.html).
* Paste into an empty R script.
* Select all and go to the `Addins` and select `Paste as data.frame`.
* Notice that the text has transformed into code defining data!
* Grab code, write `dat_name <- ` and paste in code.

---

## Minimal Code

Include the **necessary** libraries.

Test run the code in a restarted R session to make sure it is runnable!

```r
library(tidyverse)

mtcars %>%
  arrange(cyl) %>%
  ggplot(mapping = aes(x = factor(cyl))) +
  geom_bar()
```

---

## Make sure your code is copy-and-paste-able!

Don't copy from the console.

```r
> library(tidyverse)
> 
> mtcars %>%
+   arrange(cyl) %>%
+   ggplot(mapping = aes(x = factor(cyl))) +
+   geom_bar()
```

---

## Make sure your code is copy-and-paste-able!

No screenshots!

![](img/screenShotCode.png)

---

## What Else to Include?

(Don't need to do this for our class Slack channel)

* R Version

* Platform

```r
sessionInfo()
```

```
## R version 4.0.3 (2020-10-10)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Debian GNU/Linux 10 (buster)
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.8.0
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.8.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] forcats_0.5.0   stringr_1.4.0   dplyr_1.0.2     purrr_0.3.4    
##  [5] readr_1.4.0     tidyr_1.1.2     tibble_3.0.4    ggplot2_3.3.3  
##  [9] tidyverse_1.3.0 knitr_1.30     
## 
## loaded via a namespace (and not attached):
##  [1] tidyselect_1.1.0  xfun_0.19         haven_2.3.1       colorspace_2.0-0 
##  [5] vctrs_0.3.6       generics_0.1.0    htmltools_0.5.0   yaml_2.2.1       
##  [9] utf8_1.1.4        rlang_0.4.10.9000 pillar_1.4.7      glue_1.4.2       
## [13] withr_2.3.0       DBI_1.1.0         dbplyr_2.0.0      modelr_0.1.8     
## [17] readxl_1.3.1      lifecycle_0.2.0   munsell_0.5.0     gtable_0.3.0     
## [21] cellranger_1.1.0  rvest_0.3.6       evaluate_0.14     labeling_0.4.2   
## [25] fansi_0.4.1       broom_0.7.3       Rcpp_1.0.5        scales_1.1.1     
## [29] backports_1.2.1   jsonlite_1.7.2    farver_2.0.3      fs_1.5.0         
## [33] hms_0.5.3         digest_0.6.27     stringi_1.5.3     xaringan_0.19    
## [37] grid_4.0.3        cli_2.2.0         tools_4.0.3       magrittr_2.0.1   
## [41] crayon_1.3.4      pkgconfig_2.0.3   ellipsis_0.3.1    xml2_1.3.2       
## [45] reprex_1.0.0      lubridate_1.7.9.2 assertthat_0.2.1  rmarkdown_2.6    
## [49] httr_1.4.2        rstudioapi_0.13   R6_2.5.0          compiler_4.0.3
```

---

## What Else to Include?

* If it is a problem with a specific package, include the version.

```r
packageVersion("tidyverse")
```

```
## [1] '1.3.0'
```

---

## `reprex`

Now we have our reproducible example:

```r
library(tidyverse)

mtcars %>%
  arrange(cyl) %>%
  ggplot(mapping = aes(x = factor(cyl))) +
  geom_bar()
```

How can we easily share it?

* Using the `reprex()` function in the `reprex` package.

---

## `reprex` Practice Time!

But first: **Q**: What is an R script file?

* A text file for entering R commands.

**Q**: How is an R script file different from an R Markdown document?

* You only put code in an R script.  
* If you add any text you must comment it out with `#`.
* Think of it as a single r chunk that you won't compile into an output document.
* Useful when writing a lot of code and want to compartmentalize.
* Will come back to when we write an R data package!

---

#### `reprex` Practice Time!

(1) Restart your R Session.

(2) Open a script file and include in the top line:

```r
library(reprex)
```

(3) Put the code you want to use in the script file and make sure it runs.

```r
library(tidyverse)

mtcars %>%
  arrange(cyl) %>%
  ggplot(mapping = aes(x = factor(cyl))) +
  geom_bar()
```

(4) Surround the code with `reprex({ ... })` and run it.

(5) To the question "Open the output file for manual copy?" select "1: yes". A window with the output file should pop up.

(6) Head over to Slack/GitHub and create a text/code snippet with the following:

+ Type: R
+ Content: Paste code and output (but not any figures).
+ Message: Paste any images and provide your question.

