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Pandas 1.x Cookbook - Second Edition

You're reading from  Pandas 1.x Cookbook - Second Edition

Product type Book
Published in Feb 2020
Publisher Packt
ISBN-13 9781839213106
Pages 626 pages
Edition 2nd Edition
Languages
Authors (2):
Matt Harrison Matt Harrison
Profile icon Matt Harrison
Theodore Petrou Theodore Petrou
Profile icon Theodore Petrou
View More author details

Table of Contents (17) Chapters

Preface 1. Pandas Foundations 2. Essential DataFrame Operations 3. Creating and Persisting DataFrames 4. Beginning Data Analysis 5. Exploratory Data Analysis 6. Selecting Subsets of Data 7. Filtering Rows 8. Index Alignment 9. Grouping for Aggregation, Filtration, and Transformation 10. Restructuring Data into a Tidy Form 11. Combining Pandas Objects 12. Time Series Analysis 13. Visualization with Matplotlib, Pandas, and Seaborn 14. Debugging and Testing Pandas 15. Other Books You May Enjoy
16. Index

Adding columns from different DataFrames

All DataFrames can add new columns to themselves. However, as usual, whenever a DataFrame is adding a new column from another DataFrame or Series, the indexes align first, and then the new column is created.

This recipe uses the employee dataset to append a new column containing the maximum salary of that employee's department.

How to do it…

  1. Import the employee data and select the DEPARTMENT and BASE_SALARY columns in a new DataFrame:
    >>> employee = pd.read_csv("data/employee.csv")
    >>> dept_sal = employee[["DEPARTMENT", "BASE_SALARY"]]
    
  2. Sort this smaller DataFrame by salary within each department:
    >>> dept_sal = dept_sal.sort_values(
    ...     ["DEPARTMENT", "BASE_SALARY"],
    ...     ascending=[True, False],
    ... )
    
  3. Use the .drop_duplicates method to keep the first row of each DEPARTMENT: ...
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