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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

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781803239873
Length 486 pages
Edition 2nd Edition
Languages
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Author (1):
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Michael Walker Michael Walker
Author Profile Icon Michael Walker
Michael Walker
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Table of Contents (14) Chapters Close

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 PandasAI to identify outliers

We can use PandasAI to support some of the work we have done in this chapter to identify outliers. We can check for extreme values based on a univariate analysis. We can look at bivariate and multivariate relationships as well. PandasAI will also help us generate visualizations easily.

Getting ready

You need to install PandasAI to run the code in this recipe. You can do that with pip install pandasai. We will work with the COVID-19 data again, which is available in the GitHub repository, as well as the code.

You will also need an API key from OpenAI. You can get one at platform.openai.com. You will need to setup an account and then click on your profile in the upper-right corner and then View API keys.

The PandasAI library is improving rapidly, and some things have changed, even since I began writing this book. I have used PandasAI version 2.0.30 in this recipe. It also matters which version of pandas you use with it. I have use...

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