I have gridded data files ( see sample -each file consist of monthly precip and is label pYYYYMM) https://www.dropbox.com/sh/63z166tjxyu12s5/AAAs3Ccn1zdVoBYMj8Y1o303a?dl=0.
I am trying to extract the point data for each territories of Canada and so that i can get a time series for each lat and longitude within the dataset
library(raster) files= list.files( ,pattern='*.grd',full.names=TRUE) s <- stack(files) # Setting Missing values s[s >= 170141000918782798866653488190622531584.00] <- NA_real_ # read in my point of interest, pt<- read.csv("latandlong")
This data is available https://www.dropbox.com/s/3p4u4pyxkyo2q15/latandlong.csv?dl=0
# Setting the data points to spatial value using the first two columns point <- SpatialPoints(pt) df1 <- extract(s, point, df=TRUE,method='simple') write.csv(df1, 'precip.csv') str(df1) data.frame': 409 obs. of 1922 variables: $ ID : num 1 2 3 4 5 6 7 8 9 10 ... $ t190001: num -18.8 -19.6 -20.2 -20.8 -21.9 ... $ t190002: num -23 -23.4 -23.8 -24.8 -25.6 ... $ t190003: num -14 -14.4 -14.5 -15.3 -15.9 ...
When I run the extract function advised by RobertH, this work but I just need one final step. I also need the corresponding x-y values and lat / lat coordinates to be included in my dataframe as well or is there any way to extract data for each territories directly for each point.