CODEWITHSUNDEEP
rggplot2
peho15ae
peho15ae

Reputation: 119

ggplot2 using facetwrap and multiple variables

I am looking to create a plot depicting the total number of observations and the number of observations with the variable Rating = Rated within each segment small, medium, and large. My expected output would be three graphs with one line depicting the total number of observations and one line depicting the number of observations with the variable Rated

My current code looks like this:

df <- CombData %>%
  group_by(Date, MarketSeg) %>%
  summarise(Total = n())

ggplot(data = CombData1, aes(x=Date, y=Ratings, group=MarketSeg, color=MarketSeg)) + 
  geom_line() + facet_wrap(~MarketSeg)

Thanks in advance.

Data:

structure(list(Date = structure(c(17044, 17044, 17044, 17044, 
17044, 17044, 17044, 17044, 17044, 17044, 17044, 17044, 17044, 
17044, 17044, 17044, 17044, 17044, 17044, 17044, 17044, 17044, 
17044, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 
17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 
17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 
17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 
17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 
17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 
17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 
17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 
17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 
17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 
17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 
17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 
17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 
17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 17074, 
17074, 17074, 17074, 17074, 17074, 17074, 17074, 17105, 17105, 
17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 
17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 
17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 
17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 
17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 
17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 
17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 
17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 
17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 
17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 
17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 
17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 
17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 
17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 17105, 
17105, 17105, 17105, 17105, 17135, 17135, 17135, 17135, 17135, 
17135, 17135, 17135, 17135, 17135, 17135, 17135, 17135, 17135, 
17135, 17135, 17135, 17135, 17135, 17135, 17135, 17135, 17135, 
17135, 17135, 17135, 17135, 17135, 17135, 17135, 17135, 17135, 
17135, 17135), class = "Date"), MarketCap = c(17793490000, 37606234252.4, 
2.1108e+10, 1309638615, 1.113e+10, 3397350000, 2652530240, 37091806405, 
1359499200, 6809300000, 76266899.28, 13774786240, 1545680000, 
63594722.73, 51341862.01, 50107136.47, 1.29e+09, 46223250, 128974374.6, 
3577976769.416, 3706781337, 11026283863.73, 5842461152.7, 4362690525, 
821145923.5, 238287420, 227040000, 131262000, 73756593.4, 77758200, 
73271825.2, 89201950, 24055716, 7815943725, 75117974128, 35904920250, 
1040640000, 17203972.5, 243725033, 275137500, 797503125, 2959027243, 
12806008832, 87684100, 1081800000, 251619858, 12771500000, 745577600, 
901299772.75, 97787904480, 1037369208, 269790000, 96921756.9, 
82668000, 363480200, 11028750000, 313985864.5, 2174677900, 765596013, 
72429837.39, 1065910694, 1324654600.8, 120852648578.5, 288792000, 
264450000, 165827845.298, 68080914610, 22072758675.4, 190250062289, 
2650279142.5, 93334060, 42901711525.4, 10427653484.6, 385600000, 
1381724307.15, 290812500, 29367359691, 14549176078.6, 248830003.2, 
793066396.5, 58800000, 14086361.16, 8761750000, 7733515000, 262440000, 
739680000, 8636728800, 1.28e+09, 8033914752, 42317532.63, 9663376.8, 
89517150, 2008211179.58, 1422750374.5, 233263043.52, 616047756.6, 
216763086, 483999180, 77497804.8, 18828151.2, 328728735, 6.27e+10, 
117600000, 3996340000, 371634938.745, 1.332e+09, 321133312.5, 
67716000, 115604797000, 71070174, 334599975, 1077300000, 170400000, 
67878383.2, 572400000, 352716000, 51949883424, 93762513621, 2421822652, 
313731880, 74698740600, 1.01772e+11, 17622500000, 360985600, 
