class: center, middle, inverse, title-slide .title[ # Data and visualization <br> 💹 ] .author[ ### S. Mason Garrison ] --- layout: true <div class="my-footer"> <span> <a href="https://DataScience4Psych.github.io/DataScience4Psych/" target="_blank">Data Science for Psychologists</a> </span> </div> --- ``` ## learnr (NA -> a644d2dd4...) [GitHub] ``` ``` ## ## ── R CMD build ────────────────────────────────────────────────── ## checking for file 'C:\Users\smaso\AppData\Local\Temp\RtmpwPhRPP\remotes7783d867964\rstudio-learnr-a644d2d/DESCRIPTION' ... ✔ checking for file 'C:\Users\smaso\AppData\Local\Temp\RtmpwPhRPP\remotes7783d867964\rstudio-learnr-a644d2d/DESCRIPTION' ## ─ preparing 'learnr': (6.8s) ## checking DESCRIPTION meta-information ... checking DESCRIPTION meta-information ... ✔ checking DESCRIPTION meta-information ## ─ checking for LF line-endings in source and make files and shell scripts (357ms) ## ─ checking for empty or unneeded directories ## ─ building 'learnr_0.11.5.9000.tar.gz' (363ms) ## ## ``` ``` ## ── R CMD build ────────────────────────────────────────────────── ## checking for file 'C:\Users\smaso\AppData\Local\Temp\RtmpwPhRPP\remotes7786f101001\rstudio-gradethis-502af70/DESCRIPTION' ... ✔ checking for file 'C:\Users\smaso\AppData\Local\Temp\RtmpwPhRPP\remotes7786f101001\rstudio-gradethis-502af70/DESCRIPTION' ## ─ preparing 'gradethis': (3.1s) ## checking DESCRIPTION meta-information ... checking DESCRIPTION meta-information ... ✔ checking DESCRIPTION meta-information ## ─ installing the package to process help pages ## ─ saving partial Rd database (7.4s) ## ─ checking for LF line-endings in source and make files and shell scripts ## ─ checking for empty or unneeded directories ## Removed empty directory 'gradethis/archive' ## Omitted 'LazyData' from DESCRIPTION ## ─ building 'gradethis_0.2.14.tar.gz' (587ms) ## ## ``` class: middle # Exploring Our Data: What is in a dataset? --- .pull-left[ > "We will be exploring numbers. We need to handle them easily and look at them effectively. Techniques for handling and looking — whether graphical, arithmetic, or intermediate — will be important." > John Tukey ] .pull-right[ <img src="img/orangebook.png" width="77%" style="display: block; margin: auto;" /> ] --- ## Dataset terminology - Each row is an **observation** - Each column is a **variable** .center[.midi[ ``` r starwars ``` ``` ## # A tibble: 87 × 14 ## name height mass hair_color skin_color eye_color birth_year ## <chr> <int> <dbl> <chr> <chr> <chr> <dbl> ## 1 Luke S… 172 77 blond fair blue 19 ## 2 C-3PO 167 75 <NA> gold yellow 112 ## 3 R2-D2 96 32 <NA> white, bl… red 33 ## 4 Darth … 202 136 none white yellow 41.9 ## 5 Leia O… 150 49 brown light brown 19 ## 6 Owen L… 178 120 brown, gr… light blue 52 ## # ℹ 81 more rows ## # ℹ 7 more variables: sex <chr>, gender <chr>, homeworld <chr>, ## # species <chr>, films <list>, vehicles <list>, ## # starships <list> ``` ] ] --- ## Luke Skywalker  --- ## What's in the Star Wars data? Take a `glimpse` at the data: .medi[ ``` r glimpse(starwars) ``` ``` ## Rows: 87 ## Columns: 14 ## $ name <chr> "Luke Skywalker", "C-3PO", "R2-D2", "Darth V… ## $ height <int> 172, 167, 96, 202, 150, 178, 165, 97, 183, 1… ## $ mass <dbl> 77.0, 75.0, 32.0, 136.0, 49.0, 120.0, 75.0, … ## $ hair_color <chr> "blond", NA, NA, "none", "brown", "brown, gr… ## $ skin_color <chr> "fair", "gold", "white, blue", "white", "lig… ## $ eye_color <chr> "blue", "yellow", "red", "yellow", "brown", … ## $ birth_year <dbl> 19.0, 112.0, 33.0, 41.9, 19.0, 52.0, 47.0, N… ## $ sex <chr> "male", "none", "none", "male", "female", "m… ## $ gender <chr> "masculine", "masculine", "masculine", "masc… ## $ homeworld <chr> "Tatooine", "Tatooine", "Naboo", "Tatooine",… ## $ species <chr> "Human", "Droid", "Droid", "Human", "Human",… ## $ films <list> <"A New Hope", "The Empire Strikes Back", "… ## $ vehicles <list> <"Snowspeeder", "Imperial Speeder Bike">, <… ## $ starships <list> <"X-wing", "Imperial shuttle">, <>, <>, "TI… ``` ] --- .question[ How many rows and columns does this dataset have? What does each row represent? What does each column represent? ] ``` r ?starwars ``` <img src="img/starwars-help.png" width="60%" style="display: block; margin: auto;" /> --- .question[ How many rows and columns does this dataset have? ] .pull-left[ ``` r nrow(starwars) # number of rows ``` ``` ## [1] 87 ``` ``` r ncol(starwars) # number of columns ``` ``` ## [1] 