此答案避免使用subset,处理缺失的观察结果并使用as.POSIXct 日期/时间格式。虽然,其余代码实际上与 Tyler Rinker 的答案相同。请注意,我必须在 as.POSIXct 中指定日期/时间变量的名称,而不是使用未格式化变量的名称 Date_Time。
my.data <- read.csv(text = '
Date_Time, state, city
10/05/2011 07:32:40, AK, aa
15/06/2011 13:26:02, AK, bb
19/07/2011 13:26:02, OH, cc
NA, OH, dd
20/05/2012 14:57:27, PA, ee
22/07/2012 14:57:27, AL, ff
20/03/2013 15:03:18, NY, gg
', header=TRUE, stringsAsFactors = FALSE, na.strings = 'NA', strip.white = TRUE)
my.data$my_Date_Time <- as.POSIXct(my.data$Date_Time, format = "%d/%m/%Y %H:%M:%S")
# Select May
my.data[format.Date(my.data$my_Date_Time, "%m")=="05" &
!is.na(my.data$my_Date_Time),]
# Date_Time state city my_Date_Time
# 1 10/05/2011 07:32:40 AK aa 2011-05-10 07:32:40
# 5 20/05/2012 14:57:27 PA ee 2012-05-20 14:57:27
# Select 2012
my.data[format.Date(my.data$my_Date_Time, "%Y")=="2012" &
!is.na(my.data$my_Date_Time),]
# Date_Time state city my_Date_Time
# 5 20/05/2012 14:57:27 PA ee 2012-05-20 14:57:27
# 6 22/07/2012 14:57:27 AL ff 2012-07-22 14:57:27
# Select May 2012
my.data[format.Date(my.data$my_Date_Time, "%m")=="05" &
format.Date(my.data$my_Date_Time, "%Y")=="2012" &
!is.na(my.data$my_Date_Time),]
# Date_Time state city my_Date_Time
# 5 20/05/2012 14:57:27 PA ee 2012-05-20 14:57:27