Graphing with ggplot2

Kelly McConville

Stat 100
Week 3 | Fall 2023

Announcements

With COVID working its way through campus right now, make sure to check the Sections spreadsheet and the Office hours spreadsheet for updates!
Grab a postcard and/or a stamp from SC 316 if you lost yours.
- We also have markers, colored pencils, and crayons!
Don’t forget that P-Set 1 due on Tuesday by 5pm in Gradescope.
Come by office hours with any questions.

Goals for Today

Come back to the general structure of ggplot2.
Learn a few standard graphs for numerical/quantitative data:
- Histogram: one numerical variable
- Side-by-side boxplot: one numerical variable and one categorical variable
- Side-by-side violin plot: one numerical variable and one categorical variable
- Scatterplot: two numerical variables
- Linegraph: two numerical variables

And, learn the standard graphic for categorical data:
- Barplot: one categorical variable
- Segmented barplot: two categorical variables
Also cover some common extensions and customizations.

Load Necessary Packages

ggplot2 is part of this collection of data science packages.

# Load necessary packages
library(tidyverse)

Data Setting: Eco-Totem Broadway Bicycle Count

Import the Data

july_2019 <- read_csv("data/july_2019.csv")

# Inspect the data
glimpse(july_2019)

Rows: 192
Columns: 8
$ DateTime  <chr> "07/04/2019 12:00:00 AM", "07/04/2019 12:15:00 AM", "07/04/2…
$ Day       <chr> "Thursday", "Thursday", "Thursday", "Thursday", "Thursday", …
$ Date      <date> 2019-07-04, 2019-07-04, 2019-07-04, 2019-07-04, 2019-07-04,…
$ Time      <time> 00:00:00, 00:15:00, 00:30:00, 00:45:00, 01:00:00, 01:15:00,…
$ Total     <dbl> 2, 3, 2, 0, 3, 2, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, …
$ Westbound <dbl> 2, 3, 1, 0, 2, 2, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, …
$ Eastbound <dbl> 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, …
$ Occasion  <chr> "Fourth of July", "Fourth of July", "Fourth of July", "Fourt…

`ggplot2` example code

Guiding Principle: We will map variables from the data to the aesthetic attributes (e.g. location, size, shape, color) of geometric objects (e.g. points, lines, bars).

ggplot(data = ---, mapping = aes(---)) +
  geom_---(---)

There are other layers, such as scales_---_---() and labs(), but we will wait on those.

Histograms

# Create histogram
ggplot(data = july_2019, 
       mapping = aes(x = Total)) +
  geom_histogram()

Histograms

# Create histogram
ggplot(data = july_2019, 
       mapping = aes(x = Total)) +
  geom_histogram(color = "white",
                 fill = "violetred1",
                 bins = 50)

mapping to a variable goes in aes()
setting to a specific value goes in the geom_---()

Boxplots

Five number summary:
- Minimum
- First quartile (Q1)
- Median
- Third quartile (Q3)
- Maximum
Interquartile range (IQR) \(=\) Q3 \(-\) Q1
Outliers: unusual points
- Boxplot defines unusual as being beyond \(1.5*IQR\) from \(Q1\) or \(Q3\).
Whiskers: reach out to the furthest point that is NOT an outlier

Boxplots

# Create boxplot
ggplot(data = july_2019, 
       mapping = aes(x = Occasion, 
                     y = Total)) +
  geom_boxplot()

Boxplots

ggplot(data = july_2019, 
       mapping = aes(x = Occasion, 
                     y = Total)) +
  geom_boxplot(fill = "springgreen3")

Boxplots

ggplot(data = july_2019, 
       mapping = aes(x = Occasion, 
                     y = Total,
                     fill = Total)) +
  geom_boxplot()

Boxplots

ggplot(data = july_2019, 
       mapping = aes(x = Occasion, 
                     y = Total,
                     fill = Occasion)) +
  geom_boxplot() +
  guides(fill = "none")

Violin Plots

ggplot(data = july_2019, 
       mapping = aes(x = Occasion, 
                     y = Total,
                     fill = Occasion)) +
  geom_violin() +
  guides(fill = "none")

Boxplot Versus Violin Plots

Scatterplots

Explore relationships between numerical variables.
- We will be especially interested in linear relationships.

ggplot(data = july_2019,
       mapping = aes(x = Time,
                     y = Total)) +
  geom_point(size = 2)

Scatterplots

ggplot(data = july_2019,
       mapping = aes(x = Time,
                     y = Total)) +
  geom_point(size = 2, alpha = 0.6)

Fix over-plotting
Why the weird pattern??

