#### Overview of this book

Machine learning is becoming increasingly pervasive in the modern data-driven world. It is used extensively across many fields such as search engines, robotics, self-driving cars, and more. With this book, you will learn how to perform various machine learning tasks in different environments. We’ll start by exploring a range of real-life scenarios where machine learning can be used, and look at various building blocks. Throughout the book, you’ll use a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms. You’ll discover how to deal with various types of data and explore the differences between machine learning paradigms such as supervised and unsupervised learning. We also cover a range of regression techniques, classification algorithms, predictive modeling, data visualization techniques, recommendation engines, and more with the help of real-world examples.
Python Machine Learning Cookbook
Credits
www.PacktPub.com
Preface
Free Chapter
The Realm of Supervised Learning
Visualizing Data
Index

## Drawing pie charts

Let's see how to plot pie charts. This is useful when you want to visualize the percentages of a set of labels in a group.

### How to do it…

1. Create a new Python file, and import the following packages:

```import numpy as np
import matplotlib.pyplot as plt ```
2. Define the labels and values:

```# Labels and corresponding values in counter clockwise direction
data = {'Apple': 26,
'Mango': 17,
'Pineapple': 21,
'Banana': 29,
'Strawberry': 11}```
3. Define the colors for visualization:

```# List of corresponding colors
colors = ['orange', 'lightgreen', 'lightblue', 'gold', 'cyan']```
4. Define a variable to highlight a section of the pie chart by separating it from the rest. If you don't want to highlight any section, set all the values to `0`:

```# Needed if we want to highlight a section
explode = (0, 0, 0, 0, 0)  ```
5. Plot the pie chart. Note that if you use Python 3, you should use `list(data.values())` in the following function call:

```# Plot the pie chart
plt.pie(data.values(), explode...```