calculate the mean for each column of a matrix in R

I am working on R in R studio. I need to calculate the mean for each column of a data frame.

 cluster1  // 5 by 4 data frame
 mean(cluster1) // 

I got :

  Warning message:
  In mean.default(cluster1) :
  argument is not numeric or logical: returning NA

But I can use

  mean(cluster1[[1]])

to get the mean of the first column.

How to get means for all columns ?

Any help would be appreciated.

Solution 1:

You can use colMeans:

### Sample data
set.seed(1)
m <- data.frame(matrix(sample(100, 20, replace = TRUE), ncol = 4))

### Your error
mean(m)
# [1] NA
# Warning message:
# In mean.default(m) : argument is not numeric or logical: returning NA

### The result using `colMeans`
colMeans(m)
#   X1   X2   X3   X4 
# 47.0 64.4 44.8 67.8 

Solution 2:

You can use 'apply' to run a function or the rows or columns of a matrix or numerical data frame:

cluster1 <- data.frame(a=1:5, b=11:15, c=21:25, d=31:35)

apply(cluster1,2,mean)  # applies function 'mean' to 2nd dimension (columns)

apply(cluster1,1,mean)  # applies function to 1st dimension (rows)

sapply(cluster1, mean)  # also takes mean of columns, treating data frame like list of vectors

Solution 3:

In case you have NA's:

sapply(data, mean, na.rm = T)      # Returns a vector (with names)   
lapply(data, mean, na.rm = T)      # Returns a list  

Remember that "mean" needs numeric data. If you have mixed class data, then use:

numdata<-data[sapply(data, is.numeric)]  
sapply(numdata, mean, na.rm = T)  # Returns a vector
lapply(numdata, mean, na.rm = T)  # Returns a list