问题
I'm working with a dataset in R where the main area of interest is the date. (It has to do with army skirmishes and the date of the skirmish is recorded). I wanted to check if these were more likely to happen in a given season, or near a holiday, etc, so I want to be able to see how many dates there are in the summer, winter, etc but I'm sort of at a loss for how to do that.
回答1:
A general recommendation: use the package lubridate
for converting from strings to dates if you're having trouble with that. use cut()
to divide dates into ranges, like so:
someDates <- c( '1-1-2013',
'2-14-2013',
'3-5-2013',
'8-21-2013',
'9-15-2013',
'11-28-2013',
'12-22-2013')
cutpoints<- c('1-1-2013',# star of range 'winter'
'3-20-2013',# spring
'6-21-2013',# summer
'9-23-2013',# fall
'12-21-2013',# winter
'1-1-2014')# end of range
library(lubridate)
temp <- cut(mdy(someDates),
mdy(cutpoints),
labels=FALSE)
someSeasons <- c('winter',
'spring',
'summer',
'fall',
'winter')[temp]
Now use 'someSeasons' to group your data into date ranges with your favorite statistical analysis. For a choice of statistical analysis, poisson regression adjusting for exposure (i.e. length of the season), comes to mind, but that is probably a better question for Cross Validated
You can make a vector of cut points with regular intervals like so:
cutpoints<- c('3-20-2013',# spring
'6-21-2013',# summer
'9-23-2013',# fall
'12-21-2013')# winter
temp <- cut(mdy(someDates),
outer(mdy(cutpoints), years(1:5),`+`),
labels=F)
someSeasons <- c('spring',
'summer',
'fall',
'winter')[(temp-1)%% 4 + 1] #the index is just a little tricky...
来源:https://stackoverflow.com/questions/28662110/categorizing-date-in-r