Graphing with ggplot2
Kelly McConville
Stat 100
Week 3 | Fall 2023
ggplot2
.ggplot2
is part of this collection of data science packages.
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 codeGuiding 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).
There are other layers, such as scales_---_---()
and labs()
, but we will wait on those.
aes()
geom_---()
Also called time series plot when time is represented on the x axis.
Also called time series plot when time is represented on the x axis.
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…
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)
Displays the frequency for each category.
How could we make this graph better?
Each bar is divided into the frequencies of the fill
variable.
Hard to make comparisons across categories.
position
argument into the geom_bar()
.fill
variable.aes
thetics of the geom
aes
theticscolor
.
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")
ggplot2
PlotsThere are so many ways you can customize the look of your ggplot2
plots.
Let’s look at some common changes:
geoms
geom
sgeom
s [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"
ggplot2
questions do we have?