background-image: url("img/logo_padded.001.jpeg") background-position: left background-size: 60% class: middle, center, .pull-right[ <br> ## .base_color[Customizing] ## .base_color[`ggplot2`] <br> <br> ### .navy[Kelly McConville] #### .navy[ Stat 108 | Week 2 | Spring 2023] ] --- ## Announcements * [Office Hours Schedule](https://docs.google.com/spreadsheets/d/1HqEmr4tEtFPWRrF5TJHd1VgtVD030w6aAYySoFTnhBw/edit?usp=share_link) + Some office hours will start in Week 3 so make sure to check the schedule. * [Section Schedule](https://docs.google.com/spreadsheets/d/1DkR88j_jIkn9ZrA30FA8u3EAusAUaDN5TGhtuUVEyYA/edit?usp=share_link) * Fill out [this short form](https://forms.gle/H67c4XftzcD9e1vr7) so that we can add you to the Stat 108 GitHub organization and so we know how many paper copies of the slides to bring to lecture. * Week 2 Lecture Quiz released at 10:30am on Wednesday. + Due at noon on Friday. * P-Set 1 released at 9am on Thursday. + Will discuss how to access the p-sets today! + Due at 5pm the following Wednesday --- ## Week 2 Goals .pull-left[ **Mon Lecture** * Basics of `ggplot2` * Explore several `geoms`. * And a little data wrangling with `dplyr` as needed! ] .pull-right[ **Wed Lecture** * Context! + Labels + Highlighting + Useful text * Look at more `geom`s. * Explore further customizations. + Color + Themes * Learn how to ask coding questions well. ] --- ## 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. <img src="img/rmarkdown.png" width="20%" style="display: block; margin: auto;" /> --- <img src="img/reprex.png" width="15%" style="float:left; padding:10px" style="display: block; margin: auto;" /> ## Creating `repr`oducible `ex`amples with `reprex` <br> <br> <br> #### Why do I need to learn to create reproducible technical examples? -- So that you can ask and answer questions in our class Slack Workspace or Stack Overflow or other `R` help sites! --- ## What is wrong with this coding 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 = factor(that))) + geom_bar() 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) library(palmerpenguins) penguins <- penguins %>% group_by(species) %>% mutate(mean_flipper = mean(flipper_length_mm)) %>% ungroup() %>% mutate(long = case_when(flipper_length_mm < mean(flipper_length_mm) ~ "no", flipper_length_mm >= mean(flipper_length_mm) ~ "yes")) penguins %>% ggplot(mapping = aes(x = factor(species))) + geom_bar() penguins %>% count(species) ``` ``` ## # A tibble: 3 × 2 ## species n ## <fct> <int> ## 1 Adelie 152 ## 2 Chinstrap 68 ## 3 Gentoo 124 ``` <img src="stat108_wk02wed_files/figure-html/unnamed-chunk-3-1.png" width="576" style="display: block; margin: auto;" /> --- ## 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) library(palmerpenguins) penguins %>% ggplot(mapping = aes(x = factor(species))) + 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 doesn't wreak havoc on other people's computers. * It includes code **and output** so that others don't have to run it! * It includes any necessary information on the used packages, R version, system, etc. + Should not be a concern for our class Slack since we are all on the same RStudio Server. + Can use `packageVersion("tidyverse")` or `sessionInfo()` to find this information. --- ## 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(palmerpenguins) penguins ``` ``` ## # A tibble: 344 × 10 ## species island bill_le…¹ bill_…² flipp…³ body_…⁴ sex year mean_…⁵ long ## <fct> <fct> <dbl> <dbl> <int> <int> <fct> <int> <dbl> <chr> ## 1 Adelie Torgersen 39.1 18.7 181 3750 male 2007 NA <NA> ## 2 Adelie Torgersen 39.5 17.4 186 3800 fema… 2007 NA <NA> ## 3 Adelie Torgersen 40.3 18 195 3250 fema… 2007 NA <NA> ## 4 Adelie Torgersen NA NA NA NA <NA> 2007 NA <NA> ## 5 Adelie Torgersen 36.7 19.3 193 3450 fema… 2007 NA <NA> ## 6 Adelie Torgersen 39.3 20.6 190 3650 male 2007 NA <NA> ## 7 Adelie Torgersen 38.9 17.8 181 3625 fema… 2007 NA <NA> ## 8 Adelie Torgersen 39.2 19.6 195 4675 male 2007 NA <NA> ## 9 Adelie Torgersen 34.1 18.1 193 3475 <NA> 2007 NA <NA> ## 10 Adelie Torgersen 42 20.2 190 4250 <NA> 2007 NA <NA> ## # … with 334 more rows, and abbreviated variable names ¹​bill_length_mm, ## # ²​bill_depth_mm, ³​flipper_length_mm, ⁴​body_mass_g, ⁵​mean_flipper ``` --- ## Minimal Code Include the **necessary** libraries. Test run the code in a restarted R session to make sure it is runnable! ```r library(tidyverse) library(palmerpenguins) penguins %>% ggplot(mapping = aes(x = factor(species))) + geom_bar() ``` <img src="stat108_wk02wed_files/figure-html/unnamed-chunk-7-1.png" width="360" style="display: block; margin: auto;" /> --- ## Make sure your code is copy-and-paste-able! Don't copy from the console. ```r > library(tidyverse) > library(palmerpenguins) > > penguins %>% + ggplot(mapping = aes(x = factor(species))) + + geom_bar() ``` --- ## Make sure your code is copy-and-paste-able!  --- Now we have our reproducible example: How can I reorder the bars in the ggplot to go from the most frequent to the least frequent category? ```r library(tidyverse) library(palmerpenguins) penguins %>% ggplot(mapping = aes(x = factor(species))) + geom_bar() ``` <img src="stat108_wk02wed_files/figure-html/unnamed-chunk-9-1.png" width="288" style="display: block; margin: auto;" /> -- **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 knit into an output document. * Useful when writing a lot of code and want to compartmentalize. --- #### `reprex` Practice Time! (1) In **Session**, select "Clear Workspace" and then "Restart R". (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) library(palmerpenguins) penguins %>% ggplot(mapping = aes(x = factor(species))) + geom_bar() ``` (4) Surround the code with `reprex({ ... }, venue = "slack")` and run it. (5) An md file will pop up. Copy all the contents of that file. (6) Head over to the #q-and-a and paste in the contents as a reply to the `reprex` practice message. A text box will pop-up and select "Apply". (7) Above your code, type your question. Then hit "Send". --- ## Recap Data: Births2015 ```r # Load libraries library(mosaicData) library(tidyverse) # Grab data data(Births2015) # Inspect data glimpse(Births2015) ``` ``` ## Rows: 365 ## Columns: 8 ## $ date <date> 2015-01-01, 2015-01-02, 2015-01-03, 2015-01-04, 2015-01-… ## $ births <dbl> 8068, 10850, 8328, 7065, 11892, 12425, 12141, 12094, 1186… ## $ wday <ord> Thu, Fri, Sat, Sun, Mon, Tue, Wed, Thu, Fri, Sat, Sun, Mo… ## $ year <dbl> 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 201… ## $ month <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, … ## $ day_of_year <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17… ## $ day_of_month <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17… ## $ day_of_week <dbl> 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 1, 2, … ``` --- ## Recap Data: Births2015 .pull-left[ ```r ggplot(data = Births2015, mapping = aes(x = date, y = births, color = wday)) + geom_point() ``` * Let's think more about the **scales**. * Let's add more **context**! ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss1-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Scales .pull-left[ ```r ggplot(data = Births2015, mapping = aes(x = date, y = births, color = wday)) + geom_point() + scale_x_date(date_labels = "%b", date_breaks = "1 month") + scale_y_continuous(breaks = seq(6000, 14000, by = 500)) + scale_color_brewer(type = "qual", palette = 1) ``` * Maybe we want to change the default settings of a scale. * Maybe we want a different scale than the default. ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss2-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Context: Labels .pull-left[ ```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? ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss3-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Context: Labels .pull-left[ ```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") ``` * Prefer citing the data at the bottom? ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss4-1.png" width="768" style="display: block; margin: auto;" /> ] * For slide space, I will neglect my labeling in the rest of the presentation. * Now we want to add even more context to help the reader understand whether or not birth rates on national holidays behave like weekends. --- ##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"), emoji = c("1f389", "1f396", "1f386", "1f384", "1f983", "1f381", "1f477")) holidays <- left_join(holidays, Births2015) ``` --- ## Context: Adding Holidays ```r glimpse(holidays) ``` ``` ## Rows: 7 ## Columns: 10 ## $ date <date> 2015-01-01, 2015-05-25, 2015-07-04, 2015-12-25, 2015-11-… ## $ occasion <chr> "New Year", "Memorial Day", "Independence Day", "Christma… ## $ emoji <chr> "1f389", "1f396", "1f386", "1f384", "1f983", "1f381", "1f… ## $ 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. --- ## Context: Adding Holidays .pull-left[ ```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) ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss5-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Context: Adding Holidays .pull-left[ ```r ggplot(data = Births2015, mapping = aes(x = date, y = births, color = wday)) + geom_point() + geom_text(data = holidays, mapping = aes(label = occasion)) ``` * Problems? ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss6-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Context: Adding Holidays .pull-left[ ```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) ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss7-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Context: Adding Holidays .pull-left[ ```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) ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss8-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Context: Adding Holidays .pull-left[ ```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() ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss9-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Context: Adding Holidays .pull-left[ ```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("text", x = as_date("2015-09-01"), y = 7500, label = "Holidays", color="black", size=5) ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss10-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Context: Adding Holidays .pull-left[ ```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 = 7500, label = "Holidays", color="black", size=5) ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss11-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Context: Adding Holidays ```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.") ``` --- ## Context: Adding Holidays .pull-left[ ```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") ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss12-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Context: Adding Holidays .pull-left[ ```r library(ggimage) 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") + geom_emoji(data = holidays, mapping = aes(image = emoji, x = date, y = births)) ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss13-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Context: Adding Holidays .pull-left[ ```r library(ggimage) 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") + geom_emoji(data = holidays, mapping = aes(image = emoji, x = date, y = births), inherit.aes = FALSE) ``` * What does `inherit.aes` do? ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss14-1.png" width="768" style="display: block; margin: auto;" /> ] --- ### Context .pull-left[ 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. ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/unnamed-chunk-30-1.png" width="576" style="display: block; margin: auto;" /> ] --- ## Handling Over-plotting * Let's return to the US Forest Inventory and Analysis Program Idaho data .pull-left[ ```r dat <- readRDS(url("https://mcconvil.github.io/fia_workshop_2021/data/IDdata.rds","rb")) idaho_plots <- dat$pltassgn ggplot(data = idaho_plots, mapping = aes(x = elev, y = BA_TPA_ADJ)) + geom_point() ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/fia1-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Handling Over-plotting .pull-left[ ```r ggplot(data = idaho_plots, mapping = aes(x = elev, y = BA_TPA_ADJ)) + geom_jitter() ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/fia2-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Handling Over-plotting .pull-left[ ```r ggplot(data = idaho_plots, mapping = aes(x = elev, y = BA_TPA_ADJ)) + geom_point(alpha = 0.2) ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/fia3-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Handling Over-plotting .pull-left[ ```r ggplot(data = idaho_plots, mapping = aes(x = elev, y = BA_TPA_ADJ)) + geom_bin2d() ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/fia4-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Handling Transformations .pull-left[ ```r ggplot(data = idaho_plots, mapping = aes(x = elev, y = COUNT_TPA_ADJ)) + geom_bin2d() ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/fia5-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Handling Transformations .pull-left[ ```r ggplot(data = idaho_plots, mapping = aes(x = elev, y = log10(COUNT_TPA_ADJ))) + geom_bin2d() ``` * Transform variables directly. ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/fia6-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Handling Transformations .pull-left[ ```r ggplot(data = idaho_plots, mapping = aes(x = elev, y = COUNT_TPA_ADJ)) + geom_bin2d() + scale_y_log10() ``` * Transform scale. ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/fia7-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## ColorBrewer ```r RColorBrewer::display.brewer.all() ``` <img src="stat108_wk02wed_files/figure-html/unnamed-chunk-38-1.png" width="576" style="display: block; margin: auto;" /> --- ## Color Options: Saturation .pull-left[ ```r ggplot(data = idaho_plots, mapping = aes(x = elev, y = log10(COUNT_TPA_ADJ))) + geom_bin2d() + scale_fill_distiller(palette = "Purples") ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/fia8-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## ColorBrewer YlGn palette .pull-left[ ```r ggplot(data = idaho_plots, mapping = aes(x = elev, y = log10(COUNT_TPA_ADJ))) + geom_bin2d() + scale_fill_distiller(palette = "YlGn", direction = 1) ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/fia9-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## [Viridis Palette](https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html) .pull-left[ ```r library(viridis) ggplot(data = idaho_plots, mapping = aes(x = elev, y = log10(COUNT_TPA_ADJ))) + geom_bin2d() + scale_fill_viridis_c(direction = -1, option = "A") ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/fia10-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## [Viridis Palette](https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html) .pull-left[ ```r library(viridis) ggplot(data = idaho_plots, mapping = aes(x = elev, y = log10(COUNT_TPA_ADJ))) + geom_bin2d() + scale_fill_viridis_c(direction = -1, option = "C") ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/fia11-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## [Viridis Palette](https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html) .pull-left[ ```r library(viridis) ggplot(data = idaho_plots, mapping = aes(x = elev, y = log10(COUNT_TPA_ADJ))) + geom_bin2d() + scale_fill_viridis_c(direction = -1, option = "D") ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/fia12-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## 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 .pull-left[ ```r ggplot(data = Births2015, mapping = aes(x = date, y = births, color = wday)) + geom_point() + scale_color_manual(values = sample(colors(), 7)) ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss15-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## Color Options: [Hue](http://www.colourlovers.com/palette/694737/Thought_Provoking) .pull-left[ ```r ggplot(data = Births2015, mapping = aes(x = date, y = births, color = wday)) + geom_point() + scale_color_manual(values= c("#ECD078", "#D95B43", "#C02942", "#8A9B0F", "#542437", "#53777A", "#6A4A3C")) ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss16-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## ColorBrewer Hue .pull-left[ ```r ggplot(data = Births2015, mapping = aes(x = date, y = births, color = wday)) + geom_point() + scale_color_brewer(palette = "Dark2") ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss17-1.png" width="768" style="display: block; margin: auto;" /> ] --- ## [Themes](https://r-graphics.org/recipe-appearance-theme-modify) ```r #?theme ``` * Can override specific aspects of the theme + EX: `+ theme(legend.position = "bottom")` * Can globally set theme options: ```r theme_update(text = element_text(size = 20)) ``` --- ## Themes .pull-left[ ```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)) ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss18-1.png" width="768" style="display: block; margin: auto;" /> ] --- ### [Built-in Themes](https://ggplot2.tidyverse.org/reference/ggtheme.html) .pull-left[ ```r ggplot(data = Births2015, mapping = aes(x = date, y = births, color = wday)) + geom_point() + theme_bw() ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss19-1.png" width="768" style="display: block; margin: auto;" /> ] --- ### Built-in Themes .pull-left[ ```r ggplot(data = Births2015, mapping = aes(x = date, y = births, color = wday)) + geom_point() + theme_dark() ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss20-1.png" width="768" style="display: block; margin: auto;" /> ] --- ### Built-in Themes .pull-left[ ```r ggplot(data = Births2015, mapping = aes(x = date, y = births, color = wday)) + geom_point() + theme_void() ``` * Useful for maps and pie charts! ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss21-1.png" width="768" style="display: block; margin: auto;" /> ] --- ### Additional Themes Package: [ggthemes](https://cran.r-project.org/web/packages/ggthemes/vignettes/ggthemes.html) .pull-left[ ```r library(ggthemes) ggplot(data = Births2015, mapping = aes(x = date, y = births, color = wday)) + geom_point() + theme_economist() ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss22-1.png" width="768" style="display: block; margin: auto;" /> ] --- ### Additional Themes Package .pull-left[ ```r ggplot(data = Births2015, mapping = aes(x = date, y = births, color = wday)) + geom_point() + theme_wsj() ``` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss23-1.png" width="768" style="display: block; margin: auto;" /> ] --- ### Controlling the size of your figures .pull-left[ ```r ggplot(data = Births2015, mapping = aes(x = date, y = births, color = wday)) + geom_point() ``` R Chunk options: Adjust 2 of these * `fig.asp` * `fig.width` * `fig.height` ] .pull-right[ <img src="stat108_wk02wed_files/figure-html/birthss24-1.png" width="768" style="display: block; margin: auto;" /> ] --- class: middle, center ## To Do Now ### Practice accessing and saving the course p-sets on the Stat 108 RStudio Server! --- ### Reminders * [Office Hours Schedule](https://docs.google.com/spreadsheets/d/1HqEmr4tEtFPWRrF5TJHd1VgtVD030w6aAYySoFTnhBw/edit?usp=share_link) + Some office hours will start in Week 3 so make sure to check the schedule. * [Section Schedule](https://docs.google.com/spreadsheets/d/1DkR88j_jIkn9ZrA30FA8u3EAusAUaDN5TGhtuUVEyYA/edit?usp=share_link) * Fill out [this short form](https://forms.gle/H67c4XftzcD9e1vr7) so that we can add you to the Stat 108 GitHub organization and so we know how many paper copies of the slides to bring to lecture. * Week 2 Lecture Quiz released at 10:30am on Wednesday. + Due at noon on Friday. * P-Set 1 released at 9am on Thursday. + Will discuss how to access the p-sets today! + Due at 5pm the following Wednesday