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The Pandas Workshop

You're reading from  The Pandas Workshop

Product type Book
Published in Jun 2022
Publisher Packt
ISBN-13 9781800208933
Pages 744 pages
Edition 1st Edition
Languages
Authors (4):
Blaine Bateman Blaine Bateman
Profile icon Blaine Bateman
Saikat Basak Saikat Basak
Profile icon Saikat Basak
Thomas V. Joseph Thomas V. Joseph
Profile icon Thomas V. Joseph
William So William So
Profile icon William So
View More author details

Table of Contents (21) Chapters

Preface 1. Part 1 – Introduction to pandas
2. Chapter 1: Introduction to pandas 3. Chapter 2: Working with Data Structures 4. Chapter 3: Data I/O 5. Chapter 4: Pandas Data Types 6. Part 2 – Working with Data
7. Chapter 5: Data Selection – DataFrames 8. Chapter 6: Data Selection – Series 9. Chapter 7: Data Exploration and Transformation 10. Chapter 8: Understanding Data Visualization 11. Part 3 – Data Modeling
12. Chapter 9: Data Modeling – Preprocessing 13. Chapter 10: Data Modeling – Modeling Basics 14. Chapter 11: Data Modeling – Regression Modeling 15. Part 4 – Additional Use Cases for pandas
16. Chapter 12: Using Time in pandas 17. Chapter 13: Exploring Time Series 18. Chapter 14: Applying pandas Data Processing for Case Studies 19. Chapter 15: Appendix 20. Other Books You May Enjoy

Activity 7.01 – data analysis using pivot tables

In this activity, you will build pivot tables in order to perform data analysis. We will work on the Student Performance dataset from the GitHub repository.

Note

More details about the Student Performance dataset can be found at https://archive.ics.uci.edu/ml/datasets/Student+Performance.

Your tasks will be to do the following:

  1. Open a Jupyter notebook.
  2. Import the pandas package.
  3. Load the CSV file (using the ; delimiter to separate the columns) as a DataFrame.
  4. Modify the DataFrame to contain only these columns: school, sex, age, address, heath, absences, G1, G2, and G3.
  5. Display the first 10 rows of the DataFrame.
  6. Build a pivot table that is indexed on school.
  7. Build a pivot table that is indexed on school and age.
  8. Build a pivot table that is indexed on school, sex, and age, with the mean and sum aggregation on the absences column.

The expected output is as follows:

...
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