Scatterplots

ggplot(data = july_2019,
       mapping = aes(x = Time,
                     y = Total,
                     color = Occasion)) +
  geom_point(size = 2, alpha = 0.6)

Linegraphs

Also called time series plot when time is represented on the x axis.

ggplot(data = july_2019,
       mapping = aes(x = Time,
                     y = Total,
                     color = Occasion)) +
  geom_line(alpha = 0.6)

Linegraphs

Also called time series plot when time is represented on the x axis.

ggplot(data = july_2019,
       mapping = aes(x = Time,
                     y = Total,
                     color = Occasion)) +
  geom_line(alpha = 0.6) +
  theme(legend.pos = "bottom")

New Data Setting: Dog Names in Cambridge, MA

Based on dog license data collected by Cambridge’s Animal Commission

# Import and inspect data
dogs <- read_csv("https://data.cambridgema.gov/api/views/sckh-3xyx/rows.csv")
glimpse(dogs)

Rows: 3,942
Columns: 6
$ Dog_Name         <chr> "Butch", "Baxter", "Bodhi", "Ocean", "Coco", "Brio", …
$ Dog_Breed        <chr> "Mixed Breed", "Mixed Breed", "Golden Retriever", "Pu…
$ Location_masked  <chr> "POINT (-71.1328 42.3989)", "POINT (-71.1186 42.3814)…
$ Latitude_masked  <dbl> 42.3989, 42.3814, 42.3998, 42.3726, 42.3610, 42.3892,…
$ Longitude_masked <dbl> -71.1328, -71.1186, -71.1308, -71.1087, -71.1022, -71…
$ Neighborhood     <chr> "North Cambridge", "Neighborhood Nine", "North Cambri…

Data Wrangling

We haven’t learned this topic yet.

I only included this code for completeness/transparency.

# Create a column for Breed
dogs <- mutate(dogs, Breed = if_else(
                       Dog_Breed == "Mixed Breed",
                       "Mixed", "Single"))


# Find the 5 top most common names
top5names <- count(dogs, Dog_Name) %>%
  slice_max(n = 5, order_by = n) %>%
  select(Dog_Name) %>%
  pull()
  
# Filter dataset to only the 5 top most common names
dogs_top5 <- filter(dogs,
                     Dog_Name %in% top5names)

Before we graph the data, do we have any guesses on popular dog names?

Barplots

Displays the frequency for each category.

Barplots

# Create barplot
ggplot(data = dogs_top5, 
    mapping = aes(x = Dog_Name)) +
  geom_bar()

How could we make this graph better?

Barplots

# Create barplot
ggplot(data = dogs_top5, 
  mapping = aes(x = fct_infreq(Dog_Name))) +
  geom_bar()

Segmented Barplots

# Create segmented barplot
ggplot(data = dogs_top5, 
       mapping = aes(x = fct_infreq(Dog_Name),
                     fill = Breed)) +
  geom_bar() +
  theme(legend.pos = "bottom")

Each bar is divided into the frequencies of the fill variable.
Hard to make comparisons across categories.

Segmented Barplots

# Create segmented barplot
ggplot(data = dogs_top5, 
       mapping = aes(x = fct_infreq(Dog_Name),
                     fill = Breed)) +
  geom_bar(position = "dodge") +
  theme(legend.pos = "bottom")

Can add the position argument into the geom_bar().

Segmented Barplots

# Create segmented barplot
ggplot(data = dogs_top5, 
       mapping = aes(x = fct_infreq(Dog_Name),
                     fill = Breed)) +
  geom_bar(position = "fill") +
  theme(legend.pos = "bottom")

Now each bar is divided into proportions based on the fill variable.

Adding More Variables

Two main approaches:
- Utilize other aesthetics of the geom
- Facet: Create multiple plots across the categories of a categorical variable.

Utilize other `aes`thetics

ggplot(data = july_2019,
       mapping = aes(x = Time,
                     y = Total,
                     color = Occasion)) +
  geom_line(size = 2) +
  theme(legend.pos = "bottom")

Already saw how to add a third variable to a line graph (and a scatterplot) via color.
- Can also change size or type.

