Drawing multiple barplots on a graph using data with different size - r

Question

I can plot multiple bar plots on one plot with following code (taken from this question):
mydata <- data.frame(Barplot1=rbinom(5,16,0.6), Barplot2=rbinom(5,16,0.25),
Barplot3=rbinom(5,5,0.25), Barplot4=rbinom(5,16,0.7))
barplot(as.matrix(mydata), main="Interesting", ylab="Total", beside=TRUE,
col=terrain.colors(5))
legend(13, 12, c("Label1","Label2","Label3","Label4","Label5"), cex=0.6,
fill=terrain.colors(5))
But my scenario is a bit different: I have data stored in 3 data.frames (sorted according to V2 column) where V1 column is the Y axis and V2 column is the X axis:
> tail(hist1)
V1 V2
67 2 70
68 2 72
69 1 73
70 2 74
71 1 76
72 1 84
> tail(hist2)
V1 V2
87 1 92
88 3 94
89 1 95
90 2 96
91 1 104
92 1 112
> tail(hist3)
V1 V2
103 3 110
104 1 111
105 2 112
106 2 118
107 2 120
108 1 138
For plotting one single plot it is just simple as:
barplot(hist3$V1, main="plot title", names.arg = hist3$V2)
But I cannot construct the matrix needed for plot because of several problems that I can see right now (maybe there are several others):
My data has different size:
> nrow(hist1)
[1] 72
> nrow(hist2)
[1] 92
> nrow(hist3)
[1] 108
There are X (and therefore Y also) values which are in one list but not in another list e.g.:
> hist3$V2[which(hist3$V2==138)]
[1] 138
> hist1$V2[which(hist1$V2==138)]
integer(0)
What I need (I guess) is something that will create appropriate V2 (x axis) with 0 Y value in appropriate data.frame so they will have same length and I will be able combine them as above example. See following example with only 2 data.frames (v2 and v1 are reversed as in previous example):
> # missing v2 for 3,4,5
> df1
v2 v1
1 1 1
2 2 2
3 6 3
4 7 4
5 8 5
6 9 6
7 10 7
> # missing v2 for 1,2,9,10
> df2
v2 v1
1 3 1
2 4 2
3 5 3
4 6 4
5 7 5
6 8 6
> # some_magic_goes_here ...
> df1
v2 v1
1 1 1
2 2 2
3 3 0 # created
4 4 0 # created
5 5 0 # created
6 6 3
7 7 4
8 8 5
9 9 6
10 10 7
> df2
v2 v1
1 1 0 # created
2 2 0 # created
3 3 1
4 4 2
5 5 3
6 6 4
7 7 5
8 8 6
9 9 0 # created
10 10 0 # created
Thanks

Answer 1

Probably, you can do this by 1) retrieving all possible x-axis values (v2 values) from all data.frames. and 2) using this information to retrieve existing values and/or filling missing ones with zeroes.
set.seed(111)
df1 <- data.frame(v2= sample(1:10, size = 7),
v1 = sample(1:100, size = 1))
df2 <- data.frame(v2= sample(1:10, size = 7),
v1 = sample(1:100, size = 1))
df3 <- data.frame(v2= sample(1:10, size = 7),
v1 = sample(1:100, size = 1))
First, retrieve your categories / x-axis values / v2
Note that if class(df1$v2) == "factor", then you should use levels() instead of unique()
my.x <- unique(c(df1$v2, df2$v2, df3$v2))
Likely, you want it sorted
my.x <- sort(my.x)
Now, use my.x to re-order/fill your data.frames, starting with df1. Specifically, you check each value of my.x: if that value is included in df1$v2, then the corresponding v1 is returned, otherwise 0.
my.df1 <- data.frame(v2 = my.x,
v1 = sapply(my.x, (function(i){
ifelse (i %in% df1$v2, df1$v1[df1$v2 == i], 0)
})))
my.df1
A simple way to apply this operation to all your data.frames is to list them together and then use lapply()
dfs <- list(df1 = df1, df2 = df2, df3 = df3)
dfs <- lapply(dfs, (function(df){
data.frame(v2 = my.x,
v1 = sapply(my.x, (function(i){
ifelse (i %in% df$v2, df$v1[df$v2 == i], 0)
})))
}))
# show all data.frames
dfs
# show df1
dfs$df1