---

## Recap: Components of Data Graphics

* **data**: dataset that contains the raw data

* **geom**: geometric shape that the data are mapped to.
    + point, line, bar, text, ...
    
* **aes**thetic: visual properties of the **geom** 
    + x position, y position, color, fill, shape
    
* **coord**: coordinate system
    + Cartesian, polar
    
* **scale**: controls how data are mapped to the visual values of the aesthetic.
    + EX: particular colors, linear

* **guide**: legend to help user convert visual display back to the data

---

## ggplot2 example code

```r
ggplot(data = ---, mapping = aes(---)) +
  geom_---(---) + 
  coord_---() + 
  scale_---_---() +
  ---
```

---

##Recap Data: Births2015

```r
# Load libraries
library(mosaicData)
library(tidyverse)

# Grab data
data(Births2015)
```

---

## Recap Data: Births2015

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point()
```

* Let's think more about the scales.
* Want to add more context!

---

## Scales

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() +
  scale_x_date() +
  scale_y_continuous() +
  scale_color_discrete()
```

* Maybe we want to change the default settings.
* Maybe we want a different scale than the default.

---

## Scales

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() +
  scale_y_continuous(breaks = seq(6000, 14000, by = 500)) +
  scale_color_brewer(type = "qual", palette = 1)
```

---

##Context: Labels

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() + 
   labs(x = "Date", y = "Number of Births in US", 
        title = "Trend of Births in 2015", 
        subtitle = "Data: National Vital Statistics System", 
        color = "Week Days")
```

* Prefer citing the data at the bottom?

---

##Context: Labels

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() + 
   labs(x = "Date", y = "Number of Births in US", 
        title = "Trend of Births in 2015", 
        caption = "Data: National Vital Statistics System", 
        color = "Week Days")
```

* Now we want to add even more context: Identify holidays.

---

##Context: Labels

* For slide space, I neglect my labeling in the rest of the presentation.

---

##Context: Adding Holidays

```r
library(lubridate)
holidays <- 
  data.frame(date = ymd("2015-01-01","2015-05-25", "2015-07-04",
                        "2015-12-25", "2015-11-26", "2015-12-24",
                        "2015-09-07"), 
            occasion = c("New Year", "Memorial Day", 
                         "Independence Day", "Christmas",
                         "Thanksgiving", "Christmas Eve", 
                         "Labor Day"),
            image = c("https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.com/thumbs/240/apple/271/party-popper_1f389.png",
                      "https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.com/thumbs/240/apple/271/military-medal_1f396-fe0f.png",
                      "https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.com/thumbs/240/apple/271/sparkler_1f387.png",
                      "https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.com/thumbs/240/apple/271/christmas-tree_1f384.png",
                      "https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.com/thumbs/240/apple/271/turkey_1f983.png",
                      "https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.com/thumbs/240/apple/271/wrapped-gift_1f381.png",
                      "https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.com/thumbs/320/apple/271/construction-worker_1f477.png"
                      ),
            image2 = c("https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.com/thumbs/240/apple/271/party-popper_1f389.png",
                      "https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.com/thumbs/240/apple/271/military-medal_1f396-fe0f.png",
                      "https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.com/thumbs/240/apple/271/sparkler_1f387.png",
                      "https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.com/thumbs/240/apple/271/christmas-tree_1f384.png",
                      "https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.com/thumbs/240/apple/271/turkey_1f983.png",
                      "https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.com/thumbs/240/apple/271/wrapped-gift_1f381.png",
                      "~/math241s21/img/full_bernie.png"
                      ))

holidays <- left_join(holidays, Births2015)
```

---

##Context: Adding Holidays

```r
glimpse(holidays)
```

```
## Rows: 7
## Columns: 11
## $ date         <date> 2015-01-01, 2015-05-25, 2015-07-04, 2015-12-25, 2015-11…
## $ occasion     <chr> "New Year", "Memorial Day", "Independence Day", "Christm…
## $ image        <chr> "https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.…
## $ image2       <chr> "https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.…
## $ births       <dbl> 8068, 7746, 7944, 6515, 7332, 8714, 8127
## $ wday         <ord> Thu, Mon, Sat, Fri, Thu, Thu, Mon
## $ year         <dbl> 2015, 2015, 2015, 2015, 2015, 2015, 2015
## $ month        <dbl> 1, 5, 7, 12, 11, 12, 9
## $ day_of_year  <int> 1, 145, 185, 359, 330, 358, 250
## $ day_of_month <dbl> 1, 25, 4, 25, 26, 24, 7
## $ day_of_week  <dbl> 5, 2, 7, 6, 5, 5, 2
```

* Let's add some context.

---

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() + 
  geom_point(data = holidays, mapping = aes(x = date, y = births), 
             color = "black", size = 3)
```

