Book Image

Matplotlib for Python Developers - Second Edition

By : Aldrin Yim, Claire Chung, Allen Yu
Book Image

Matplotlib for Python Developers - Second Edition

By: Aldrin Yim, Claire Chung, Allen Yu

Overview of this book

Python is a general-purpose programming language increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the Matplotlib library. Matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. After that, you’ll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You’ll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, you’ll explore Matplotlib 2.1.x on the web, from a cloud-based platform using third-party packages such as Django. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples. By the end of this book, you’ll be thoroughly comfortable with using the popular Python data visualization library Matplotlib 2.1.x and leveraging its power to build attractive, insightful, and powerful visualizations.
Table of Contents (16 chapters)
Title Page
Dedication
Packt Upsell
Contributors
Preface
Index

Our first plots with Matplotlib


We have just revised the basic ways of data handling with Python. Without further ado, let's create our first "Hello World!" plot example.

Importing the pyplot

To create a pandas DataFrame from objects such as lists and ndarrays, you may call:

importpandasaspd

To start creating Matplotlib plots, we first import the plotting API pyplot by entering this command:

importmatplotlib.pyplotasplt

This will start your plotting routine.

Note

In Jupyter Notebook, you need to import modules once you begin a notebook session after starting the kernel.

Line plot

After importing matplotlib.pyplot as plt, we draw line plots with the plt.plot() command.

Here is a code snippet for a simple example of plotting the temperature of the week:

# Import the Matplotlib module
importmatplotlib.pyplotasplt

# Use a list to store the daily temperature
t = [22.2,22.3,22.5,21.8,22.5,23.4,22.8]

# Plot the daily temperature t as a line plot
plt.plot(t)

# Show the plot
plt.show()

After you run the code...