Consider Doing Both!

ggplot(data = dogs_top5,
       mapping = aes(x = Longitude_masked,
                     y = Latitude_masked,
                     color = Breed)) +
  geom_point(size = 2) +
  facet_wrap(~Dog_Name, ncol = 2)

Adding Some Context

ggplot(data = july_2019,
       mapping = aes(x = Time,
                     y = Total,
                     color = Occasion)) +
  geom_line(size = 2) +
  theme(legend.pos = "bottom") +
  labs(x = "Time of Day",
       y = "Number of Passes",
       color = "What Type of Day?",
       caption = "Data Collected by Eco-Totem",
       title = "Cycling Patterns at Broadway Bike Counter")

Customizing your `ggplot2` Plots

There are so many ways you can customize the look of your ggplot2 plots.
Let’s look at some common changes:
- Fussing with labels
- Zooming in
- Using multiple geoms
- Color!
- Themes

Fussing with Labels: Rotate

ggplot(data = dogs_top5,
       mapping = aes(x = Longitude_masked,
                     y = Latitude_masked)) +
  geom_point(size = 2)  +
  facet_grid(Breed~Dog_Name) + 
  theme(axis.text.x =
          element_text(angle = 45,
                       vjust = 1,
                       hjust = 1))

Zooming In

ggplot(data = july_2019, 
       mapping = aes(x = Occasion, 
                     y = Total,
                     fill = Occasion)) +
  geom_boxplot() +
  guides(fill = "none")

Zooming In

ggplot(data = july_2019, 
       mapping = aes(x = Occasion, 
                     y = Total)) +
  geom_boxplot(fill = "springgreen2") +
  guides(fill = "none") +
  coord_cartesian(ylim = c(0, 40))  +
  scale_fill_manual()

Multiple `geom`s

ggplot(data = july_2019, 
       mapping = aes(x = Occasion, 
                     y = Total,
                     fill = Occasion)) +
  geom_boxplot() +
  guides(fill = "none") +
  coord_cartesian(ylim = c(0, 40)) +
  geom_jitter(width = 0.1,
              height = 0, 
              alpha = 0.6)

Multiple `geom`s

ggplot(data = july_2019,
       mapping = aes(x = Time,
                     y = Total,
                     color = Occasion)) +
  geom_line(size = 2) +
  theme(legend.pos = "bottom") +
  geom_point(size = 3)

Change the Color

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"

Change the Color

ggplot(data = july_2019,
       mapping = aes(x = Time,
                     y = Total,
                     color = Occasion)) +
  geom_line(size = 2) +
  theme(legend.pos = "bottom") +
  scale_color_manual(values = c("violetred2",
                                "steelblue4"))

Change the Color

ggplot(data = july_2019,
       mapping = aes(x = Time,
                     y = Total,
                     color = Occasion)) +
  geom_line(size = 2) +
  theme(legend.pos = "bottom") +
  scale_color_manual(values = c("#0D6759",
                                "#E4844A"))

Use a Different Theme

ggplot(data = july_2019,
       mapping = aes(x = Time,
                     y = Total,
                     color = Occasion)) +
  geom_line(size = 2) +
  scale_color_manual(values = c("#0D6759",
                                "#E4844A")) +
  theme_bw() +
  theme(legend.pos = "bottom")

What `ggplot2` questions do we have?

Reminders

With COVID working its way through campus right now, make sure to check the Sections spreadsheet and the Office hours spreadsheet for updates!
Grab a postcard and/or a stamp from SC 316 if you lost yours.
- We also have markers, colored pencils, and crayons!
Don’t forget that P-Set 1 due on Tuesday by 5pm in Gradescope.
Come by office hours with any questions.

Announcements

Goals for Today

Load Necessary Packages

Data Setting: Eco-Totem Broadway Bicycle Count

Import the Data

ggplot2 example code

Histograms

Histograms

Boxplots

Boxplots

Boxplots

Boxplots

Boxplots

Violin Plots

Boxplot Versus Violin Plots

Scatterplots

Scatterplots

Scatterplots

Linegraphs

Linegraphs

New Data Setting: Dog Names in Cambridge, MA

Data Wrangling

Before we graph the data, do we have any guesses on popular dog names?

Barplots

Barplots

Barplots

Segmented Barplots

Segmented Barplots

Segmented Barplots

Adding More Variables

Utilize other aesthetics

Facet

Facet

Consider Doing Both!

Adding Some Context

Customizing your ggplot2 Plots

Fussing with Labels: Rotate

Zooming In

Zooming In

Multiple geoms

Multiple geoms

Change the Color

Change the Color

Change the Color

Use a Different Theme

What ggplot2 questions do we have?

Reminders

`ggplot2` example code

Utilize other `aes`thetics

Customizing your `ggplot2` Plots

Multiple `geom`s

Multiple `geom`s

What `ggplot2` questions do we have?