按组计算非 NA 值 [英] Count non-NA values by group

问题描述

这是我的例子

mydf<-data.frame('col_1' = c('A','A','B','B'), 'col_2' = c(100,NA, 90,30))

我想按 col_1 分组并计算 col_2

I would like to group by col_1 and count non-NA elements in col_2

我想用 dplyr 来做.这是我尝试过的:

I would like to do it with dplyr. Here is what I tried:

mydf %>% group_by(col_1) %>% summarise_each(funs(!is.na(col_2)))
mydf %>% group_by(col_1) %>% mutate(non_na_count = length(col_2, na.rm=TRUE))
mydf %>% group_by(col_1) %>% mutate(non_na_count = count(col_2, na.rm=TRUE))

没有任何效果.有什么建议吗?

Nothing worked. Any suggestions?

推荐答案

你可以使用这个

mydf %>% group_by(col_1) %>% summarise(non_na_count = sum(!is.na(col_2)))

# A tibble: 2 x 2
   col_1 non_na_count
  <fctr>        <int>
1      A            1
2      B            2

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