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Matplotlib 3.0 Cookbook

You're reading from   Matplotlib 3.0 Cookbook Over 150 recipes to create highly detailed interactive visualizations using Python

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781789135718
Length 676 pages
Edition 1st Edition
Languages
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Authors (2):
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Nikhil Borkar Nikhil Borkar
Author Profile Icon Nikhil Borkar
Nikhil Borkar
Srinivasa Rao Poladi Srinivasa Rao Poladi
Author Profile Icon Srinivasa Rao Poladi
Srinivasa Rao Poladi
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Toc

Table of Contents (17) Chapters Close

Preface 1. Anatomy of Matplotlib FREE CHAPTER 2. Getting Started with Basic Plots 3. Plotting Multiple Charts, Subplots, and Figures 4. Developing Visualizations for Publishing Quality 5. Plotting with Object-Oriented API 6. Plotting with Advanced Features 7. Embedding Text and Expressions 8. Saving the Figure in Different Formats 9. Developing Interactive Plots 10. Embedding Plots in a Graphical User Interface 11. Plotting 3D Graphs Using the mplot3d Toolkit 12. Using the axisartist Toolkit 13. Using the axes_grid1 Toolkit 14. Plotting Geographical Maps Using Cartopy Toolkit 15. Exploratory Data Analysis Using the Seaborn Toolkit 16. Other Books You May Enjoy

Line plot

The line plot is used to represent a relationship between two continuous variables. It is typically used to represent the trend of a variable over time, such as GDP growth rate, inflation, interest rates, and stock prices over quarters and years. All the graphs we have seen in Chapter 1, Anatomy of Matplotlib are examples of a line plot.

Getting ready

We will use the Google Stock Price data for plotting time series line plot. We have the data (date and daily closing price, separated by commas) in a .csv file without a header, so we will use the pandas library to read it and pass it on to the matplotlib.pyplot function to plot the graph.

Let's now import required libraries with the following code:

import matplotlib...
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