Missing_Values = data.frame(colSums(is.na(train)))
Missing_Values_per = data.frame(colMeans(is.na(train))) * 100
data.frame(Column_Name = names(train))
我需要使用这三个变量创建数据框,有人可以帮忙吗
答案 0 :(得分:0)
尝试一下:
library(tidyverse)
train <- tibble(a = c(NA, 1, 4, NA, NA),
b = c(6, NA, NA, NA, NA))
train %>%
gather(column_name, v) %>%
group_by(column_name) %>%
summarize(missing_values = sum(is.na(v)),
missing_values_per = mean(is.na(v)) * 100)