【发布时间】:2020-10-19 11:39:43
【问题描述】:
为了简单起见,我创建了小型虚拟数据集。
library(tidyverse)
library(lubridate)
myDF <- tibble(country = rep(c("UK", "US"), each = 3),
date = c("2020-01-01", "2020-02-01", "2020-02-01", "2020-03-01",
"2020-03-01", "2020-03-01"))
myDF <- myDF %>% mutate(date = as_date(date))
country date
<chr> <date>
1 UK 2020-01-01
2 UK 2020-02-01
3 UK 2020-02-01
4 US 2020-03-01
5 US 2020-03-01
6 US 2020-03-01
我知道可以使用 unique() 函数查找日期列中有 3 个唯一值(“2020-01-01”、“2020-02-01”、“2020-03-01”) .
unique(myDF$date) # the unique values
length(unique(myDF$date)) # number of unique values
但是如何创建一个小表格输出,以显示数据集中特定列(即日期)中每个独特事件的频率?我正在寻找这样的东西:
myDF$date freq
"2020-01-01" 1
"2020-02-01" 2
"2020-03-01" 3
【问题讨论】:
-
示例代码:myDF %>% count(date, name = 'freq')
-
myDF %>% group_by(date) %>% summarise(n = n()) %>% ungroup()