What is rowmeans and colmeans in R?

Recipe Objective

Exploratory Data Analysis is a crucial step before building any machine learning model on a dataset. This also includes gathering statistical inferences from the data. There are a few main terms in statistics which describes the central tendency of the variables i.e. means and medians. R gives us the flexibilty to calculate these measures row-wise and column-wise.

This recipe focuses on using rowMeans() and colMeans() functions.

rowMeans() function calculates the means of of all the rows in the dataset and displays the output

colMeans() function calculates the means of all the columns in the dataset and displays the output

Access House Price Prediction Project using Machine Learning with Source Code

Step 1: Importing libraries and loading dataset

# Data manipulation package library(tidyverse) ​ # reading a dataset customer_seg = read.csv('R_77_Mall_Customers.csv') ​ glimpse(customer_seg)

Rows: 200
Columns: 5
$ CustomerID              1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1...
$ Gender                  Male, Male, Female, Female, Female, Female, ...
$ Age                     19, 21, 20, 23, 31, 22, 35, 23, 64, 30, 67, ...
$ Annual.Income..k..      15, 15, 16, 16, 17, 17, 18, 18, 19, 19, 19, ...
$ Spending.Score..1.100.  39, 81, 6, 77, 40, 76, 6, 94, 3, 72, 14, 99,...

Dataset description: It is the basic data about the customers going to the supermarket mall. We are interested in all the numeric variables in the dataset.

Step 2: Using rowMeans()

# calculating means of every row apart ignoring the values in the 2nd column as it is categorical rowMeans(customer_seg[,-2])

Step 3: Using colMeans()

# calculating means of every column apart ignoring the values in the 2nd column as it is categorical in nature colMeans(customer_seg[,-2])

CustomerID100.5Age38.85Annual.Income..k..60.56Spending.Score..1.100.50.2