问题
I'm working with a data set corresponding to the extract:
set.seed(1)
df <- data.frame(indicator=runif(n = 100),cohort=letters[1:4],
year=rep(1976:2000, each=4))
I would like to generate a variable with percentage year-on-year change for each cohort represented in the data set. I have tried to use the code below (from this discussion):
df$ind_per_chng <- transform(new.col=c(NA,indicator[-1]/indicator[-nrow(df)]-1))
but I'm interested in making it work within each subgroup and generating only one extra column with percentage change instead of set of columns that are presently created:
> head(df)
indicator cohort year ind_per_chng.indicator ind_per_chng.cohort ind_per_chng.year
1 0.2655087 a 1976 0.2655087 a 1976
2 0.3721239 b 1976 0.3721239 b 1976
3 0.5728534 c 1976 0.5728534 c 1976
4 0.9082078 d 1976 0.9082078 d 1976
5 0.2016819 a 1977 0.2016819 a 1977
6 0.8983897 b 1977 0.8983897 b 1977
ind_per_chng.new.col
1 NA
2 0.4015509
3 0.5394157
4 0.5854106
5 -0.7779342
6 3.4544877
Edit
To answer the useful comments, the format of the output should correspond to the table below:
There are no other changes to original data.frame with exception of the column that provides value for the percentage change for the selected variable for each cohort across years.
回答1:
I'm not sure I'm correctly understanding what you want the output to look like, but is that what you're after?
library(dplyr)
df2 <- df%>%
group_by(cohort) %>%
arrange(year) %>%
mutate(pct.chg = (indicator - lag(indicator))/lag(indicator))
If you want your percentages on a 0-100 scale instead of 0-1, add 100 * () to that last line, so mutate(pct.chg = 100 * ((indicator - lag(indicator))/lag(indicator))). Here's what the result looks like:
indicator cohort year pct.chg
1 0.2655087 a 1976 NA
2 0.2016819 a 1977 -24.039416
3 0.6291140 a 1978 211.933767
4 0.6870228 a 1979 9.204818
5 0.7176185 a 1980 4.453369
6 0.9347052 a 1981 30.250993
来源:https://stackoverflow.com/questions/31812864/obtaining-year-on-year-percentage-change-by-group