> On Nov 24, 2017, at 3:35 PM, Allaisone 1 wrote:
>
> Thank you for clarifying this point but my main question was about how to
> modify my code to do the analysis correctly.
You need to first clarify what your proposed statistical hypothesis might be.
If you are doing prop.test on 300 column
I have a returned tibble of station operational record similar to the following:
> data.collection
# A tibble: 5 x 4
STATION_NUMBER YEAR_FROM YEAR_TO RECORD
107EA001 19601960QMS
207EA001 19611970QMC
307EA001 1971197
dplyr may have something for this, but in base R I think the following does
what you want. I've shortened the name of your data set to 'd'.
i <- rep(seq_len(nrow(d)), d$YEAR_TO-d$YEAR_FROM+1)
j <- sequence(d$YEAR_TO-d$YEAR_FROM+1)
transform(d[i,], YEAR=YEAR_FROM+j-1, YEAR_FROM=NULL, YEAR_TO=NULL)
Hi
On 11/23/2017 10:04 AM, Stefano Sofia wrote:
Thank you Sarah and Mike for your explanations. My final objective is
to produce maps (png image or any kind of extension I can import in
LaTeX) where rainfall data are interpolated, using the Inverse
Distance method or Kriging. My input file (po
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