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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 14.01 – analyzing air quality data

Consider that you're working as a data analyst for your city's municipality. The Department for the Environment needs your help in getting answers to some questions related to emissions. The following are the questions the department wants answers to:

  • Which day of the week has the highest NO2(GT) emissions?
  • At what time of the day are NMHC(GT) emissions highest?
  • Which month has the lowest CO(GT) emissions?

    Note

    The emissions dataset has been sourced from the following link:

    https://archive.ics.uci.edu/ml/machine-learning-databases/00360/

    You can find the dataset in the GitHub repository for this book. Download the data, unzip the data, and then load the CSV file in a data folder of your local machine. The department needs the answers through good visualizations.

The following steps will help you complete this activity:

  1. Open a new Jupyter notebook.
  2. Download the data and then read the data using...
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