steve_fried...@nps.gov wrote:
My data contains a variable "observation_date" and it contains values as:
1985-09-02
1985-09-15
1985-07-31
1985-09-02
I need to process data annually rather than daily, therefore I'm trying to
1) either extract the first 4 digits from this field and use them as a new
variable "year"
year <- as.numeric(format((strptime(observation_date, "%Y-%m-%d")), "%Y"))
or
year <- as.numeric(substr(observation_date, 1, 4))
Uwe Ligges
or 2) keep the variable as it is and process the analysis
using the first 4 digits of the observation_date field.
I'm not sure how to do either one of these approaches. I've looked in the
R-archive help pages, date, strsplit and a few others
attach(gator)
observation_date[1:10]
[1] 1985-09-02 1985-09-16 1985-07-31 1985-07-31 1985-09-02 1985-08-26
1985-07-31 1985-08-26 1985-09-02 1985-09-16
as.date(observation_date)
Error in as.date(observation_date) : Cannot coerce to date format
mode(observation_date)
"numeric"
y <- as.character(observation_date)
[1] "1985-09-02" "1985-09-16" "1985-07-31" "1985-07-31" "1985-09-02"
"1985-08-26" "1985-07-31" "1985-08-26" "1985-09-02" "1985-09-16"
< y.date <- as.date(y)
[1] <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> on and on
and on ...
x <- strsplit(observation_date, "-")
Error in strsplit(observation_date, "-") : non-character argument
All help is greatly appreciated.
Thanks
Steve
Steve Friedman Ph. D.
Spatial Statistical Analyst
Everglades and Dry Tortugas National Park
950 N Krome Ave (3rd Floor)
Homestead, Florida 33034
steve_fried...@nps.gov
Office (305) 224 - 4282
Fax (305) 224 - 4147
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and provide commented, minimal, self-contained, reproducible code.
