Mastering Plotly and Dash Data Visualization with Python/

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Continuous vs Categorical Bivariate Analysis: Boxplot & Histogram

Continuous vs Categorical Bivariate Analysis: Boxplot & Histogram

Learn how to analyse a continuous variable and a categorical variable together.

We'll cover the following...

Bivariate analysis: Bivariate histograms

In this section, we will discuss the ways in which we can analyze a continuous variable and a categorical variable together.

Bivariate analysis

Bivariate analysis is a statistical technique that encompasses exploring the relationship between two variables. Bivariate analysis can be implemented when a variable is continuous, and another is categorical, in which we are then able to determine if there is a difference in the distribution of the continuous variable for each category of the categorical variable.

For the next few examples, we will use a customer churn dataset that details whether individuals have left a company. The dataset details important features of the customer, such as their age, credit score, place of residence, etc.

Python 3.8
# Import libraries
import pandas as pd
# Import dataset
churn = pd.read_csv("/usr/local/csvfiles/churn.csv")
# Look at data
print(churn.head())

Bivariate box plots

We will expand our work from the first chapter and, this time, group our plots by category. We will start by ...