---

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() + 
  geom_text(data = holidays, mapping = aes(label = occasion))
```

* Problems?

---

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() + 
  geom_text(data = holidays, mapping = aes(label = occasion), 
            show.legend = FALSE)
```

---

```r
library(ggrepel)
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() + 
  geom_text_repel(data = holidays, mapping = aes(label = occasion), 
                  show.legend = FALSE)
```

---

---

---

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday))  + 
   
  geom_point(size = 6, color = "black", data=holidays) + 
  geom_point(size = 5, color = "grey90", data=holidays) + 
  geom_point()  + 
  annotate("segment", colour = "black", x = as_date("2015-09-01"), 
           xend = holidays$date, y = 6800, yend = holidays$births, 
           size = 1, alpha = 0.2, arrow = arrow()) + 
  annotate("text", x = as_date("2015-09-01"), y = 6600, 
           label = "Holidays", color = "black", size = 5)
```

---

```r
# Create a story label
label_data <- data.frame(date = ymd("2015-01-01"), 
                         births = max(Births2015$births),
label = "The frequency of births on holidays \nfollows weekend \ntrends.")
```

---

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday))  + 
  geom_point() +
  geom_text(mapping = aes(label = label), data = label_data, 
            color = "black", vjust = "top", hjust = "left")
```

---

```r
library(ggimage)
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() + 
  geom_image(data = holidays, mapping = aes(image = image, 
                                            x = date, 
                                            y = births),
             inherit.aes = FALSE)  +
  geom_text(mapping = aes(label = label), data = label_data, 
            color = "black", vjust = "top", hjust = "left")
```

---

```r
library(ggimage)
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() + 
  geom_image(data = holidays, mapping = aes(image = image2, 
                                            x = date, 
                                            y = births),
             inherit.aes = FALSE, size = .05)  +
  geom_text(mapping = aes(label = label), data = label_data, 
            color = "black", vjust = "top", hjust = "left")
```

---

### Context

And there are lots more ways to annotate your graph (shaded regions, spike lines...).

A few notes:

* Don't over do it!
* Like with selecting a `geom` or a `mapping` or a `scale`, try several out first.

