I am making a histogram of data with ggplot2. I am using facet_grid with two discrete variables, all combinations of which exist in the data. I would like to show percentages on the y-axis (in this particular case this is what is required, even though there are good arguments for using density). I initially posted this question but have added additional variables and changed my approach, and I would now prefer to use ggplot2.
I have binned the data outside ggplot2 and used geom_bar. This is the approach described in the second answer to the following question - i.e. the answer by the OP, Feng Mai:
Let ggplot2 histogram show classwise percentages on y axis
(I also tried the approach described in the accepted answer to the above question, which is by Rorschach. However, ns for each graph still appeared to be calculated based on the total number of participants rather than classwise. For now I have made greater headway with binning).
My problem is that I end up with unexpected results on the x-axis (see reprex below):
The x-axis is overwritten several times. I think this is because an x-axis is being produced for every level of the variable Profile, but I am not sure how to stop this happening.
The x-axis shows the brackets produced by the cut function. Perhaps this is related to the first problem, perhaps not. EDIT: I was expecting an x-axis showing 1-100 underneath each column, rather than an x-axis showing bins with brackets. User Feng Mai seems to have achieved this in the question that I linked above.
I would be very grateful for advice on fixing these problems.
library(tidyverse)
library(ggplot2)
library(scales)
d <- data.frame(
n = c(1L,7L,8L,17L,31L,24L,13L,16L,
14L,14L,17L,19L,14L,4L,1L,2L,15L,18L,13L,14L,17L,
6L,10L,4L,3L,1L,3L,5L,6L,22L,24L,21L,10L,4L,
6L,5L,8L,29L,17L,34L,8L,9L,3L,5L,19L,16L,20L,4L,
1L,9L,14L,35L,1L,3L,5L,32L,33L,17L,44L,23L,11L,
9L,4L,4L,4L,5L,11L,17L,14L,16L,11L,6L,3L,2L,
15L,32L,42L),
freq = c(0.0099009900990099,
0.0693069306930693,0.0792079207920792,0.168316831683168,0.306930693069307,
0.237623762376238,0.128712871287129,0.158415841584158,
0.138613861386139,0.138613861386139,0.168316831683168,
0.188118811881188,0.138613861386139,0.0396039603960396,
0.0099009900990099,0.0198019801980198,0.148514851485149,
0.178217821782178,0.128712871287129,0.138613861386139,
0.168316831683168,0.0594059405940594,0.099009900990099,
0.0396039603960396,0.0297029702970297,0.0099009900990099,
0.0297029702970297,0.0495049504950495,0.0594059405940594,
0.217821782178218,0.237623762376238,0.207920792079208,
0.099009900990099,0.0396039603960396,0.0594059405940594,
0.0847457627118644,0.135593220338983,0.491525423728814,0.288135593220339,
0.576271186440678,0.135593220338983,0.152542372881356,
0.0508474576271186,0.0847457627118644,0.322033898305085,
0.271186440677966,0.338983050847458,0.0677966101694915,
0.0169491525423729,0.152542372881356,0.23728813559322,
0.593220338983051,0.010989010989011,0.032967032967033,
0.0549450549450549,0.351648351648352,0.362637362637363,
0.186813186813187,0.483516483516484,0.252747252747253,0.120879120879121,
0.0989010989010989,0.043956043956044,0.043956043956044,
0.043956043956044,0.0549450549450549,0.120879120879121,
0.186813186813187,0.153846153846154,0.175824175824176,
0.120879120879121,0.0659340659340659,0.032967032967033,
0.021978021978022,0.164835164835165,0.351648351648352,
0.461538461538462),
Profile = as.factor(c("1","1","1",
"1","1","1","1","1","1","1","1","1","1",
"1","1","1","1","1","1","1","1","1","1",
"1","1","1","1","1","1","1","1","1","1",
"1","1","2","2","2","2","2","2","2","2",
"2","2","2","2","2","2","2","2","2","3",
"3","3","3","3","3","3","3","3","3","3",
"3","3","3","3","3","3","3","3","3","3",
"3","3","3","3")),
TimeFactor = as.factor(c("FactorScoreO",
"FactorScoreO","FactorScoreO","FactorScoreO",
"FactorScoreO","FactorScoreO","FactorScoreO",
"FactorScoreM","FactorScoreM","FactorScoreM",
"FactorScoreM","FactorScoreM","FactorScoreM",
"FactorScoreM","FactorScoreM","FactorScoreM",
"FactorScoreP","FactorScoreP","FactorScoreP",
"FactorScoreP","FactorScoreP","FactorScoreP","FactorScoreP",
"FactorScoreP","FactorScoreP","FactorScoreP",
"FactorScoreD","FactorScoreD","FactorScoreD",
"FactorScoreD","FactorScoreD","FactorScoreD",
"FactorScoreD","FactorScoreD","FactorScoreD",
"FactorScoreO","FactorScoreO","FactorScoreO",
"FactorScoreO","FactorScoreM","FactorScoreM",
"FactorScoreM","FactorScoreM","FactorScoreM",
"FactorScoreP","FactorScoreP","FactorScoreP","FactorScoreP",
"FactorScoreD","FactorScoreD","FactorScoreD",
"FactorScoreD","FactorScoreO","FactorScoreO",
"FactorScoreO","FactorScoreO","FactorScoreO",
"FactorScoreO","FactorScoreM","FactorScoreM",
"FactorScoreM","FactorScoreM","FactorScoreM",
"FactorScoreP","FactorScoreP","FactorScoreP",
"FactorScoreP","FactorScoreP","FactorScoreP",
"FactorScoreP","FactorScoreP","FactorScoreP","FactorScoreP",
"FactorScoreD","FactorScoreD","FactorScoreD",
"FactorScoreD")),
score_cut = as.factor(c("(20,30]",
"(40,50]","(50,60]","(60,70]","(70,80]","(80,90]",
"(90,100]","[0,10]","(10,20]","(20,30]",
"(30,40]","(40,50]","(50,60]","(60,70]","(70,80]",
"(80,90]","[0,10]","(10,20]","(20,30]","(30,40]",
"(40,50]","(50,60]","(60,70]","(70,80]",
"(80,90]","(90,100]","(10,20]","(20,30]","(30,40]",
"(40,50]","(50,60]","(60,70]","(70,80]",
"(80,90]","(90,100]","(60,70]","(70,80]","(80,90]",
"(90,100]","[0,10]","(10,20]","(20,30]",
"(30,40]","(40,50]","[0,10]","(10,20]","(20,30]",
"(30,40]","(60,70]","(70,80]","(80,90]",
"(90,100]","(40,50]","(50,60]","(60,70]","(70,80]",
"(80,90]","(90,100]","[0,10]","(10,20]",
"(20,30]","(30,40]","(40,50]","[0,10]","(10,20]",
"(20,30]","(30,40]","(40,50]","(50,60]",
"(60,70]","(70,80]","(80,90]","(90,100]","(60,70]",
"(70,80]","(80,90]","(90,100]"))
)
hist <- ggplot(d, aes(x = score_cut, y = freq*100, fill=Profile)) +
geom_bar (stat="identity", position="dodge") +
xlab("Raw unweighted factor score") + ylab("Percentage of participants") +
theme_bw()+
facet_grid(vars(TimeFactor), vars(Profile)) +
theme(panel.grid.major = element_blank()) +
scale_fill_manual(values=c("#56B4E9", "#E69F00", "#999999"))
hist
Created on 2021-04-30 by the reprex package (v0.3.0)
