I have a dataframe like this:
| Year | Net | Cost | Gross |
|---|---|---|---|
| 2010 | 5637 | 6749 | 6849 |
| 2011 | 5738 | 2810 | 5749 |
| 2012 | 4829 | 5738 | 5783 |
| 2013 | 9587 | 6749 | 5739 |
| 2014 | 4638 | 6739 | 6748 |
I want column wise percerntages for each year:
| Year | Net | Cost | Gross |
|---|---|---|---|
| 2010 | XX% | XX% | XX% |
| 2011 | XX% | XX% | XX% |
| 2012 | XX% | XX% | XX% |
| 2013 | XX% | XX% | XX% |
| 2014 | XX% | XX% | XX% |
These percentages are column wise percentages. I coded as this:
percent = prop.table(as.matrix(test[2:4]), margin=2)
But I do not get the Year column. Please help!
CodePudding user response：
We could use mutate with across
library(dplyr)
test %>%
mutate(round(100 *across(2:4, proportions), 2))
-output
Year Net Cost Gross
1 2010 18.53 23.45 22.19
2 2011 18.86 9.76 18.62
3 2012 15.87 19.93 18.73
4 2013 31.51 23.45 18.59
5 2014 15.24 23.41 21.86
With the OP's code, we could cbind with the first column
cbind(test[1], prop.table(as.matrix(test[2:4]), margin=2))
data
test <- structure(list(Year = 2010:2014, Net = c(5637L, 5738L, 4829L,
9587L, 4638L), Cost = c(6749L, 2810L, 5738L, 6749L, 6739L), Gross = c(6849L,
5749L, 5783L, 5739L, 6748L)), class = "data.frame", row.names = c(NA,
-5L))
CodePudding user response：
Solution with bind_cols:
percent <- test[1] %>% bind_cols(as.data.frame(prop.table(as.matrix(test[2:4]), margin=2)))