How to Use ColMeans Function in R?
In this article, we will discuss how to use the ColMeans function in R Programming Language.
Using colmeans() function
The colmean() function call be simply called by passing the parameter as the data frame to get the mean of every column present in the data frame separately in the R language.
Syntax:
colMeans(dataframe)
where dataframe is the input dataframe.
Example:
Under this example, we will be using the colmeans() function with the data frame containing three different columns to get the mean of each column present in the R language.
R
# create dataframe with three columns data= data.frame (col1= c (1,34,56,32,23), col2= c (21,34,56,32,34), col3= c (1:5)) # get mean of all columns print ( colMeans (data)) |
Output:
col1 col2 col3 29.2 35.4 3.0
Calculate mean of specific columns
In this method, the user has an option to get the mean of the specific column of the given data frame either to get the mean of the complete data frame using the colmean() function with the name of the specific column within it for which mean is to be calculated in the R language.
Syntax:
colMeans(dataframe)
where,
- dataframe is the input dataframe
- columns are the columns to get mean
Example:
In this example, we will be using the colmean() function with the name of the column as its argument to get the mean of that particular column of the data frame in the R language.
R
# create dataframe with three columns data= data.frame (col1= c (1,34,56,32,23), col2= c (21,34,56,32,34), col3= c (1:5)) # get mean of col2 and col3 print ( colMeans (data[ c ( 'col2' , 'col3' )])) |
Output:
col2 col3 35.4 3.0
Here, we can also use column numbers to get the mean value using colMeans().
Syntax:
colMeans(dataframe)
where
- col_value_start is the first column index
- col_value_end is the last column index
Example:
R
# create dataframe with three columns data= data.frame (col1= c (1,34,56,32,23), col2= c (21,34,56,32,34), col3= c (1:5)) # get mean from column1 to column3 print ( colMeans (data[ c (1,3)])) |
Output:
col1 col3 29.2 3.0
Calculate the mean of every column & exclude NA’s
In this example, the user has to use the colmean() function with the na.rm argument to calculate the mean of a column by excluding NA. NA stands for Not a number, we can do this by using na.rm() method, we will set it to True to remove NA values in the dataframe column.
Syntax:
colMeans(dataframe,na.rm=TRUE)
Example:
In this example, we will create three columns that include three NA values and get the mean of all columns using the na.rm argument under the colmeans() function.
R
# create dataframe with three columns data= data.frame (col1= c (1,34,56,32,23, NA , NA , NA ), col2= c (21, NA , NA , NA ,34,56,32,34), col3= c (1:5, NA , NA , NA )) # get mean of all columns excluding NA print ( colMeans (data,na.rm= TRUE )) |
Output:
col1 col2 col3 29.2 35.4 3.0
Calculate the mean of columns of the array in R
In this approach, the user needs to call the colmean() function with the name of the array with its dimensions as the parameter to get the mean of the columns of the given array in the R language.
Syntax:
colMeans(data, dims )
where,
- data is the input array
- dims stands for dimensions
Example:
in this example, we will create an array with 3 dimensions with 1 to 12 elements and calculate column means using the colmeans() function in the R programming language.
R
# Initializing a 3D array data= array (1:12, c (2, 3, 3)) # colmeans for one dimension print ( colMeans (data, dims = 1)) # colmeans for two dimension print ( colMeans (data, dims = 2)) |
Output:
[,1] [,2] [,3] [1,] 1.5 7.5 1.5 [2,] 3.5 9.5 3.5 [3,] 5.5 11.5 5.5 [1] 3.5 9.5 3.5
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