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Python Data Cleaning Cookbook

You're reading from Python Data Cleaning Cookbook Prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn, and OpenAI

Product type Paperback

Published in May 2024

Publisher Packt

ISBN-13 9781803239873

Length 486 pages

Edition 2nd Edition

Languages

Python

Tools

Matplotlib

Concepts

Data Analysis

Author (1):

Michael Walker

View More author details

Table of Contents (14) Chapters

Preface

1. Anticipating Data Cleaning Issues When Importing Tabular Data with pandas

2. Anticipating Data Cleaning Issues When Working with HTML, JSON, and Spark Data FREE CHAPTER

3. Taking the Measure of Your Data

4. Identifying Outliers in Subsets of Data

5. Using Visualizations for the Identification of Unexpected Values

6. Cleaning and Exploring Data with Series Operations

7. Identifying and Fixing Missing Values

8. Encoding, Transforming, and Scaling Features

9. Fixing Messy Data When Aggregating

10. Addressing Data Issues When Combining DataFrames

11. Tidying and Reshaping Data

12. Automate Data Cleaning with User-Defined Functions, Classes, and Pipelines

13. Index

Using line plots to examine trends in continuous variables

A typical way to visualize values for a continuous variable over regular intervals of time is through a line plot, though sometimes bar charts are used for small numbers of intervals. We will use line plots in this recipe to display variable trends and examine sudden deviations in trends and differences in values over time by groups.

Getting ready

We will work with daily COVID-19 case data in this recipe. In previous recipes, we have used totals by country. The daily data provides us with the number of new cases and new deaths each day by country, in addition to the same demographic variables we used in other recipes. You will need Matplotlib installed to run the code in this recipe.

How to do it…

We use line plots to visualize trends in daily COVID-19 cases and deaths. We create line plots by region, and stacked plots to get a better sense of how much one country can drive the number of cases for a...

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Authors (1)

Michael Walker

Michael Walker

Michael Walker has worked as a data analyst for over 30 years at a variety of educational institutions. He is currently the CIO at College Unbound in Providence, Rhode Island, in the United States. He has also taught data science, research methods, statistics, and computer programming to undergraduates since 2006.

See other products by Michael Walker

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