I'm usign two dataframes that contain coordinates (x,y) and a value for precipitation, since I'm trying to plot maps for the distribution od the rainfall in a certain area.
The contents of my datadrames are the following
head(cruproc,n=10)
x y value
1 -97.75 15.75 0.1354839
2 -97.25 15.75 0.1419355
3 -96.75 15.75 0.0000000
4 -96.25 15.75 0.0000000
5 -95.75 15.75 0.1580645
6 -93.75 15.75 0.2129032
7 -93.25 15.75 0.1096774
8 -92.75 15.75 0.1419355
9 -92.25 15.75 0.4322581
10 -91.75 15.75 0.8483871
head(interp.df,n=10)
x y pr
1 -97.75 -52.25 4.4805383
2 -97.25 -52.25 4.0390802
3 -97.75 -51.75 3.6501175
4 -97.25 -51.75 3.3274986
5 -97.75 -51.25 2.9044791
6 -97.25 15.75 3.0526965
7 -97.75 -49.75 2.7278418
8 -97.25 -49.75 2.8603867
9 -92.75 15.75 2.6617398
10 -93.25 15.75 2.6521587
As you can see many of the coordinates present in interp.df don't exist in cruproc, so I was trying to eliminate all of the rows of interp.df whose coordinates aren't present also in cruproc.
In the example of the rows I presented, only rows 6,9,10 of interp.df would be kept since they have the same coordinates as rows 2,8,7 respectively in the other dataframe. So that the output should be:
1 -97.25 15.75 3.0526965
2 -92.75 15.75 2.6617398
3 -93.25 15.75 2.6521587
I'm pretty new on R, so I would really appreciate any insights on how to do this.
We could use inner_join():
return all rows from x where there are matching values in y, and all columns from x and y. If there are multiple matches between x and y, all combination of the matches are returned.
See https://www.rdocumentation.org/packages/dplyr/versions/0.7.8/topics/join
library(dplyr)
inner_join(interp.df, cruproc, by=c("x", "y")) %>%
select(-value)
x y pr
1 -97.25 15.75 3.052697
2 -92.75 15.75 2.661740
3 -93.25 15.75 2.652159