How to Un-Sort The legends in the graph in R?

Question

I am not an expert in R. I am having an issue, the legends are sorted alphabetically.

I cannot arrange them manually because I have 87 patients and each patient has 300 days and the status (category) changes every day so i want to plot the graph exactly like it has in the source.

ggplot(data = summ_cc, 
       aes(x = data$`Patient Number`, y = data$count_day, fill = data$Category)) + 
  geom_bar(position = position_stack(reverse = TRUE), stat="identity",na.rm = FALSE)+
  scale_fill_discrete(breaks = data$Category)

structure(list(`Patient Number` = c("Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 1", 
"Patient 1", "Patient 1", "Patient 1", "Patient 1", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2", 
"Patient 2", "Patient 2", "Patient 2", "Patient 2", "Patient 2"
), Day = c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 
15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 
31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 
47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 
63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 
79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 
95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 
109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 
122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 
135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 
148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 
161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 
174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 
187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 
200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 
213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 
226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 
239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 
252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 
265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 
278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 
291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 
304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 0, 
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 
19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 
35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 
51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 
67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 
83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 
99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 
112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 
125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 
138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 
151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 
164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 
177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 
190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 
203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 
216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 
229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 
242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 
255), Category = structure(c(65L, 65L, 65L, 65L, 65L, 65L, 65L, 
65L, 65L, 16L, 27L, 38L, 49L, 57L, 58L, 59L, 60L, 6L, 7L, 8L, 
9L, 10L, 11L, 12L, 13L, 14L, 15L, 17L, 18L, 19L, 20L, 21L, 22L, 
23L, 24L, 25L, 26L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 
37L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 50L, 51L, 
52L, 53L, 54L, 55L, 56L, 61L, 61L, 64L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 67L, 
67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 
67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 
67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 
67L, 67L, 67L, 67L, 67L, 63L, 63L, 63L, 63L, 63L, 63L, 63L, 63L, 
63L, 63L, 63L, 63L, 63L, 63L, 63L, 66L, 66L, 66L, 66L, 66L, 66L, 
66L, 66L, 66L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 
66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 
66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 66L, 
66L, 66L, 66L, 66L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 65L, 65L, 
65L, 65L, 65L, 65L, 65L, 65L, 65L, 65L, 65L, 65L, 62L, 62L, 62L, 
62L, 62L, 62L, 62L, 62L, 62L, 62L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 62L, 62L, 62L, 62L, 62L, 62L, 62L, 
62L, 62L, 62L, 62L, 68L, 68L, 68L, 68L, 68L, 68L, 68L, 68L, 1L, 
1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 67L, 67L, 67L, 67L, 67L, 67L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 67L, 67L, 67L, 67L, 67L, 
67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 
67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 
67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 
67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 67L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("AD", "Admin delay", 
"CC", "CD", "CP", "CP10", "CP11", "CP12", "CP13", "CP14", "CP15", 
"CP16", "CP17", "CP18", "CP19", "CP2", "CP20", "CP21", "CP22", 
"CP23", "CP24", "CP25", "CP26", "CP27", "CP28", "CP29", "CP3", 
"CP30", "CP31", "CP32", "CP33", "CP34", "CP35", "CP36", "CP37", 
"CP38", "CP39", "CP4", "CP40", "CP41", "CP42", "CP43", "CP44", 
"CP45", "CP46", "CP47", "CP48", "CP49", "CP5", "CP50", "CP51", 
"CP52", "CP53", "CP54", "CP55", "CP56", "CP6", "CP7", "CP8", 
"CP9", "DG", "ECG", "LG", "MDC", "PP", "SC", "SPC", "SPEC"), class = "factor")), row.names = c(NA, 
-572L), class = "data.frame")

I wanted to count the frequency for each patient's category.

df=test %>% count(Category, `Patient Number`)

Here is the result:

 tibble: 72 x 3
   Category    `Patient Number`     n
   <fct>       <chr>            <int>
 1 AD          Patient 1           34
 2 AD          Patient 2           15
 3 Admin delay Patient 2           30
 4 CC          Patient 2           20
 5 CD          Patient 1           52
 6 CD          Patient 2           88
 7 CP          Patient 1           52
 8 CP10        Patient 1            1
 9 CP11        Patient 1            1
10 CP12        Patient 1            1

Issue: I want to plot them into a staked bar chart on the x axis it should be Patient number on y axis should be N(Count) with respective category and it should not be sorted. I have 87 patients number.

ggplot(data = df, aes(x = `Patient Number`, y = n, fill = as.factor(Category))) + geom_bar(position = position_stack(reverse = TRUE), stat="identity",na.rm = FALSE)+scale_fill_discrete(breaks = Category)

(1) `ggplot2` keeps the order when the variable being ordered is a `factor`. Try `data$Category <- factor(data$Category, levels=...)` where `...` is the order unique vector of all possible values. (2) Don't use `data$` within calls, just `aes(`Patient Number`, ...)`. (3) If you want more help, then make this question reproducible, see https://stackoverflow.com/q/5963269, [mcve], and https://stackoverflow.com/tags/r/info. — r2evans, Jul 06 '20 at 16:35
Thank you for replying but I can not arrange it manually because each patient has 300 values(days) in their respective category. How can I arrange this? All I want is, I can plot the data exactly like it shows in the data set right after another for 87 patients 300 days with a respective category. — tashu, Jul 07 '20 at 13:47

How to Un-Sort The legends in the graph in R?

0 Answers0