ggplot stacked bar plot from 2 separate data frames
mar*_*y_c 4 r bar-chart ggplot2
I have been struggling with this conundrum all day and getting close, but no cigar. I have two data frames which are the results of two separate socio-economic surveys from two districts within a city. I want to compare columns from these data frames side by side in a bar plot to show the frequencies (counts) of responses to a particular question across both surveys.
The questions asked in each survey were identical. However, they were coded slightly differently and therefore the column names are slightly different as follows! I have managed to plot data from my two data frames (ar and bn) on the same bar plot with the raw data i.e. without having to merge the data frames. However, I seem unable to plot stacked bar plots side-by-side.
I used ggplot2 with the following code:
ggplot(bn, aes(A8_HHH_hig, fill=A6_Sex_HHH))
+ geom_bar(position="stack", alpha=0.5)
+ geom_bar(data=ar, aes(A9_HHHedulevl, fill=A7_HHsex), position="stack", alpha=0.5)
Which produces this:
As you'll notice I am attempting to plot the split between male and female respondents based on their highest level of schooling for the two data frames. (Note the sex of the respondent is also coded differently in each data frame i.e. male/m and female/f.)
I'd really like these two stacked bar plots to be plotted on the same grid, side by side so it is easy for me to compare values. However, I'm not entirely sure if I can use the position="dodge" option here, as the values come from different dataframes.
Does anyone know if this is possible?! Or perhaps another way of comparing these values, visually?
I've attached some reproducible code if anyone has the time to have a look!
thanks
dput(ar)
structure(list(District = c("Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi"), A9_HHHedulevl = structure(c(9L,
9L, 9L, 9L, 8L, 9L, 5L, 9L, 9L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 2L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 3L, 9L, 3L, 9L, 9L, 9L, 9L,
7L, 7L, 8L, 6L, 9L, 9L, 8L, 9L, 9L, 8L, 6L, 9L, 9L, 9L, 9L, 8L,
6L, 9L, 9L, 9L, 6L, 9L, 9L, 1L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 4L, 9L, 6L, 9L, 9L, 9L, 9L, 6L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 8L, 6L, 8L, 9L, 9L, 9L, 6L, 6L, 3L, 6L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 6L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 6L, 9L, 9L, 9L,
3L), .Label = c("Adult Education", "Junior Secondary", "koranic",
"NCE", "None", "Polytechnic", "Senior Primary", "Senior Secondary",
"University"), class = "factor"), A7_HHsex = structure(c(2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L), .Label = c("female", "male"), class = "factor")), .Names = c("District",
"A9_HHHedulevl", "A7_HHsex"), row.names = c(1L, 2L, 3L, 4L, 5L,
6L, 7L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 19L, 20L,
21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L,
34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 46L, 47L,
48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L,
61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L,
74L, 75L, 76L, 77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 86L,
87L, 88L, 89L, 90L, 91L, 92L, 93L, 94L, 95L, 96L, 97L, 98L, 99L,
100L, 101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 110L,
111L, 113L, 114L, 115L, 116L, 117L, 118L, 119L, 120L, 121L, 122L,
123L, 124L, 125L, 126L, 127L, 128L, 129L, 130L, 131L, 132L, 133L,
134L), class = "data.frame", na.action = structure(131:135, .Names = c("135",
"136", "137", "138", "139"), class = "omit"))
dput(bn)
structure(list(District = c("Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa"), A8_HHH_hig = structure(c(7L, 7L, 7L, 12L, 7L, 7L,
12L, 4L, 4L, 4L, 4L, 4L, 9L, 7L, 7L, 10L, 4L, 1L, 4L, 7L, 10L,
12L, 12L, 12L, 7L, 12L, 9L, 6L, 4L, 11L, 4L, 4L, 4L, 10L, 12L,
12L, 12L, 12L, 7L, 10L, 9L, 11L, 7L, 7L, 7L, 7L, 9L, 7L, 7L,
7L, 7L, 9L, 7L, 12L, 12L, 7L, 12L, 11L, 7L, 7L, 12L, 12L, 12L,
12L, 12L, 12L, 7L, 12L, 10L, 10L, 12L, 8L, 4L, 4L, 12L, 12L,
4L, 12L, 12L, 12L, 7L, 7L, 9L, 2L, 9L, 12L, 2L, 5L, 12L, 7L,
10L, 10L, 12L, 10L, 10L, 4L, 10L, 1L, 5L, 7L, 1L, 10L, 10L, 10L,
10L, 10L, 10L, 3L, 10L, 10L, 4L, 10L, 10L, 10L, 10L, 10L, 4L,
10L, 10L, 10L, 3L, 10L, 9L, 4L, 4L, 4L, 4L, 12L, 12L, 12L, 12L,
3L, 7L, 7L, 5L, 7L, 7L, 12L, 12L, 7L, 10L, 7L, 7L, 7L, 12L, 12L,
7L, 7L, 12L, 12L, 12L, 12L, 12L, 7L, 12L, 12L, 12L, 12L, 12L,
10L, 10L, 12L, 12L, 9L, 12L, 12L, 7L, 6L, 12L, 12L, 7L, 12L,
