[英]Applying same operation to several columns using tidyverse summarize
I'm trying to create a summary table that gives me the proportion of yes responses for 17 questions sorted by year.我正在尝试创建一个汇总表,该表为我提供按年份排序的 17 个问题的肯定回答比例。 I just don't know how to apply the summarize operation to multiple columns easily without hard-coding it.
我只是不知道如何在不对其进行硬编码的情况下轻松地将汇总操作应用于多个列。
Unfortunately, I can't use the summarize_at or summarize_all functions because I'm working with a dataframe.不幸的是,我不能使用 summarise_at 或 summarise_all 函数,因为我正在使用 dataframe。 I was thinking of writing a function, looping through the columns, and rbinding the summary columns together, but summarize is a bit weird with column names, which can't be of type character.
我正在考虑编写一个 function,遍历列,并将汇总列绑定在一起,但是汇总列名有点奇怪,不能是类型字符。 What do you recommend?
你有什么建议吗?
Here's what I currently have:这是我目前拥有的:
s2 <- db %>%
group_by(Year)%>%
summarize(Q1=round(sum(Q1d, na.rm=TRUE)*100/length(which(!is.na(Q1d))),1),
Q2=round(sum(Q2d, na.rm=TRUE)*100/length(which(!is.na(Q2d))),1),
Q3=round(sum(Q3d, na.rm=TRUE)*100/length(which(!is.na(Q3d))),1),
Q4=round(sum(Q4d, na.rm=TRUE)*100/length(which(!is.na(Q4d))),1),
Q5=round(sum(Q5d, na.rm=TRUE)*100/length(which(!is.na(Q5d))),1),
Q6=round(sum(Q6d, na.rm=TRUE)*100/length(which(!is.na(Q6d))),1),
Q7=round(sum(Q7d, na.rm=TRUE)*100/length(which(!is.na(Q7d))),1),
Q8=round(sum(Q8d, na.rm=TRUE)*100/length(which(!is.na(Q8d))),1),
Q9=round(sum(Q9d, na.rm=TRUE)*100/length(which(!is.na(Q9d))),1),
Q10=round(sum(Q10d, na.rm=TRUE)*100/length(which(!is.na(Q10d))),1),
Q11=round(sum(Q11d, na.rm=TRUE)*100/length(which(!is.na(Q11d))),1),
Q12=round(sum(Q12d, na.rm=TRUE)*100/length(which(!is.na(Q12d))),1),
Q13=round(sum(Q13d, na.rm=TRUE)*100/length(which(!is.na(Q13d))),1),
Q14=round(sum(Q14d, na.rm=TRUE)*100/length(which(!is.na(Q14d))),1),
Q15=round(sum(Q15d, na.rm=TRUE)*100/length(which(!is.na(Q15d))),1),
Q16=round(sum(Q16d, na.rm=TRUE)*100/length(which(!is.na(Q16d))),1),
Q17=round(sum(Q17d, na.rm=TRUE)*100/length(which(!is.na(Q17d))),1),
)
Note: Q1d, Q2d... are the names of the columns注意:Q1d, Q2d... 是列的名称
We can use across
in dplyr
我们可以
across
dplyr
中使用
library(dplyr)
library(stringr)
db %>%
group_by(Year) %>%
summarise(across(matches('^Q\\d+d$'), ~
sum(., na.rm = TRUE) * 100 /sum(!is.na(.))),
.groups = 'drop') %>%
rename_with(~ str_remove(., 'd$'), -Year)
or using collapse
或使用
collapse
library(collapse)
f1 <- function(x) sum(x, na.rm = TRUE) * 100/sum(!is.na(x))
collap(db, ~ Year, FUN = f1)
# Year Q1d Q2d
#1 2010 250.0000 350
#2 2015 293.3333 320
db <- data.frame(Year = c(2010, 2010, 2015, 2015, 2015, 2015),
Q1d = c(2.5, NA, 3, 3.5, NA, 2.3), Q2d = c(NA, 3.5, NA, 2, 4.6, 3))
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