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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 generative AI to display descriptive statistics

Generative AI tools provide data scientists with a great opportunity to streamline the data cleaning and exploration parts of our workflow. Large language models, in particular, have the potential to make this work much easier and more intuitive. Using these tools, we can select rows and columns by criteria, generate summary statistics, and plot variables.

A simple way to introduce generative AI tools into your data exploration is with PandasAI. PandasAI uses the OpenAI API to translate natural language queries into data selection and operations that pandas can understand. As of July 2023, OpenAI is the only large language model API that can be used with PandasAI, though the developers of the library anticipate adding other APIs.

We can use PandasAI to substantially reduce the lines of code we need to write to produce some of the tabulations and visualizations we have created so far in this chapter. The steps in this recipe...

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