---

## BLS Consumer Expenditure Survey

* New dataset: Last quarter of the Bureau of Labor Statistics Consumer Expenditure Survey.

```r
ce <- read_csv("/home/courses/math241s21/Data/ce.csv")
glimpse(ce)
```

```
## Rows: 6,301
## Columns: 49
## $ FINLWT21 <dbl> 25985, 6581, 20208, 18078, 20112, 19907, 11705, 24431, 42859…
## $ FINCBTAX <dbl> 116920, 200, 117000, 0, 2000, 942, 0, 91000, 95000, 40037, 1…
## $ BLS_URBN <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …
## $ POPSIZE  <dbl> 2, 3, 4, 2, 2, 2, 1, 2, 5, 2, 3, 2, 2, 3, 4, 3, 3, 1, 4, 1, …
## $ EDUC_REF <chr> "16", "15", "16", "15", "14", "11", "10", "13", "12", "12", …
## $ EDUCA2   <chr> "15", "15", "13", NA, NA, NA, NA, "15", "15", "14", "12", "1…
## $ AGE_REF  <dbl> 63, 50, 47, 37, 51, 63, 77, 37, 51, 64, 26, 59, 81, 51, 67, …
## $ AGE2     <chr> "50", "47", "46", ".", ".", ".", ".", "36", "53", "67", "44"…
## $ SEX_REF  <dbl> 1, 1, 2, 1, 2, 1, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, …
## $ SEX2     <dbl> 2, 2, 1, NA, NA, NA, NA, 2, 2, 1, 1, 1, NA, NA, NA, 1, NA, 1…
## $ REF_RACE <dbl> 1, 4, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, …
## $ RACE2    <dbl> 1, 4, 1, NA, NA, NA, NA, 1, 1, 1, 1, 1, NA, NA, NA, 2, NA, 1…
## $ HISP_REF <dbl> 2, 2, 2, 2, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, …
## $ HISP2    <dbl> 2, 2, 1, NA, NA, NA, NA, 2, 2, 2, 2, 2, NA, NA, NA, 2, NA, 2…
## $ FAM_TYPE <dbl> 3, 4, 1, 8, 9, 9, 8, 3, 1, 1, 3, 1, 8, 9, 8, 5, 9, 4, 8, 3, …
## $ MARITAL1 <dbl> 1, 1, 1, 5, 3, 3, 2, 1, 1, 1, 1, 1, 2, 3, 5, 1, 3, 1, 3, 1, …
## $ REGION   <dbl> 4, 4, 3, 4, 4, 3, 4, 1, 3, 2, 1, 4, 1, 3, 3, 3, 2, 1, 2, 4, …
## $ SMSASTAT <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …
## $ HIGH_EDU <chr> "16", "15", "16", "15", "14", "11", "10", "15", "15", "14", …
## $ EHOUSNGC <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ TOTEXPCQ <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ FOODCQ   <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ TRANSCQ  <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ HEALTHCQ <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ ENTERTCQ <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ EDUCACQ  <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ TOBACCCQ <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ STUDFINX <chr> ".", ".", ".", ".", ".", ".", ".", ".", ".", ".", ".", ".", …
## $ IRAX     <chr> "1000000", "10000", "0", ".", ".", "0", "0", "15000", ".", "…
## $ CUTENURE <dbl> 1, 1, 1, 1, 1, 2, 4, 1, 1, 2, 1, 2, 2, 2, 2, 4, 1, 1, 1, 4, …
## $ FAM_SIZE <dbl> 4, 6, 2, 1, 2, 2, 1, 5, 2, 2, 4, 2, 1, 2, 1, 4, 2, 4, 1, 3, …
## $ VEHQ     <dbl> 3, 5, 0, 4, 2, 0, 0, 2, 4, 2, 3, 2, 1, 3, 1, 2, 4, 4, 0, 2, …
## $ ROOMSQ   <chr> "8", "5", "6", "4", "4", "4", "7", "5", "4", "9", "6", "10",…
## $ INC_HRS1 <chr> "40", "40", "40", "44", "40", ".", ".", "40", "40", ".", "40…
## $ INC_HRS2 <chr> "30", "40", "52", ".", ".", ".", ".", "40", "40", ".", "65",…
## $ EARNCOMP <dbl> 3, 2, 2, 1, 4, 7, 8, 2, 2, 8, 2, 8, 8, 7, 8, 2, 7, 3, 1, 2, …
## $ NO_EARNR <dbl> 4, 2, 2, 1, 2, 1, 0, 2, 2, 0, 2, 0, 0, 1, 0, 2, 1, 3, 1, 2, …
## $ OCCUCOD1 <chr> "03", "03", "05", "03", "04", NA, NA, "12", "04", NA, "01", …
## $ OCCUCOD2 <chr> "04", "02", "01", NA, NA, NA, NA, "02", "03", NA, "11", NA, …
## $ STATE    <chr> "41", "15", "48", "06", "06", "48", "06", "42", NA, "27", "2…
## $ DIVISION <dbl> 9, 9, 7, 9, 9, 7, 9, 2, NA, 4, 1, 8, 2, 5, 6, 7, 3, 2, 3, 9,…
## $ TOTXEST  <dbl> 15452, 11459, 15738, 25978, 588, 0, 0, 7261, 9406, -1414, 14…
## $ CREDFINX <chr> "0", ".", "0", ".", "5", ".", ".", ".", ".", "0", ".", "0", …
## $ CREDITB  <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ CREDITX  <chr> "4000", "5000", "2000", ".", "7000", "1800", ".", "6000", ".…
## $ BUILDING <chr> "01", "01", "01", "02", "08", "01", "01", "01", "01", "01", …
## $ ST_HOUS  <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, …
## $ INT_PHON <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ INT_HOME <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
```

---

## Issue with Plotting Bigger Datasets

```r
ggplot(data = ce, aes(x = FINCBTAX, y = TOTEXPCQ)) + 
  geom_point()
```

---

## Issue with Plotting Bigger Datasets

```r
ggplot(data = ce, aes(x = FINCBTAX, y = TOTEXPCQ)) + 
  geom_point(alpha = .2)
```

---

## Heatmaps

```r
ggplot(data = ce, aes(x = TOTEXPCQ, y = FINCBTAX)) + 
  geom_hex()
```

* Useful for seeing density for large datasets.

---

## Handling Transformations

```r
ggplot(data = ce, aes(x = log10(TOTEXPCQ), y = log10(FINCBTAX))) + 
  geom_hex() 
```

* Transform variables directly.

---

## Handling Transformations

```r
ggplot(data = ce, aes(x = TOTEXPCQ, y = FINCBTAX)) + 
  geom_hex() + 
  scale_x_log10() + 
  scale_y_log10()
```

* Transform scale.

