I would like to reorder a data frame's columns according to arithmetic mean of each column.
For:
S1 S2 S3
1 1 1
2 1 1
3 3 1
the expected output is:
S3 S2 S1
1 1 1
1 1 2
1 3 3
In above case, the averages were: S1 = 2, S2 = 1.6666 and S3 = 1, inverting S1 and S3 columns positions in a data frame.
Additionally, my real data have NA´s values too.
Use the order() function.
An exemplary data frame:
df <- data.frame(s1=runif(5), s2=runif(5), s3=runif(5))
df[1,2] <- NA # some NAs
df
## s1 s2 s3
## 1 0.74473576 NA 0.71547379
## 2 0.66997782 0.6474405 0.62320795
## 3 0.05361586 0.5370381 0.03298139
## 4 0.06209263 0.9409920 0.46096984
## 5 0.42432948 0.9983042 0.38503196
Calculate column means, with NAs omitted:
(mns <- colMeans(df, na.rm=TRUE))
## s1 s2 s3
## 0.3909503 0.7809437 0.4435330
The desired column ordering is:
order(mns)
## [1] 1 3 2
(s1 goes first, s2 goes last, and s3 should become the 2nd column)
Now you may reorder the columns:
(df <- df[,order(mns)])
## s1 s3 s2
## 1 0.74473576 0.71547379 NA
## 2 0.66997782 0.62320795 0.6474405
## 3 0.05361586 0.03298139 0.5370381
## 4 0.06209263 0.46096984 0.9409920
## 5 0.42432948 0.38503196 0.9983042
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