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

Getting values from a pandas Series

A pandas Series is a one-dimensional array-like structure that takes a NumPy data type. Each Series also has an index, an array of data labels. If an index is not specified when the Series is created, it will be the default index of 0 through N-1.

There are several ways to create a pandas Series, including from a list, dictionary, NumPy array, or a scalar. In our data cleaning work, we will most frequently be accessing data Series by selecting columns of DataFrames, using either attribute access (dataframename.columname) or bracket notation (dataframename['columnname']). Attribute access cannot be used to set values for Series, but bracket notation will work for all Series operations.

In this recipe, we’ll explore several ways we can get values from a pandas Series. These techniques are very similar to the methods we used to get rows from a pandas DataFrame, which we covered in the Selecting rows recipe of Chapter 3, Taking...

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