选择R中满足条件的数据，并在该条件下使用for循环

Question

I have a problem with the selection of column in a dataframe using a for loop. I'm new to R so it's very possible that I missed something obvious, but I did not find anything that works for me.

I have a file with 20 climatic variable measured during 60 years in 399 differents places. I have a line for each day, and my column are the 20 climatic variable for each place (with a number at the end of the name to identify the place where the measure was taken). It looks like that :

     Temperature_1   Rain_1 .....Temperature_399   Rain_399
Date 1
Date 2
...

I want to select the 20 column corresponding to one place, run some calculations on the variables, put the results in an empty 3D array I have created, then do the same for the next place until the last one.

My problem is that I don't know how to select the right columns automatically. I also have issues with the writing of the results in the array.

I tried to select the columns corresponding to one place using the numbers at the end of the name of the variables, but I don't think it is possible to change automatically the condition.

I also tried to use the position of the columns but I'm not doing it properly

This is my code :

#creation of an empty array
Indice_clim=array(NA,dim = c(60,8,399),dimnames=list(c(1959:2018),c("Huglin","CNI","HD","VHD","SHS","DoF","FreqLF","SLF"),c(1:399)))

#selection of the columns corresponding to the first place using "end with"
maille=select(donnees_SAFRAN,c(1:4),ends_with(".1",ignore.case = FALSE))

# another try using the columns position which I know is really badly done
for (j in seq(from=5, to=7984,by=20)){ 
paste0("maille",j-4)=select(donnees_SAFRAN,c(1:4),c(j:j+19))
} 

#and the calculation on the selected columns, the "i loop" is working.
for(i in 1959:2018)temp=c(maille%>%filter(an==i,mois==4|mois==5|mois==6|mois==7|mois==8|mois==9)%>%summarise(sum(((T_moy.1-10)+(T_max.1-10))/2)*1.03),
   maille%>%filter(an==i,mois==9)%>%summarise(mean(T_min.1)),
   maille%>%filter(an==i)%>%summarise(sum(T_max.1>=30)),
   maille%>%filter(an==i)%>%summarise(sum(T_max.1>=35)),
   maille%>%filter(an==i,mois==4|mois==5|mois==6|mois==7|mois==8|mois==9,T_moy.1>=28)%>%summarise(sum(T_moy.1-28)),
   maille%>%filter(an==i)%>%summarise(sum(T_min.1<=0)),
   maille%>%filter(an==i,mois==4|mois==5|mois==6|mois==7|mois==8|mois==9)%>%summarise(sum(T_min.1<=0)),
   maille%>%filter(an==i,mois==4|mois==5|mois==6|mois==7|mois==8|mois==9,T_moy.1<2)%>%summarise(sum(abs(2-T_moy.1))))

   Indice_clim[[i-1958,,]]=as.numeric(temp)}

I would like to create a loop or something to do my calculation on each place and write the result in my array. If you have any idea, I would very much appreciate it !

Answer 1

You can use the grep() function to look for each of the locations 1, 2, ..., 399 in the column names. If your big dataframe containing all the data is called df, then you could do this:

for (i in 1:399) {
  selected_indices <- grep(paste0('_', i, '$'), colnames(df))
  # do calculations on the selected columns
  df[, selected_indices]
}

The for loop will automatically run through each location i from 1 through 399. The paste0() function concatenates '_' with the variable i and the dollar sign $ to create strings like "_1$", "_2$", ..., "_399$", which are then searched for using the grep() function in the column names of df. The '$' is used to specify that you want the patterns _1, _2, ... to appear at the end of the column names (it is a regular expression special character).

The grep() function uses the above regular expressions to returns the column indices required for each location. You can then extract the relevant portion of df and do whatever calculations you want.