How to find quantile and quartiles in R?
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# How to find quantile and quartiles in R?

This recipe helps you find quantile and quartiles in R

0

## 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 stats which describes the variability of the numeric variable. These include IQR, quartiles, quantiles, mean and median. They help us to detect any outliers in the column and the distribution of the column.

This recipe focuses on finding quartile and quantile of the column.

Quantile and Quartile gives the measure of variabilty in the data. Quantiles provides a way to divide the numbers of a given distribution in equal subgroups after sorting the data. Quartiles are the three points in the dataset which divides the number of observations into four equal subgroups.

## Step 1: Loading necesary libraries and loading dataset

``` # Data manipulation package library(tidyverse) ​ # reading a dataset customer_seg = read.csv('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. The variable that we interested in finding the Quantiles and Quartiles of is Annual.Income.
```

## Step 2: Calculating Quantile/Percentile

We use the quantile() function to do the task. Let's get the 30th Quantile value of column Annual Income

``` # prob argument represent the nth percentile. In this case it's the 30th percentile. quantile(customer_seg\$Annual.Income..k.., probs = 0.30) ```
```30%: 46
```

## Step 3: Calculating Quartile

We use the quantile() function to do the same task. This time the probs = 25%, 50%, 75%.

``` quantile(customer_seg\$Annual.Income..k.., prob = c(0.25,0.50, 0.75)) ```
```25% 41.5 50% 61.5 75% 78
```

## Step 4: Calculating median and mean together

We use the summary() function to calculate the mean, median and other statistical terms of the column

``` summary(customer_seg\$Annual.Income..k..) ``` Min. 1st Qu. Median Mean 3rd Qu. Max. 15.00 41.50 61.50 60.56 78.00 137.00

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