10L, 5L, 12L, 12L, 7L, 11L, 12L, 12L, 12L, 5L, 7L, 7L, 12L, 12L,
7L, 7L, 7L, 12L, 7L, 7L, 12L, 12L, 12L, 1L), .Label = c("Adult Education",
"Junior Primary", "Junior Secondary", "Koranic", "NCE", "None",
"Polytechnic", "Prelim / JMB", "Senior Primary", "Senior Secondary",
"Technical College", "University"), class = "factor"), A6_Sex_HHH = structure(c(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, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L,
1L, 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, 1L, 1L, 2L, 1L, 2L, 2L,
2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 1L), .Label = c("F", "M"), class = "factor")), .Names = c("District",
"A8_HHH_hig", "A6_Sex_HHH"), row.names = c(NA, 196L), class = "data.frame")
This is an example of the kind of thing I am looking to produce:
structure(list(sex = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L,
2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L,
2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, NA, NA, NA, NA, NA,
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, 1L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L,
2L, 1L, 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, 1L, 1L, 2L, 1L, 2L,
2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 1L), .Label = c("female", "male"), class = "factor"),
education = structure(c(9L, 9L, 9L, 9L, 8L, 9L, 5L, 9L, 9L,
8L, 9L, 9L, 9L, 9L, 9L, 9L, 2L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 3L, 9L, 3L, 9L, 9L, 9L, 9L, 7L, 7L, 8L, 6L, 9L, 9L,
8L, 9L, 9L, 8L, 6L, 9L, 9L, 9L, 9L, 8L, 6L, 9L, 9L, 9L, 6L,
9L, 9L, 1L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 4L, 9L, 6L, 9L, 9L, 9L, 9L, 6L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 8L, 6L, 8L, 9L, 9L, 9L, 6L, 6L, 3L, 6L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 6L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 6L, 9L, 9L, 9L,
3L, NA, NA, NA, NA, NA, 6L, 6L, 6L, 9L, 6L, 6L, 9L, 3L, 3L,
3L, 3L, 3L, 7L, 6L, 6L, 8L, 3L, 1L, 3L, 6L, 8L, 9L, 9L, 9L,
6L, 9L, 7L, 5L, 3L, 12L, 3L, 3L, 3L, 8L, 9L, 9L, 9L, 9L,
6L, 8L, 7L, 12L, 6L, 6L, 6L, 6L, 7L, 6L, 6L, 6L, 6L, 7L,
6L, 9L, 9L, 6L, 9L, 12L, 6L, 6L, 9L, 9L, 9L, 9L, 9L, 9L,
6L, 9L, 8L, 8L, 9L, 11L, 3L, 3L, 9L, 9L, 3L, 9L, 9L, 9L,
6L, 6L, 7L, 10L, 7L, 9L, 10L, 4L, 9L, 6L, 8L, 8L, 9L, 8L,
8L, 3L, 8L, 1L, 4L, 6L, 1L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 8L,
8L, 3L, 8L, 8L, 8L, 8L, 8L, 3L, 8L, 8L, 8L, 2L, 8L, 7L, 3L,
3L, 3L, 3L, 9L, 9L, 9L, 9L, 2L, 6L, 6L, 4L, 6L, 6L, 9L, 9L,
6L, 8L, 6L, 6L, 6L, 9L, 9L, 6L, 6L, 9L, 9L, 9L, 9L, 9L, 6L,
9L, 9L, 9L, 9L, 9L, 8L, 8L, 9L, 9L, 7L, 9L, 9L, 6L, 5L, 9L,
9L, 6L, 9L, 8L, 4L, 9L, 9L, 6L, 12L, 9L, 9L, 9L, 4L, 6L,
6L, 9L, 9L, 6L, 6L, 6L, 9L, 6L, 6L, 9L, 9L, 9L, 1L), .Label = c("Adult Education",
"Junior Secondary", "Koranic", "NCE", "None", "Polytechnic",
"Senior Primary", "Senior Secondary", "University", "Junior Primary",
"Prelim / JMB", "Technical College"), class = "factor"),
district = c("Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Angwan Rimi", "Angwan Rimi", "Angwan Rimi", "Angwan Rimi",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa", "Barnawa",
"Barnawa", "Barnawa", "Barnawa", "Barnawa")), .Names = c("sex",
"education", "district"), row.names = c("1", "2", "3", "4", "5",
"6", "7", "9", "10", "11", "12", "13", "14", "15", "16", "17",
"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", "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", "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", "1361", "1371", "1381", "1391",
"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", "316", "317", "318", "319",
"320", "321", "322", "323", "324", "325", "326", "327", "328",
"329", "330", "331"), class = "data.frame")
这是此问题的解决方法,因为直接在一个ggplot2图中您无法组合躲避和堆叠.
对于这个图,我使用all_data了@DrewSteen回答的数据框 - 数据框应该包含所有District级别的值.
我们的想法是对的x轴组合绘制District和A8_HHH_hig.这是通过调用interaction()内部的函数实现的aes().然后将其转换为数字以确保稍后我们可以在我们想要的位置添加标签.为了fill=我们再次使用组合 - 现在sex和之间District.要获得x轴使用的标签scale_x_continuous()并将断点设置为2,4,6,...,26(两个相同教育水平的柱之间的值,最大值计算为A8_HHH_hig*级别的级别数Sex)并且标签提供的级别A8_HHH_hig.
ggplot(all_data,aes(as.numeric(interaction(District,A8_HHH_hig)),
fill=interaction(sex,District)))+
geom_bar(binwidth=1)+
theme(axis.text.x=element_text(angle=-45, hjust=0))+
scale_x_continuous("Education",breaks=seq(2,26,2),
labels=levels(all_data$A8_HHH_hig),expand=c(0,0.5),limits=c(1,27))+
scale_fill_discrete("",
labels=c("Female Angwan","Male Angwan","Female Barnawa","Male Barnawa"))
