How is table function in R useful?
How is table function in R useful
Recipe Objective
Table function (table())in R performs a tabulation of categorical variable and gives its frequency as output. It is further useful to create conditional frequency table and Proportinal frequency table.
This recipe demonstrates how to use table() function to create the following two tables:
- Frequency table
- Frequency table with proportion
Syntax:
table(x)
where: x = one or more objects which are mostly factors
Step 1: Importing required library and Reading dataset
# Data manipulation package
install.packages("tidyverse")
library(tidyverse)
# reading a dataset
customer_seg = read.csv('R_66_Mall_Customers.csv')
glimpse(customer_seg)
Rows: 200 Columns: 5 $ CustomerID1, 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. The variable that we interested in finding the frequency is Gender - Male or female
1. Frequency table
We pass the column Gender as an arguement in table function to give the frequency table.
table(customer_seg$Gender)
Female Male 112 88
Note: 112 is the number of times Female was used in the column Gender
2. Frequency table with proportion
We use the prop.table() function along with the table() funnction to get the proportions
# creating a frequency table and storing it in variable table_1
table_1 = as.table(table(customer_seg$Gender))
# passing the frequency table as the argument in prop.table()
prop.table(table_1)
Female Male 0.56 0.44
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Ameeruddin Mohammed
I come from a background in Marketing and Analytics and when I developed an interest in Machine Learning algorithms, I did multiple in-class courses from reputed institutions though I got good... Read More