I have data that looks like this:
> data1415$Lön_utv
[1] 2.500000 2.499134 11.979167 2.606635 2.299856 2.300086 2.399993 2.499763 2.499134 5.000000
[11] 2.499134 3.213068 3.497202 6.666667 3.467406 2.493373 3.976479 2.501996 2.499356 3.286318
[21] 2.503582 2.503582 2.499356 2.499356 2.499356 2.499356 2.459016 2.505516 2.499356 2.504103
[31] 2.503582 2.459016 2.503582 2.544523 5.660377 2.501949 2.503966 2.499332 2.358491 3.113852
[41] 2.499356 2.499332 2.499356 2.459016 2.499332 2.941176 2.499356 2.499356 2.499356 2.499356
[51] 3.400695 6.512312 2.504863 2.499356 2.499356 6.516168 2.503966 2.503582 3.400695 2.358491
[61] 3.899955 7.525569 2.503582 2.499236 2.283105 2.499332 2.941176 2.499356 2.503582 6.335204
[71] 5.216359 2.501495 5.936073 2.503966 2.358491 7.152135 6.072188 2.502615 6.063219 10.193115
[81] 2.504279 2.503582 2.501231 2.505728 2.500144 3.658113 2.502452 2.941176 5.000000 2.500818
[91] 2.499236 8.054799 2.500144 1.672703 2.941176 2.162162 6.072188 2.941176 3.251276 2.941176
[101] 2.501231 2.500818 7.397407 2.162162 4.860217 2.941176 2.162162 2.162162 2.162162 2.501361
If I cut the data I get this:
> c2 <- cut(data1415$Lön_utv, breaks = c(0:8, 20), include.lowest=TRUE)
> table(c2)
c2
[0,1] (1,2] (2,3] (3,4] (4,5] (5,6] (6,7] (7,8] (8,20]
0 1 79 11 1 5 7 3 3
I want to create a histogram with bins 0-1, 1-2, 2-3 and so forth. My problem is I want the x-axis to be no wider than say about 8. That would exclude all values above 8 so I would like the rightmost bin to include all values above 8. I´ve tried something like
hist(data1415$Lön_utv, breaks = c(0:8, 20), right=FALSE)
But can´t figure out how to make the x-axis no longer than 8 and still get a "top" bin with all values above.
As said in the comments, you need a barplot for this using bins. Assuming that our numerical variable is in 'value', we can calculate the bins:
dat$bin <- cut(dat$value, breaks=c(0:8,20))
Then using ggplot, we can plot the counts:
ggplot(dat, aes(x=bin)) + geom_bar()
To get percentages, we can have ggplot calculate those for us. We do need to add a percentage scale to it. And to avoid confusion, have the axis go from 0 to 100%.
ggplot(dat, aes(x=bin)) +
geom_bar(aes(y=..count../sum(..count..))) +
scale_y_continuous(limits=c(0,1),labels=scales::percent)