# How to calculate the mean of different column

What should I do for calculating the mean of different columns and result shows in seperate columns

There are several ways to do this. Here is a method using functions from base R. I did one case where you get the means of every column in the data frame and another method where you select the desired columns. The mean() function is intended to work on a single vector, not multiple columns of a data frame.

``````set.seed(123) # for reproducibility
DF <- data.frame(A = runif(10), B = runif(10), C = runif(10))
DF
#>            A          B         C
#> 1  0.2875775 0.95683335 0.8895393
#> 2  0.7883051 0.45333416 0.6928034
#> 3  0.4089769 0.67757064 0.6405068
#> 4  0.8830174 0.57263340 0.9942698
#> 5  0.9404673 0.10292468 0.6557058
#> 6  0.0455565 0.89982497 0.7085305
#> 7  0.5281055 0.24608773 0.5440660
#> 8  0.8924190 0.04205953 0.5941420
#> 9  0.5514350 0.32792072 0.2891597
#> 10 0.4566147 0.95450365 0.1471136
MEANS <- colMeans(DF)
MEANS
#>         A         B         C
#> 0.5782475 0.5233693 0.6155837

#If there are columns you want to ignore
DF2 <- data.frame(Name = LETTERS[1:10], A = runif(10), B = runif(10), C = runif(10), City = LETTERS[11:20])
DF2
#>    Name          A         B          C City
#> 1     A 0.96302423 0.1428000 0.04583117    K
#> 2     B 0.90229905 0.4145463 0.44220007    L
#> 3     C 0.69070528 0.4137243 0.79892485    M
#> 4     D 0.79546742 0.3688455 0.12189926    N
#> 5     E 0.02461368 0.1524447 0.56094798    O
#> 6     F 0.47779597 0.1388061 0.20653139    P
#> 7     G 0.75845954 0.2330341 0.12753165    Q
#> 8     H 0.21640794 0.4659625 0.75330786    R
#> 9     I 0.31818101 0.2659726 0.89504536    S
#> 10    J 0.23162579 0.8578277 0.37446278    T
MEANS2 <- colMeans(DF[, c("A","B", "C")])
MEANS2
#>         A         B         C
#> 0.5782475 0.5233693 0.6155837
``````

Created on 2022-03-26 by the reprex package (v0.2.1)

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