---

## ColorBrewer

```r
RColorBrewer::display.brewer.all()
```

---

## Color Options: Saturation

```r
ggplot(data = ce, aes(x = log10(TOTEXPCQ), y = log10(FINCBTAX))) + 
  geom_hex() + 
  scale_fill_distiller(palette = "Purples")
```

---

## ColorBrewer YlGn palette

```r
ggplot(data = ce, aes(x = log10(TOTEXPCQ), y = log10(FINCBTAX))) + 
  geom_hex() + 
  scale_fill_distiller(palette = "YlGn")
```

---

## [Viridis Palette](https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html)

```r
library(viridis)
ggplot(data = ce, aes(x = log10(TOTEXPCQ), y = log10(FINCBTAX))) + 
  geom_hex() + 
  scale_fill_viridis(direction = -1, option = "A")
```

---

## [Viridis Palette](https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html)

```r
library(viridis)
ggplot(data = ce, aes(x = log10(TOTEXPCQ), y = log10(FINCBTAX))) + 
  geom_hex() + 
  scale_fill_viridis(direction = 1, option = "C")
```

---

## [Viridis Palette](https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html)

```r
library(viridis)
ggplot(data = ce, aes(x = log10(TOTEXPCQ), y = log10(FINCBTAX))) + 
  geom_hex() + 
  scale_fill_viridis(direction = 1, option = "D")
```

