I have two dataframes, df_value and df_num. df_num has two columns:row and col which are the row and column numbers of the value from df_value that meets a specific condition. I want to calculate the mean group by col in the df_num.
I got stuck at group by col.
df_value<- data.frame('a'=1:3,'b'=2:4,'c'=1:3,'d'=3:5)
df_num <- which(df<4,arr.ind = TRUE)
df_value
a b c d
1 2 1 3
2 3 2 4
3 4 3 5
df_num
row col
1 1
2 1
3 1
1 2
2 2
1 3
2 3
3 3
1 4
I want get the mean for col1, col2, col3 and col4,
mean:
2
2.5
2
3
If you have to use df_num to subset df_val and then take mean of columns one way is to split subsetted df_value based on "col" column of df_num and take mean of each list.
sapply(split(df_value[df_num], df_num[, "col"]), mean, na.rm = TRUE)
# 1 2 3 4
#2.0 2.5 2.0 3.0
As mentioned in the comments you can directly filter df_value to take mean
sapply(df_value, function(x) mean(x[x<4], na.rm = TRUE))
# 1 2 3 4
#2.0 2.5 2.0 3.0
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