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Applying Math with Python

You're reading from   Applying Math with Python Over 70 practical recipes for solving real-world computational math problems

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Product type Paperback
Published in Dec 2022
Publisher Packt
ISBN-13 9781804618370
Length 376 pages
Edition 2nd Edition
Languages
Concepts
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Author (1):
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Sam Morley Sam Morley
Author Profile Icon Sam Morley
Sam Morley
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Toc

Table of Contents (13) Chapters Close

Preface 1. Chapter 1: An Introduction to Basic Packages, Functions, and Concepts 2. Chapter 2: Mathematical Plotting with Matplotlib FREE CHAPTER 3. Chapter 3: Calculus and Differential Equations 4. Chapter 4: Working with Randomness and Probability 5. Chapter 5: Working with Trees and Networks 6. Chapter 6: Working with Data and Statistics 7. Chapter 7: Using Regression and Forecasting 8. Chapter 8: Geometric Problems 9. Chapter 9: Finding Optimal Solutions 10. Chapter 10: Improving Your Productivity 11. Index 12. Other Books You May Enjoy

Plotting data from a DataFrame

As with many mathematical problems, one of the first steps to finding some way to visualize the problem and all the information is to formulate a strategy. For data-based problems, this usually means producing a plot of the data and visually inspecting it for trends, patterns, and the underlying structure. Since this is such a common operation, pandas provides a quick and simple interface for plotting data in various forms, using Matplotlib under the hood by default, directly from a Series or DataFrame.

In this recipe, we will learn how to plot data directly from a DataFrame or Series to understand the underlying trends and structure.

Getting ready

For this recipe, we will need the pandas library imported as pd, the NumPy library imported as np, the Matplotlib pyplot module imported as plt, and a default random number generator instance created using the following commands:

from numpy.random import default_rng
rng = default_rng(12345)

How...

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