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Python Data Visualization Cookbook (Second Edition)

You're reading from   Python Data Visualization Cookbook (Second Edition) Visualize data using Python's most popular libraries

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781784396695
Length 302 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (11) Chapters Close

Preface 1. Preparing Your Working Environment FREE CHAPTER 2. Knowing Your Data 3. Drawing Your First Plots and Customizing Them 4. More Plots and Customizations 5. Making 3D Visualizations 6. Plotting Charts with Images and Maps 7. Using the Right Plots to Understand Data 8. More on matplotlib Gems 9. Visualizations on the Clouds with Plot.ly Index

Drawing simple sine and cosine plots


This recipe will go over basics of plotting mathematical functions and several things that are related to math graphs such as writing Greek symbols in labels and on curves.

Getting ready

The most common graph we will use is the line plot command, which draws the given (x,y) coordinates on a figure plot.

How to do it...

We start with computing sine and cosine functions over the same linear interval—from Pi to Pi with 256 points in between and we plot the values for sin(x) and cos(x) over the same plot as shown here:

import matplotlib.pyplot as pl
import numpy as np

x = np.linspace(-np.pi, np.pi, 256, endpoint=True)

y = np.cos(x)
y1 = np.sin(x)

pl.plot(x,y)
pl.plot(x, y1)

pl.show()

That will give us the following graph:

Following this simple plot, we can customize more to give more information and be more precise about axes and boundaries as shown here:

from pylab import *
import numpy as np

# generate uniformly distributed
# 256 points from -pi to pi, inclusive...
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