ggplot2 using facetwrap and multiple variables

Question

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))

GGamba · Accepted Answer · 2020-04-14 09:51:19Z

2

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)}

answered Apr 14, 2020 at 9:51

GGamba

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stefan · Accepted Answer · 2020-04-14 09:40:29Z

1

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)}

answered Apr 14, 2020 at 9:40

stefan

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