More ggplot2






Grayson White

Math 141
Week 2 | Fall 2025

Goals for Today

  • Recall the graphs for numerical/quantitative data from last time:
    • 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
  • Introduce graphs for categorical data:
    • Barplot: one categorical variable
    • Segmented barplot: two categorical variables
  • Also cover some common extensions and customizations.

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: 1,581
Columns: 6
$ Dog_Name         <chr> "Thor", "Lucy", "Ruby", "Georgie", "Candy", "kylo-roo…
$ Dog_Breed        <chr> "Boxer", "Poodle", "Collie", "Lhasa Apso", "Beagle", …
$ Location_masked  <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
$ Latitude_masked  <dbl> 42.3622, 42.3696, 42.3860, 42.3742, 42.3918, 42.3862,…
$ Longitude_masked <dbl> -71.0846, -71.1109, -71.1237, -71.1418, -71.1290, -71…
$ Neighborhood     <chr> "East Cambridge", "Mid-Cambridge", "Neighborhood Nine…

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)

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.position = "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.position = "bottom")

  • Can add the position argument into the geom_bar().

Segmented Barplots

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

library(pdxTrees)
near_Reed <- get_pdxTrees_parks(park = c("Woodstock Park", "Sellwood Riverfront Park", "Kenilworth Park")) %>%
  filter(Genus %in% c("Acer", "Quercus", "Pinus", "Thuja", "Pseudotsuga"))
ggplot(data = near_Reed,
       mapping = aes(x = DBH,
                     y = Carbon_Storage_lb,
                     color = Genus)) +
  geom_point(size = 2) + 
  theme(legend.position = "bottom")

  • Already saw how to add a third variable to a scatterplot via color.
    • Can also change size or the point’s shape.

Where do the dogs live?

ggplot(data = dogs_top5,
       mapping = aes(x = Longitude_masked,
                     y = Latitude_masked)) +
  geom_point(size = 2)

  • How can we represent name?

Facet

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

  • How can we represent breed as well?

Facet

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

  • What’s another way we could represent breed?

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 = near_Reed,
       mapping = aes(x = DBH,
                     y = Carbon_Storage_lb,
                     color = Genus)) +
  geom_point(size = 2) + 
  theme(legend.position = "bottom") + 
  labs(x = "Diameter at Breast Height",
       y = "Carbon Storage (lbs)",
       color = "What Species?",
       caption = "Data Collected as part of the Urban Forestry Tree Inventory Project",
       title = "Tree Species Relationships Near Reed College")

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

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

ggplot(data = biketown, 
       mapping = aes(x = PaymentPlan, 
                     y = Distance_Miles,
                     fill = PaymentPlan)) +
  geom_boxplot() +
  guides(fill = "none")

Zooming In

ggplot(data = biketown, 
       mapping = aes(x = PaymentPlan, 
                     y = Distance_Miles,
                     fill = PaymentPlan)) +
  geom_boxplot() +
  guides(fill = "none") +
  coord_cartesian(ylim = c(0, 5))

Multiple geoms

ggplot(data = biketown, 
       mapping = aes(x = PaymentPlan, 
                     y = Distance_Miles,
                     fill = PaymentPlan)) +
  geom_boxplot() +
  guides(fill = "none") +
  coord_cartesian(ylim = c(0, 10)) +
  geom_jitter(width = 0.1,
              height = 0, 
              alpha = 0.2)

Multiple geoms

ggplot(data = near_Reed,
       mapping = aes(x = DBH,
                     y = Carbon_Storage_lb,
                     color = Genus)) +
  geom_line() +
  theme(legend.position = "bottom") +
  geom_point(size = 2)

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 = near_Reed,
       mapping = aes(x = DBH,
                     y = Carbon_Storage_lb,
                     color = Genus)) +
  geom_line(size = 2) +
  theme(legend.position = "bottom") +
  scale_color_manual(values = c("violetred2",
                                "steelblue4",
                                "forestgreen",
                                "goldenrod",
                                "maroon"))

Use a Different Theme

ggplot(data = near_Reed,
       mapping = aes(x = DBH,
                     y = Carbon_Storage_lb,
                     color = Genus)) +
  geom_line(size = 2) +
  scale_color_manual(values = c("violetred2",
                                "steelblue4",
                                "forestgreen",
                                "goldenrod",
                                "maroon")) +
  theme_bw() +
  theme(legend.position = "bottom")

What ggplot2 questions do we have?