---

## Color Options: Hue

```r
colors()
```

```
##   [1] "white"                "aliceblue"            "antiquewhite"        
##   [4] "antiquewhite1"        "antiquewhite2"        "antiquewhite3"       
##   [7] "antiquewhite4"        "aquamarine"           "aquamarine1"         
##  [10] "aquamarine2"          "aquamarine3"          "aquamarine4"         
##  [13] "azure"                "azure1"               "azure2"              
##  [16] "azure3"               "azure4"               "beige"               
##  [19] "bisque"               "bisque1"              "bisque2"             
##  [22] "bisque3"              "bisque4"              "black"               
##  [25] "blanchedalmond"       "blue"                 "blue1"               
##  [28] "blue2"                "blue3"                "blue4"               
##  [31] "blueviolet"           "brown"                "brown1"              
##  [34] "brown2"               "brown3"               "brown4"              
##  [37] "burlywood"            "burlywood1"           "burlywood2"          
##  [40] "burlywood3"           "burlywood4"           "cadetblue"           
##  [43] "cadetblue1"           "cadetblue2"           "cadetblue3"          
##  [46] "cadetblue4"           "chartreuse"           "chartreuse1"         
##  [49] "chartreuse2"          "chartreuse3"          "chartreuse4"         
##  [52] "chocolate"            "chocolate1"           "chocolate2"          
##  [55] "chocolate3"           "chocolate4"           "coral"               
##  [58] "coral1"               "coral2"               "coral3"              
##  [61] "coral4"               "cornflowerblue"       "cornsilk"            
##  [64] "cornsilk1"            "cornsilk2"            "cornsilk3"           
##  [67] "cornsilk4"            "cyan"                 "cyan1"               
##  [70] "cyan2"                "cyan3"                "cyan4"               
##  [73] "darkblue"             "darkcyan"             "darkgoldenrod"       
##  [76] "darkgoldenrod1"       "darkgoldenrod2"       "darkgoldenrod3"      
##  [79] "darkgoldenrod4"       "darkgray"             "darkgreen"           
##  [82] "darkgrey"             "darkkhaki"            "darkmagenta"         
##  [85] "darkolivegreen"       "darkolivegreen1"      "darkolivegreen2"     
##  [88] "darkolivegreen3"      "darkolivegreen4"      "darkorange"          
##  [91] "darkorange1"          "darkorange2"          "darkorange3"         
##  [94] "darkorange4"          "darkorchid"           "darkorchid1"         
##  [97] "darkorchid2"          "darkorchid3"          "darkorchid4"         
## [100] "darkred"              "darksalmon"           "darkseagreen"        
## [103] "darkseagreen1"        "darkseagreen2"        "darkseagreen3"       
## [106] "darkseagreen4"        "darkslateblue"        "darkslategray"       
## [109] "darkslategray1"       "darkslategray2"       "darkslategray3"      
## [112] "darkslategray4"       "darkslategrey"        "darkturquoise"       
## [115] "darkviolet"           "deeppink"             "deeppink1"           
## [118] "deeppink2"            "deeppink3"            "deeppink4"           
## [121] "deepskyblue"          "deepskyblue1"         "deepskyblue2"        
## [124] "deepskyblue3"         "deepskyblue4"         "dimgray"             
## [127] "dimgrey"              "dodgerblue"           "dodgerblue1"         
## [130] "dodgerblue2"          "dodgerblue3"          "dodgerblue4"         
## [133] "firebrick"            "firebrick1"           "firebrick2"          
## [136] "firebrick3"           "firebrick4"           "floralwhite"         
## [139] "forestgreen"          "gainsboro"            "ghostwhite"          
## [142] "gold"                 "gold1"                "gold2"               
## [145] "gold3"                "gold4"                "goldenrod"           
## [148] "goldenrod1"           "goldenrod2"           "goldenrod3"          
## [151] "goldenrod4"           "gray"                 "gray0"               
## [154] "gray1"                "gray2"                "gray3"               
## [157] "gray4"                "gray5"                "gray6"               
## [160] "gray7"                "gray8"                "gray9"               
## [163] "gray10"               "gray11"               "gray12"              
## [166] "gray13"               "gray14"               "gray15"              
## [169] "gray16"               "gray17"               "gray18"              
## [172] "gray19"               "gray20"               "gray21"              
## [175] "gray22"               "gray23"               "gray24"              
## [178] "gray25"               "gray26"               "gray27"              
## [181] "gray28"               "gray29"               "gray30"              
## [184] "gray31"               "gray32"               "gray33"              
## [187] "gray34"               "gray35"               "gray36"              
## [190] "gray37"               "gray38"               "gray39"              
## [193] "gray40"               "gray41"               "gray42"              
## [196] "gray43"               "gray44"               "gray45"              
## [199] "gray46"               "gray47"               "gray48"              
## [202] "gray49"               "gray50"               "gray51"              
## [205] "gray52"               "gray53"               "gray54"              
## [208] "gray55"               "gray56"               "gray57"              
## [211] "gray58"               "gray59"               "gray60"              
## [214] "gray61"               "gray62"               "gray63"              
## [217] "gray64"               "gray65"               "gray66"              
## [220] "gray67"               "gray68"               "gray69"              
## [223] "gray70"               "gray71"               "gray72"              
## [226] "gray73"               "gray74"               "gray75"              
## [229] "gray76"               "gray77"               "gray78"              
## [232] "gray79"               "gray80"               "gray81"              
## [235] "gray82"               "gray83"               "gray84"              
## [238] "gray85"               "gray86"               "gray87"              
## [241] "gray88"               "gray89"               "gray90"              
## [244] "gray91"               "gray92"               "gray93"              
## [247] "gray94"               "gray95"               "gray96"              
## [250] "gray97"               "gray98"               "gray99"              
## [253] "gray100"              "green"                "green1"              
## [256] "green2"               "green3"               "green4"              
## [259] "greenyellow"          "grey"                 "grey0"               
## [262] "grey1"                "grey2"                "grey3"               
## [265] "grey4"                "grey5"                "grey6"               
## [268] "grey7"                "grey8"                "grey9"               
## [271] "grey10"               "grey11"               "grey12"              
## [274] "grey13"               "grey14"               "grey15"              
## [277] "grey16"               "grey17"               "grey18"              
## [280] "grey19"               "grey20"               "grey21"              
## [283] "grey22"               "grey23"               "grey24"              
## [286] "grey25"               "grey26"               "grey27"              
## [289] "grey28"               "grey29"               "grey30"              
## [292] "grey31"               "grey32"               "grey33"              
## [295] "grey34"               "grey35"               "grey36"              
## [298] "grey37"               "grey38"               "grey39"              
## [301] "grey40"               "grey41"               "grey42"              
## [304] "grey43"               "grey44"               "grey45"              
## [307] "grey46"               "grey47"               "grey48"              
## [310] "grey49"               "grey50"               "grey51"              
## [313] "grey52"               "grey53"               "grey54"              
## [316] "grey55"               "grey56"               "grey57"              
## [319] "grey58"               "grey59"               "grey60"              
## [322] "grey61"               "grey62"               "grey63"              
## [325] "grey64"               "grey65"               "grey66"              
