Taking Average of Certain Columns while keeping certain columns untouched-CodePudding

I am looking to take the average of certain columns, and then renaming the first 2 columns to make a brand new data frame.

Lets say this is DF

Participant	Date	Score1	Place	Job
First	10_Sep_Mon	12	3	5.5
Second	10_Sep_Mon	11	2	5.7
Third	10_Sep_Mon	14	2.5	5
Fourth	10_Sep_Mon	21	2.8	5.1

I want to make a new data frame that looks like this, where the first column name is named different, the date is kept the same, and all columns starting the 3rd and until the very end ncol(DF), cause there are lots of columns than 3.

This would be a new data frame called DF2

Participant	Date	Score1	Place	Job
Averaged	10_Sep_Mon	14.5	2.6	5.3

What is the best way to apply this calculation?

Here is some code if that may help. Thank you!

Participant <- c("First", "Second", "Third", "Fourth")
Date <- c("10_Sep_Mon", "10_Sep_Mon", "10_Sep_Mon", "10_Sep_Mon")
Score1 <- c(12, 11, 14, 21)
Place <- c(3, 2, 2.5, 2.8)
Job <- c(5.5, 5.7, 5, 5.1)
DF <- data.frame(Participant, Date, Score1, Place, Job)

CodePudding user response：

cbind first row, first two columns to the colMeans of the remaining columns (need to be transposed).

cbind(DF[1, 1:2], t(colMeans(DF[-(1:2)])))
#   Participant       Date Score1 Place   Job
# 1       First 10_Sep_Mon   14.5 2.575 5.325

CodePudding user response：

Or using dplyr you could do:

library(dplyr, warn = FALSE)

DF %>%
  group_by(Participant = "Averaged", Date) %>%
  summarise(across(everything(), mean), .groups = "drop")
#> # A tibble: 1 × 5
#>   Participant Date       Score1 Place   Job
#>   <chr>       <chr>       <dbl> <dbl> <dbl>
#> 1 Averaged    10_Sep_Mon   14.5  2.58  5.32