我有一个日期格式为“%d-%m-%Y”的数据框,并具有星期数。日期是工作日,我希望在另一列中找到该周的星期六。
我最初使用Chron软件包中的函数检查日期是工作日还是周末,但这是布尔验证。我已经将date变量格式化为Date格式,并提取了每个日期的星期数。
df = data.frame(date=c("2014-08-20", "2014-08-25", "2014-10-08"))
df$date=as.Date(df$date,format="%Y-%m-%d")
df$week=week(ymd(df$date))
预期结果应该是:
date week EOW
2014-08-20 34 2014-08-23
2014-08-25 34 2014-08-30
2014-10-08 41 2014-10-11
答案 0 :(得分:3)
Base R选项。首先创建所有天数的列表,然后用match
weekdays
并将其从6中减去(如我们想要的星期六),以获取需要在原始date
列中添加的天数
all_days <- c("Monday","Tuesday","Wednesday","Thursday","Friday","Saturday","Sunday")
#As @nicola mentioned this is locale dependent
#If your locale is not English you need weekdays in your current locale
#which you can manually write as shown above or do any one of the following
#all_days <- weekdays(seq(as.Date("2019-01-14"),by="day",length.out=7))
#OR
#all_days <- format(seq(as.Date("2019-01-14"),by="day",length.out=7), "%A")
df$EOW <- df$date + 6 - match(weekdays(df$date), all_days)
df
# date week EOW
#1 2014-08-20 34 2014-08-23
#2 2014-08-25 34 2014-08-30
#3 2014-10-08 41 2014-10-11
或者lubridate
具有函数ceiling_date
,当与unit = "week"
一起使用时,它将返回下一个“星期日”,因此我们从中减去1天以获得“星期六”。
library(lubridate)
df$EOW <- ceiling_date(df$date, unit = "week") - 1
答案 1 :(得分:1)
使用
的另一种方法country_year
答案 2 :(得分:0)
使用data.table
连接语法:
library(data.table)
# Create a saturdays dataset
saturdays2014 <- data.table(date = seq(as.Date("2014-01-01"), as.Date("2014-12-31"), by = 1))
Sys.setlocale("LC_ALL","English")
saturdays2014 <- saturdays2014[weekdays(date) == "Saturday"]
# convert df to data.table and date to a Date variable
setDT(df)[, date := as.Date(date)]
# Join
df[saturdays2014, on = "date", roll = 6, EOW := i.date]
df
# date EOW
# 1: 2014-08-20 2014-08-23
# 2: 2014-08-25 2014-08-30
# 3: 2014-10-08 2014-10-11
答案 3 :(得分:-1)
优化代码。这是星期六。如果要在该周的星期四进行计算,请在计算中使用“ 5”而不是“ 7”。
library(lubridate)
library(dplyr)
df <- data.table(date=as.Date(c("2019-01-04","2019-01-07", "2019-01-15", "2019-01-26","2019-01-27")))
df %>% mutate(cw = wday(date)) %>%
mutate(nSaturday = date+(7-cw))
date cw nSaturday
1 2019-01-04 6 2019-01-05
2 2019-01-07 2 2019-01-12
3 2019-01-15 3 2019-01-19
4 2019-01-26 7 2019-01-26
5 2019-01-27 1 2019-02-02