问题
I am now learning R and using the SEAS package to help me with some calculation in R and data is the same format as SEAS package likes. It is a time series
require(seas)
data(mscdata)
dat.int <- (mksub(mscdata, id=1108447))
the heading of the data and it is 20 years of data
year yday date t_max t_min t_mean rain snow precip
However, I now need to calculate the number of days in each month rainfall is >= 1.0mm . So at the end of it. I would have two columns ( each month in each year and total # of days in each month rainfall>= 1.0mm )
I'm not certain how to write this code and any help would be appreciated
Thank you
Lam
回答1:
I now need to calculate the number of days in each month rainfall is >= 1.0mm. So at the end of it. I would have two columns ( each month in each year and total # of days in each month rainfall>= 1.0mm )
1) So dat.int$date is a Date object. First step is you need to create a new column dat.int$yearmon
extracting the year-month, e.g. using zoo::yearmon
Extract month and year from a zoo::yearmon object
require(zoo)
dat.int$yearmon <- as.yearmon(dat.int$date, "%b %y")
2) Second, you need to do a summarize operation (recommend you use plyr or the newer dplyr) on rain>=1.0
aggregated by yearmon. Let's name our resulting column rainy_days.
If you want to store rainy_days column back into the dat.int
dataframe, you use a transform
instead of a summarize
:
ddply(dat.int, .(yearmon), transform, rainy_days=sum(rain >= 1.0) )
or else if you really just want a new summary dataframe:
require(plyr)
rainydays_by_yearmon <- ddply(dat.int, .(yearmon), summarize, rainy_days=sum(rain >= 1.0) )
print.data.frame(rainydays_by_yearmon)
yearmon rainy_days
1 Jan 1975 14
2 Feb 1975 12
3 Mar 1975 13
4 Apr 1975 6
5 May 1975 6
6 Jun 1975 5
...
355 Jul 2004 3
356 Aug 2004 7
357 Oct 2004 14
358 Nov 2004 16
359 Dec 2004 19
Note: you can do the above with plain old R, without using zoo
or plyr/dplyr
packages. But might as well teach you nicer, more scalable, maintainable code idioms.
来源:https://stackoverflow.com/questions/26473724/aggregate-count-of-timeseries-values-which-exceed-threshold-by-year-month