## [328] "grey67"               "grey68"               "grey69"              
## [331] "grey70"               "grey71"               "grey72"              
## [334] "grey73"               "grey74"               "grey75"              
## [337] "grey76"               "grey77"               "grey78"              
## [340] "grey79"               "grey80"               "grey81"              
## [343] "grey82"               "grey83"               "grey84"              
## [346] "grey85"               "grey86"               "grey87"              
## [349] "grey88"               "grey89"               "grey90"              
## [352] "grey91"               "grey92"               "grey93"              
## [355] "grey94"               "grey95"               "grey96"              
## [358] "grey97"               "grey98"               "grey99"              
## [361] "grey100"              "honeydew"             "honeydew1"           
## [364] "honeydew2"            "honeydew3"            "honeydew4"           
## [367] "hotpink"              "hotpink1"             "hotpink2"            
## [370] "hotpink3"             "hotpink4"             "indianred"           
## [373] "indianred1"           "indianred2"           "indianred3"          
## [376] "indianred4"           "ivory"                "ivory1"              
## [379] "ivory2"               "ivory3"               "ivory4"              
## [382] "khaki"                "khaki1"               "khaki2"              
## [385] "khaki3"               "khaki4"               "lavender"            
## [388] "lavenderblush"        "lavenderblush1"       "lavenderblush2"      
## [391] "lavenderblush3"       "lavenderblush4"       "lawngreen"           
## [394] "lemonchiffon"         "lemonchiffon1"        "lemonchiffon2"       
## [397] "lemonchiffon3"        "lemonchiffon4"        "lightblue"           
## [400] "lightblue1"           "lightblue2"           "lightblue3"          
## [403] "lightblue4"           "lightcoral"           "lightcyan"           
## [406] "lightcyan1"           "lightcyan2"           "lightcyan3"          
## [409] "lightcyan4"           "lightgoldenrod"       "lightgoldenrod1"     
## [412] "lightgoldenrod2"      "lightgoldenrod3"      "lightgoldenrod4"     
## [415] "lightgoldenrodyellow" "lightgray"            "lightgreen"          
## [418] "lightgrey"            "lightpink"            "lightpink1"          
## [421] "lightpink2"           "lightpink3"           "lightpink4"          
## [424] "lightsalmon"          "lightsalmon1"         "lightsalmon2"        
## [427] "lightsalmon3"         "lightsalmon4"         "lightseagreen"       
## [430] "lightskyblue"         "lightskyblue1"        "lightskyblue2"       
## [433] "lightskyblue3"        "lightskyblue4"        "lightslateblue"      
## [436] "lightslategray"       "lightslategrey"       "lightsteelblue"      
## [439] "lightsteelblue1"      "lightsteelblue2"      "lightsteelblue3"     
## [442] "lightsteelblue4"      "lightyellow"          "lightyellow1"        
## [445] "lightyellow2"         "lightyellow3"         "lightyellow4"        
## [448] "limegreen"            "linen"                "magenta"             
## [451] "magenta1"             "magenta2"             "magenta3"            
## [454] "magenta4"             "maroon"               "maroon1"             
## [457] "maroon2"              "maroon3"              "maroon4"             
## [460] "mediumaquamarine"     "mediumblue"           "mediumorchid"        
## [463] "mediumorchid1"        "mediumorchid2"        "mediumorchid3"       
## [466] "mediumorchid4"        "mediumpurple"         "mediumpurple1"       
## [469] "mediumpurple2"        "mediumpurple3"        "mediumpurple4"       
## [472] "mediumseagreen"       "mediumslateblue"      "mediumspringgreen"   
## [475] "mediumturquoise"      "mediumvioletred"      "midnightblue"        
## [478] "mintcream"            "mistyrose"            "mistyrose1"          
## [481] "mistyrose2"           "mistyrose3"           "mistyrose4"          
## [484] "moccasin"             "navajowhite"          "navajowhite1"        
## [487] "navajowhite2"         "navajowhite3"         "navajowhite4"        
## [490] "navy"                 "navyblue"             "oldlace"             
## [493] "olivedrab"            "olivedrab1"           "olivedrab2"          
## [496] "olivedrab3"           "olivedrab4"           "orange"              
## [499] "orange1"              "orange2"              "orange3"             
## [502] "orange4"              "orangered"            "orangered1"          
## [505] "orangered2"           "orangered3"           "orangered4"          
## [508] "orchid"               "orchid1"              "orchid2"             
## [511] "orchid3"              "orchid4"              "palegoldenrod"       
## [514] "palegreen"            "palegreen1"           "palegreen2"          
## [517] "palegreen3"           "palegreen4"           "paleturquoise"       
## [520] "paleturquoise1"       "paleturquoise2"       "paleturquoise3"      
## [523] "paleturquoise4"       "palevioletred"        "palevioletred1"      
## [526] "palevioletred2"       "palevioletred3"       "palevioletred4"      
## [529] "papayawhip"           "peachpuff"            "peachpuff1"          
## [532] "peachpuff2"           "peachpuff3"           "peachpuff4"          
## [535] "peru"                 "pink"                 "pink1"               
## [538] "pink2"                "pink3"                "pink4"               
## [541] "plum"                 "plum1"                "plum2"               
## [544] "plum3"                "plum4"                "powderblue"          
## [547] "purple"               "purple1"              "purple2"             
## [550] "purple3"              "purple4"              "red"                 
## [553] "red1"                 "red2"                 "red3"                
## [556] "red4"                 "rosybrown"            "rosybrown1"          
## [559] "rosybrown2"           "rosybrown3"           "rosybrown4"          
## [562] "royalblue"            "royalblue1"           "royalblue2"          
## [565] "royalblue3"           "royalblue4"           "saddlebrown"         
## [568] "salmon"               "salmon1"              "salmon2"             
## [571] "salmon3"              "salmon4"              "sandybrown"          
## [574] "seagreen"             "seagreen1"            "seagreen2"           
## [577] "seagreen3"            "seagreen4"            "seashell"            
## [580] "seashell1"            "seashell2"            "seashell3"           
## [583] "seashell4"            "sienna"               "sienna1"             
## [586] "sienna2"              "sienna3"              "sienna4"             
## [589] "skyblue"              "skyblue1"             "skyblue2"            
## [592] "skyblue3"             "skyblue4"             "slateblue"           
## [595] "slateblue1"           "slateblue2"           "slateblue3"          
## [598] "slateblue4"           "slategray"            "slategray1"          
## [601] "slategray2"           "slategray3"           "slategray4"          
## [604] "slategrey"            "snow"                 "snow1"               
## [607] "snow2"                "snow3"                "snow4"               
## [610] "springgreen"          "springgreen1"         "springgreen2"        
## [613] "springgreen3"         "springgreen4"         "steelblue"           
## [616] "steelblue1"           "steelblue2"           "steelblue3"          
## [619] "steelblue4"           "tan"                  "tan1"                
## [622] "tan2"                 "tan3"                 "tan4"                
## [625] "thistle"              "thistle1"             "thistle2"            
## [628] "thistle3"             "thistle4"             "tomato"              
## [631] "tomato1"              "tomato2"              "tomato3"             
## [634] "tomato4"              "turquoise"            "turquoise1"          
## [637] "turquoise2"           "turquoise3"           "turquoise4"          
## [640] "violet"               "violetred"            "violetred1"          
## [643] "violetred2"           "violetred3"           "violetred4"          
## [646] "wheat"                "wheat1"               "wheat2"              
## [649] "wheat3"               "wheat4"               "whitesmoke"          
## [652] "yellow"               "yellow1"              "yellow2"             
## [655] "yellow3"              "yellow4"              "yellowgreen"
```

