Get started with the basics of analytics in Python, the language of choice for data science.

Python Data Analysis and Visualization

Get started with the basics of analytics in Python, the language of choice for data science using Python data structures,  descriptive statistics, and much more.

Data Analysis and Visualization

# Introduction to categorical data

Sometimes you get [categorical data](https://en.wikipedia.org/wiki/Categorical_variable) which are variables with a limited and usually fixed number of values. For example, **male** and **female**. Machine learning algorithms need numbers to work, so how do you deal with these? We will discuss two ways: 

* Label encoding 
* One-hot encoding a.k.a. dummy variables.

# Dealing with categorical data

## Label encoding

**Label encoding** works by converting the unique values to a numeric representation. For example, if we have two categories **male** and **female**, we can categorize them as numbers:

* male as **0**
* female **1**

Pandas provides an easy way to do this by using the `category` type.

This lesson discusses what is categorical data and how Pandas provide support dealing with it.

Categorical Data

Introduction to categorical data