15977500000, 4872145008, 507927000, 224770774, 554260125600, 
51077328972.6, 38632433, 5137500000, 17690700000, 37577980132, 
2.01e+10, 1322669845, 1.13e+10, 3386700000, 2521047060, 36000870922.5, 
1282459200, 6535100000, 72800222.04, 14776392320, 1432862000, 
58929472.8, 47415719.621, 43476908, 1.27e+09, 41416032, 104091858.6, 
3534532125.208, 3769080183, 11393974326.04, 5644411622.1, 4462246625, 
814971894, 239169966, 254100000, 133620000, 72896458.2, 74767500, 
81688183.5, 94192500, 15034822.5, 7716165720, 72621965494, 42379578000, 
1010830000, 13233825, 249669546, 276375000, 799912500, 3239810850, 
12182897664, 94959200, 1083600000, 292003292, 12617750000, 755452800, 
927965446.5, 104629033600, 977750288, 263160000, 65804771.79, 
75696000, 361630000, 10977750000, 311226762, 2350055150, 878472348.25, 
64650336.337, 1108358465, 1278175492, 120409559124.5, 270742500, 
269062500, 167940301.926, 67357931446, 21267861444.6, 205792725082, 
2615176107.5, 93536520, 43178369269, 12247597602.8, 424160000, 
1404375525.3, 290812500, 29224799692.5, 15307698168.1, 220318232, 
733721292, 51300000, 9328716, 8848500000, 7114833800, 270540000, 
753080000, 8434161600, 1.11e+09, 8536034424, 47942014.815, 10974835.08, 
84062700, 2076286134.82, 1465733769.5, 216692444.8, 629969739.8, 
218176758.3, 482694600, 82056499.2, 17833167.6, 298047386.4, 
6.2396e+10, 128800000, 4070190000, 369604146.73, 1.314e+09, 328084250, 
65407500, 112956396196, 63568322.3, 326381730, 1065960000, 1.92e+08, 
72918857.2, 587250000, 392616000, 53505742876.8, 103244116122, 
2449851782, 403369560, 64499735880, 93614400000, 17337500000, 
355699200, 15541750000, 5166831198, 515508000, 237105755.5, 487845513600, 
49462015406.4, 36267182, 5037500000, 17149700000, 37408455409.6, 
1.965e+10, 1316154230, 1.173e+10, 3.408e+09, 2449588810, 33579526315, 
1335360000, 6553380000, 69600212.28, 14568858720, 1423750000, 
59175012.27, 46207675.809, 45650753.4, 1.3e+09, 49181538, 111635430.34, 
3413507759.2, 3613333068, 10906673713.34, 5050263030.3, 4419579725, 
703839363, 241229240, 251790000, 137812000, 73111492, 75764400, 
83173423.2, 92506950, 16237608.3, 7815943725, 70957959738, 39358071050, 
1151750000, 9175452, 259554030.12, 282975000, 798707812.5, 3175014633, 
12161411072, 87301200, 1083600000, 333939935, 14749750000, 720889600, 
767971404, 93663106040, 977750288, 265200000, 153274185.36, 74700000, 
370040000, 1.1934e+10, 231764610), MarketSeg = c("Large", "Large", 
"Large", "Medium", "Large", "Medium", "Medium", "Large", "Medium", 
"Medium", "Small", "Large", "Medium", "Small", "Small", "Small", 
"Medium", "Small", "Small", "Medium", "Medium", "Large", "Medium", 
"Medium", "Small", "Small", "Small", "Small", "Small", "Small", 
"Small", "Small", "Small", "Large", "Large", "Large", "Small", 
"Small", "Small", "Small", "Small", "Medium", "Large", "Small", 
"Small", "Small", "Large", "Small", "Small", "Large", "Small", 
"Small", "Small", "Small", "Small", "Large", "Small", "Medium", 
"Small", "Small", "Small", "Medium", "Large", "Small", "Small", 
"Small", "Large", "Large", "Large", "Medium", "Small", "Large", 
"Large", "Small", "Medium", "Small", "Large", "Large", "Small", 
"Small", "Small", "Small", "Large", "Large", "Small", "Small", 
"Large", "Medium", "Large", "Small", "Small", "Small", "Medium", 
"Medium", "Small", "Small", "Small", "Small", "Small", "Small", 
"Small", "Large", "Small", "Medium", "Small", "Medium", "Small", 
"Small", "Large", "Small", "Small", "Small", "Small", "Small", 
"Small", "Small", "Large", "Large", "Medium", "Small", "Large", 
"Large", "Large", "Small", "Large", "Medium", "Small", "Small", 
"Large", "Large", "Small", "Medium", "Large", "Large", "Large", 
"Medium", "Large", "Medium", "Medium", "Large", "Medium", "Medium", 
"Small", "Large", "Medium", "Small", "Small", "Small", "Medium", 
"Small", "Small", "Medium", "Medium", "Large", "Medium", "Medium", 
"Small", "Small", "Small", "Small", "Small", "Small", "Small", 
"Small", "Small", "Large", "Large", "Large", "Small", "Small", 
"Small", "Small", "Small", "Medium", "Large", "Small", "Small", 
"Small", "Large", "Small", "Small", "Large", "Small", "Small", 
"Small", "Small", "Small", "Large", "Small", "Medium", "Small", 
"Small", "Small", "Medium", "Large", "Small", "Small", "Small", 
"Large", "Large", "Large", "Medium", "Small", "Large", "Large", 
"Small", "Medium", "Small", "Large", "Large", "Small", "Small", 