14 ``` ``` r dim(starwars) # dimensions (row column) ``` ``` ## [1] 87 14 ``` ] --- ## Mass vs. height .question[ How would you describe the relationship between mass and height of Starwars characters? What other variables would help us understand data points that don't follow the overall trend? Who is the not so tall but really chubby character? ] <img src="d03_dataviz_files/figure-html/unnamed-chunk-8-1.png" width="50%" style="display: block; margin: auto;" /> --- ## Jabba! <img src="img/jabbaplot.png" width="80%" style="display: block; margin: auto;" /> --- ## Mass vs. height ``` r ggplot(data = starwars, mapping = aes(x = height, y = mass)) + geom_point() + labs(title = "Mass vs. height of Starwars characters", x = "Height (cm)", y = "Weight (kg)") ``` ``` ## Warning: Removed 28 rows containing missing values or values outside the ## scale range (`geom_point()`). ``` <img src="d03_dataviz_files/figure-html/mass-height-1.png" width="50%" style="display: block; margin: auto;" /> --- .question[ - What are the functions doing the plotting? - What is the dataset being plotted? - Which variables map to which features (aesthetics) of the plot? - What does the warning mean?<sup>+</sup> ] ``` r ggplot(data = starwars, mapping = aes(x = height, y = mass)) + geom_point() + labs(title = "Mass vs. height of Starwars characters", x = "Height (cm)", y = "Weight (kg)") ``` ``` ## Warning: Removed 28 rows containing missing values or values outside the ## scale range (`geom_point()`). ``` .footnote[ <sup>+</sup>Suppressing warning to subsequent slides to save space ] --- ## Hello ggplot2! .pull-left-narrow[ <img src="img/ggplot2-part-of-tidyverse.png" width="80%" style="display: block; margin: auto;" /> ] .pull-right[ - **ggplot2** is tidyverse's data visualization package - `gg` in "ggplot2" stands for Grammar of Graphics - Inspired by the book **Grammar of Graphics** by Leland Wilkinson - `ggplot()` is the main function in ggplot2 - Plots are constructed in layers - Structure of the code for plots can be summarized as ] -- ``` r ggplot(data = [dataset], mapping = aes(x = [x-variable], y = [y-variable])) + geom_xxx() + other options ``` --- ## ggplot2 `\(\in\)` tidyverse a.k.a. Grammar of Graphics .pull-left-narrow[ - **ggplot2** is tidyverse's data visualization package - `gg` in "ggplot2" stands for Grammar of Graphics - Inspired by the book **Grammar of Graphics** by Leland Wilkinson - Grammar of graphics is a tool to concisely describe the components of a graphic - The ggplot2 package comes with the tidyverse ``` r library(tidyverse) ``` - For help with ggplot2, see [ggplot2.tidyverse.org](http://ggplot2.tidyverse.org/) ] .pull-right-wide[ <img src="img/grammar-of-graphics.png" width="90%" style="display: block; margin: auto;" /> ] .footnote[ Source: [BloggoType](http://bloggotype.blogspot.com/2016/08/holiday-notes2-grammar-of-graphics.html)] --- class: middle # Wrapping Up... --- class: middle # Why do we visualize? --- ## Anscombe's quartet .midi.pull-left[ ``` ## set x y ## 1 I 10 8.04 ## 2 I 8 6.95 ## 3 I 13 7.58 ## 4 I 9 8.81 ## 5 I 11 8.33 ## 6 I 14 9.96 ## 7 I 6 7.24 ## 8 I 4 4.26 ## 9 I 12 10.84 ## 10 I 7 4.82 ## 11 I 5 5.68 ## 12 II 10 9.14 ## 13 II 8 8.14 ## 14 II 13 8.74 ## 15 II 9 8.77 ## 16 II 11 9.26 ## 17 II 14 8.10 ## 18 II 6 6.13 ## 19 II 4 3.10 ## 20 II 12 9.13 ## 21 II 7 7.26 ## 22 II 5 4.74 ``` ] .midi.pull-right[ ``` ## set x y ## 23 III 10 7.46 ## 24 III 8 6.77 ## 25 III 13 12.74 ## 26 III 9 7.11 ## 27 III 11 7.81 ## 28 III 14 8.84 ## 29 III 6 6.08 ## 30 III 4 5.39 ## 31 III 12 8.15 ## 32 III 7 6.42 ## 33 III 5 5.73 ## 34 IV 8 6.58 ## 35 IV 8 5.76 ## 36 IV 8 7.71 ## 37 IV 8 8.84 ## 38 IV 8 8.47 ## 39 IV 8 7.04 ## 40 IV 8 5.25 ## 41 IV 19 12.50 ## 42 IV 8 5.56 ## 43 IV 8 7.91 ## 44 IV 8 6.89 ``` ] --- ## Summarizing Anscombe's quartet <br> .medi.pull-left-narrow[ ``` r quartet %>% group_by(set) %>% summarize( mean_x = mean(x), mean_y = mean(y), sd_x = sd(x), sd_y = sd(y), r = cor(x, y) ) ``` ] .pull-right-wide[ ``` ## # A tibble: 4 × 6 ## set mean_x mean_y sd_x sd_y r ## <fct> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 I 9 7.50 3.32 2.03 0.816 ## 2 II 9 7.50 3.32 2.03 0.816 ## 3 III 9 7.5 3.32 2.03 0.816 ## 4 IV 9 7.50 3.32 2.03 0.817 ``` ] --- ## Visualizing Anscombe's quartet <br> .middle[ <img src="d03_dataviz_files/figure-html/quartet-plot-1.png" width="80%" style="display: block; margin: auto;" /> ] --- class: middle # Wrapping Up...