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The Pandas Workshop

You're reading from   The Pandas Workshop A comprehensive guide to using Python for data analysis with real-world case studies

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Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781800208933
Length 744 pages
Edition 1st Edition
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Authors (4):
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Blaine Bateman Blaine Bateman
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Blaine Bateman
William So William So
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William So
Saikat Basak Saikat Basak
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Saikat Basak
Thomas Joseph Thomas Joseph
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Thomas Joseph
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Toc

Table of Contents (21) Chapters Close

Preface 1. Part 1 – Introduction to pandas
2. Chapter 1: Introduction to pandas FREE CHAPTER 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 6.02 – DataFrame data selection

In this activity, you need to analyze data from this year's survey of Abalone oysters for the National Marine Fisheries Service (the source data can be found in the UCI repository: https://archive.ics.uci.edu/ml/datasets/abalone). In particular, you want to get some summary values for the dimensions of male and female samples in the data, depending on the number of rings in the oysters' shells. The ring count is a measure of age, and reviewing this data provides comparisons to previous years to help you understand the health of the population. The data contains several observations, including sex, length, diameter, weight, shell weight, and the number of rings.

To complete this activity, follow these steps:

  1. For this activity, all you will need is the pandas library. Load it into the first cell of the notebook.
  2. Read the abalone.csv file into a DataFrame called abalone and view the first five rows.
  3. Create a...
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