[英]How to get month/year/day of the week from different date formats in R
I have a data frame that contains a column call "date".我有一个包含列调用“日期”的数据框。 However the date formats are distinctively different.然而,日期格式明显不同。 Data type is string.数据类型为字符串。 I am trying to create "month" "year" and "day of the week" columns from this data column.我正在尝试从此数据列创建“月”、“年”和“星期几”列。
dataid date
1 Tue 11/3
2 Wed 11/4
3 N/A
4 Monday, February 1, 2016
5 Thursday, March 25, 2015
What is the best way to do this?做这个的最好方式是什么?
The robust way is to use lubridate::parse_date_time()
, but those dates witout year may be wrongly parsed (you may need to manually edit it).可靠的方法是使用lubridate::parse_date_time()
,但那些没有年份的日期可能会被错误解析(您可能需要手动编辑它)。
You may read "help("strptime")" to learn more about how to format orders to parse your date.您可以阅读“help("strptime")”以了解有关如何格式化订单以解析您的日期的更多信息。
ps March 25, 2015 is wednesday, not Thursday as in your example data. ps 2015 年 3 月 25 日是星期三,而不是示例数据中的星期四。
library(dplyr)
library(lubridate)
df <- data.table::fread(
"dataid date
1 'Tue 11/3'
2 'Wed 11/4'
3 'N/A'
4 'Monday, February 1, 2016'
5 'Thursday, March 25, 2015'
",quote="\'")
df.new <- df %>%
mutate(
date2 =lubridate::parse_date_time(x =date, orders = c("%a %m/%d", "%A, %B %d, %Y"))
)
#> Warning: 1 failed to parse.
df.new
#> dataid date date2
#> 1 1 Tue 11/3 2018-11-03
#> 2 2 Wed 11/4 2018-11-04
#> 3 3 N/A <NA>
#> 4 4 Monday, February 1, 2016 2016-02-01
#> 5 5 Thursday, March 25, 2015 2015-03-25
Created on 2018-10-08 by the reprex package (v0.2.1)由reprex 包(v0.2.1) 于 2018 年 10 月 8 日创建
from there you can extract year, month, day of week like this:从那里你可以像这样提取年、月、星期几:
df.new %>%
mutate(
year = lubridate::year(date2),
month = lubridate::month(date2),
day_of_week = weekdays(date2)
)
# dataid date date2 year month day_of_week
#1 1 Tue 11/3 2018-11-03 2018 11 Saturday
#2 2 Wed 11/4 2018-11-04 2018 11 Sunday
#3 3 N/A <NA> NA NA <NA>
#4 4 Monday, February 1, 2016 2016-02-01 2016 2 Monday
#5 5 Thursday, March 25, 2015 2015-03-25 2015 3 Wednesday
If the day and month are written as characters, then regular expressions can be used within a dplyr::case_when()
call:如果将日期和月份写为字符,则可以在dplyr::case_when()
调用中使用正则表达式:
library(dplyr)
df <- df %>%
mutate(
day_of_the_week = case_when(
grepl("mon", date, ignore.case = T) ~ "mon",
grepl("tue", date, ignore.case = T) ~ "tues",
grepl("wed", date, ignore.case = T) ~ "wed",
grepl("thu", date, ignore.case = T) ~ "thurs",
grepl("fri", date, ignore.case = T) ~ "fri",
grepl("sat", date, ignore.case = T) ~ "sat",
grepl("sun", date, ignore.case = T) ~ "sun",
T ~ NA_character_
),
month = case_when(
grepl("jan", date, ignore.case = T) ~ "jan",
grepl("feb", date, ignore.case = T) ~ "feb",
grepl("mar", date, ignore.case = T) ~ "mar",
grepl("apr", date, ignore.case = T) ~ "apr",
grepl("may", date, ignore.case = T) ~ "may",
grepl("jun", date, ignore.case = T) ~ "jun",
grepl("jul", date, ignore.case = T) ~ "jul",
grepl("aug", date, ignore.case = T) ~ "aug",
grepl("sep", date, ignore.case = T) ~ "sep",
grepl("oct", date, ignore.case = T) ~ "oct",
grepl("nov", date, ignore.case = T) ~ "nov",
grepl("dec", date, ignore.case = T) ~ "dec",
T ~ NA_character_
)
)
# dataid date day_of_the_week month
# 1 1 Tue 11/3 tues <NA>
# 2 2 Wed 11/4 wed <NA>
# 3 3 <NA> <NA> <NA>
# 4 4 Monday, February 1, 2016 mon feb
# 5 5 Thursday, March 25, 2015 thurs mar
It's a harder to pull out day/month number (you could possibly do it in a similar way for days of month between 13 and 31, but otherwise it's impossible to know if the number is for the day or month).提取日/月数比较困难(您可以在 13 到 31 之间的月份中以类似的方式执行此操作,否则就不可能知道该数字是当天还是月份)。
df <- read.table(text = "
dataid date
1 'Tue 11/3'
2 'Wed 11/4'
3 N/A
4 'Monday, February 1, 2016'
5 'Thursday, March 25, 2015'",
header = T,
stringsAsFactors = F,
na.strings = "N/A")
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