---

## Color Options: Hue

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() + 
  scale_color_manual(name = "Day of the Week", 
                     values=sample(colors(), 7))
```

---

## Color Options: [Hue](http://www.colourlovers.com/palette/694737/Thought_Provoking)

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() + 
  scale_color_manual(name = "Day of the Week", 
                     values=c("#ECD078", "#D95B43", "#C02942",
                              "#542437", "#53777A", "#8A9B0F",
                              "#6A4A3C"))
```

---

## ColorBrewer Hue

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() + 
  scale_color_brewer(name = "Day of the Week", palette = "Dark2")
```

---

## [Themes](https://r-graphics.org/recipe-appearance-theme-modify)

```r
#?theme
```

* Can override specific aspects of the theme
    + EX: `+ theme(legend.position = "bottom")`

---

## Themes

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() +
  theme(axis.title.x = element_text(color = "#C1D82F", size = 20), 
        axis.title.y = element_text(color = "#00857D", size = 25),
        axis.text.x = element_text(color = "#C1D82F", size = 12),
        axis.text.y = element_text(color = "#FF7401", size = 18)) 
```

---

### [Built-in Themes](https://ggplot2.tidyverse.org/reference/ggtheme.html)

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point()  + 
  theme_bw()
```

---

### Built-in Themes

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() + 
  theme_dark()
```

---

### Built-in Themes

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() + 
  theme_void()
```

---

### Additional Themes Package: [ggthemes](https://cran.r-project.org/web/packages/ggthemes/vignettes/ggthemes.html)

```r
library(ggthemes)
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() + 
  theme_economist()
```

---

### Additional Themes Package

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() +  
  theme_fivethirtyeight() 
```

---

### Additional Themes Package

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point() + 
  theme_wsj()
```

---

### Controlling the size of your figures

R Chunk options:

* `fig.asp`
* `fig.width`
* `fig.height`

```r
ggplot(data = Births2015, mapping = aes(x = date, y = births, 
                                        color = wday)) + 
  geom_point()
```

---

## To Do Now

* Practice assessing and downloading the class lab assignments.
    + Shared folder: `/home/courses/math241s21`