"Small", "Small", "Large", "Medium", "Small", "Small", "Large", 
"Small", "Large", "Small", "Small", "Small", "Medium", "Medium", 
"Small", "Small", "Small", "Small", "Small", "Small", "Small", 
"Large", "Small", "Medium", "Small", "Medium", "Small", "Small", 
"Large", "Small", "Small", "Small", "Small", "Small", "Small", 
"Small", "Large", "Large", "Medium", "Small", "Large", "Large", 
"Large", "Small", "Large", "Medium", "Small", "Small", "Large", 
"Large", "Small", "Medium", "Large", "Large", "Large", "Medium", 
"Large", "Medium", "Medium", "Large", "Medium", "Medium", "Small", 
"Large", "Medium", "Small", "Small", "Small", "Medium", "Small", 
"Small", "Medium", "Medium", "Large", "Medium", "Medium", "Small", 
"Small", "Small", "Small", "Small", "Small", "Small", "Small", 
"Small", "Large", "Large", "Large", "Medium", "Small", "Small", 
"Small", "Small", "Medium", "Large", "Small", "Small", "Small", 
"Large", "Small", "Small", "Large", "Small", "Small", "Small", 
"Small", "Small", "Large", "Small"), ESG = c("Not Rated", "Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Rated", "Not Rated", "Not Rated", "Not Rated", "Rated", "Not Rated", 
"Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Rated", "Rated", "Not Rated", 
"Not Rated", "Rated", "Rated", "Not Rated", "Not Rated", "Rated", 
"Not Rated", "Not Rated", "Not Rated", "Rated", "Rated", "Not Rated", 
"Not Rated", "Not Rated", "Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Rated", "Not Rated", 
"Not Rated", "Not Rated", "Rated", "Not Rated", "Rated", "Not Rated", 
"Not Rated", "Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Rated", "Rated", "Not Rated", "Not Rated", "Rated", 
"Rated", "Not Rated", "Not Rated", "Rated", "Not Rated", "Not Rated", 
"Not Rated", "Rated", "Rated", "Not Rated", "Not Rated", "Not Rated", 
"Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Rated", "Not Rated", 
"Not Rated", "Not Rated", "Not Rated", "Not Rated", "Not Rated", 
"Not Rated")), class = c("grouped_df", "tbl_df", "tbl", "data.frame"
), row.names = c(NA, -321L), groups = structure(list(Date = structure(c(17044, 
17044, 17074, 17074, 17105, 17105, 17135, 17135), class = "Date"), 
    ESG = c("Not Rated", "Rated", "Not Rated", "Rated", "Not Rated", 
    "Rated", "Not Rated", "Rated"), .rows = list(c(1L, 3L, 4L, 
    5L, 6L, 7L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 
    19L, 21L, 22L, 23L), c(2L, 8L, 20L), c(24L, 25L, 26L, 27L, 
    28L, 29L, 30L, 31L, 32L, 33L, 34L, 36L, 37L, 38L, 39L, 40L, 
    41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 51L, 52L, 53L, 
    54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 64L, 65L, 66L, 
    68L, 70L, 71L, 72L, 73L, 74L, 75L, 76L, 78L, 79L, 80L, 81L, 
    82L, 83L, 84L, 85L, 86L, 87L, 88L, 89L, 90L, 91L, 92L, 93L, 
    94L, 95L, 96L, 97L, 98L, 99L, 100L, 101L, 103L, 104L, 105L, 
    106L, 107L, 108L, 110L, 111L, 112L, 113L, 114L, 115L, 116L, 
    119L, 120L, 123L, 124L, 126L, 127L, 128L, 131L, 132L, 133L, 
    135L, 136L, 137L, 138L, 139L, 141L, 142L, 143L, 144L, 145L, 
    146L, 147L, 148L, 149L, 150L, 151L, 153L, 154L, 155L), c(35L, 
    50L, 63L, 67L, 69L, 77L, 102L, 109L, 117L, 118L, 121L, 122L, 
    125L, 129L, 130L, 134L, 140L, 152L), c(156L, 157L, 158L, 
    159L, 160L, 161L, 162L, 163L, 164L, 165L, 166L, 168L, 169L, 
    170L, 171L, 172L, 173L, 174L, 175L, 176L, 177L, 178L, 179L, 
    180L, 181L, 183L, 184L, 185L, 186L, 187L, 188L, 189L, 190L, 
    191L, 192L, 193L, 194L, 196L, 197L, 198L, 200L, 202L, 203L, 
    205L, 206L, 207L, 208L, 210L, 211L, 212L, 213L, 214L, 215L, 
    216L, 217L, 218L, 219L, 220L, 221L, 222L, 223L, 224L, 225L, 
    226L, 227L, 228L, 229L, 230L, 231L, 232L, 233L, 235L, 236L, 
    237L, 238L, 239L, 240L, 242L, 243L, 244L, 245L, 246L, 247L, 
    248L, 251L, 252L, 255L, 256L, 258L, 259L, 260L, 263L, 264L, 
    265L, 267L, 268L, 269L, 270L, 271L, 273L, 274L, 275L, 276L, 
    277L, 278L, 279L, 280L, 281L, 282L, 283L, 285L, 286L, 287L
    ), c(167L, 182L, 195L, 199L, 201L, 204L, 209L, 234L, 241L, 
    249L, 250L, 253L, 254L, 257L, 261L, 262L, 266L, 272L, 284L
    ), c(288L, 289L, 290L, 291L, 292L, 293L, 294L, 295L, 296L, 
    297L, 298L, 300L, 301L, 302L, 303L, 304L, 305L, 306L, 307L, 
    308L, 309L, 310L, 311L, 312L, 313L, 315L, 316L, 317L, 318L, 
    319L, 320L, 321L), c(299L, 314L))), row.names = c(NA, -8L
), class = c("tbl_df", "tbl", "data.frame"), .drop = TRUE))

