cut
cut breaks a vector x into factors specified by the argument breaks. cut is particularly useful to break Date data into categories like "Q1", "Q2", or 1998, 1999, 2000, etc.
You can find more useful information by running ?cut.POSIXt.
Examples
How can I create a new column in a data.frame df that is a factor based on the year?
Click to see solution
df$year <- cut(df$times, breaks="year")
str(df)'data.frame': 24 obs. of 3 variables:
$ times: POSIXct, format: "2020-06-01 06:00:00" "2020-07-01 06:00:00" ...
$ value: int 48 62 55 4 83 77 5 53 68 46 ...
$ year : Factor w/ 3 levels "2020-01-01","2021-01-01",..: 1 1 1 1 1 1 1 2 2 2 ...How can I create a new column in a data.frame df that is a factor based on the quarter?
Click to see solution
df$quarter <- cut(df$times, breaks="quarter")
str(df)'data.frame': 24 obs. of 4 variables:
$ times : POSIXct, format: "2020-06-01 06:00:00" "2020-07-01 06:00:00" ...
$ value : int 48 62 55 4 83 77 5 53 68 46 ...
$ year : Factor w/ 3 levels "2020-01-01","2021-01-01",..: 1 1 1 1 1 1 1 2 2 2 ...
$ quarter: Factor w/ 9 levels "2020-04-01","2020-07-01",..: 1 2 2 2 3 3 3 4 4 4 ...How can I create a new column in a data.frame df that is a factor based on every 2 weeks?
Click to see solution
df$biweekly <- cut(df$times, breaks="2 weeks")For an example with the 7581 data set:
myDF <- read.csv("/depot/datamine/data/fars/7581.csv")These are the values of the HOUR column:
table(myDF$HOUR)0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 17704 18671 17262 9908 6438 5463 6749 7088 6308 6275 7311 8401 8929 9872 12066 14138
We can break these values into 6-hour intervals:
table( cut(myDF$HOUR, breaks=c(0,6,12,18,24,99), include.lowest=T) )[0,6] (6,12] (12,18] (18,24] (24,99] 82195 44312 85388 86567 1597
We can then find the total number of PERSONS who are involved in accidents during each 6-hour interval
tapply( myDF$PERSONS, cut(myDF$HOUR, breaks=c(0,6,12,18,24,99), include.lowest=T), sum )[0,6] (6,12] (12,18] (18,24] (24,99] 187397 119261 238193 230289 2269