Book Image

Matplotlib 2.x By Example

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

Matplotlib 2.x By Example

By: Allen Yu, Claire Chung, Aldrin Yim

Overview of this book

Big data analytics are driving innovations in scientific research, digital marketing, policy-making and much more. Matplotlib offers simple but powerful plotting interface, versatile plot types and robust customization. Matplotlib 2.x By Example illustrates the methods and applications of various plot types through real world examples. It begins by giving readers the basic know-how on how to create and customize plots by Matplotlib. It further covers how to plot different types of economic data in the form of 2D and 3D graphs, which give insights from a deluge of data from public repositories, such as Quandl Finance. You will learn to visualize geographical data on maps and implement interactive charts. By the end of this book, you will become well versed with Matplotlib in your day-to-day work to perform advanced data visualization. This book will guide you to prepare high quality figures for manuscripts and presentations. You will learn to create intuitive info-graphics and reshaping your message crisply understandable.
Table of Contents (15 chapters)
Title Page
About the Authors
About the Reviewer
Customer Feedback

Test your skills

Now that we have gone through each style setting one by one, it's your showtime to combine all the techniques!

import matplotlib.pyplot as plt; plt.rcdefaults()
import numpy as np 
import matplotlib as mpl'seaborn-darkgrid')

# 2001-2015 per genome sequencing cost in USD
# Adapted from NIH National Human Genome Research Institute figures
# Data were quoted from on May 8th 2017
# Seasonal data were averaged by year for simplicity

# Prepare the data
years = list(range(2001,2016))
y_pos = np.arange(len(years)) 
seqcost = [95263071.92,70175437.42,61448421.50,53751684.08,