Upvotes: 1

Views: 66

Answers (2)

GGamba
GGamba

Reputation: 13680

Or:

library(ggplot2) 
library(dplyr)

df <- df %>%
  group_by(Date, MarketSeg, ESG) %>%
  summarise(Total = n()) 

df %>%
  ggplot(aes(x=Date, y=Total, group=MarketSeg, color=MarketSeg, size = 'Rated')) + 
  geom_line(data = ~.x %>% summarise(Total=sum(Total)), aes(size='Total')) + 
  geom_line(data = ~.x %>% filter(ESG=='Rated')) +
  facet_wrap(~MarketSeg) +
  scale_size_manual(values = c(.5, 2))

Created on 2020-04-14 by the reprex package (v0.3.0)

Upvotes: 2

stefan
stefan

Reputation: 123783

Try this.

library(ggplot2)
library(dplyr)

# Total number of obs
df <- CombData %>%
  group_by(Date, MarketSeg) %>%
  summarise(Total = n())

# Number of rated obs
df1 <- CombData %>%
  group_by(Date, MarketSeg, ESG) %>%
  summarise(Total = n()) %>% 
  filter(ESG == "Rated")

ggplot() +
  geom_line(data = df, mapping = aes(x = Date, y = Total, group = MarketSeg, color = MarketSeg)) +
  geom_line(data = df1, mapping = aes(x = Date, y = Total, group = MarketSeg, lty = ESG), color = "red", size = 1) +
  facet_wrap(~MarketSeg)

Created on 2020-04-14 by the reprex package (v0.3.0)

Upvotes: 1

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