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Hands-On Data Analysis with Pandas

You're reading from Hands-On Data Analysis with Pandas Efficiently perform data collection, wrangling, analysis, and visualization using Python

Product type Paperback

Published in Jul 2019

Publisher

ISBN-13 9781789615326

Length 740 pages

Edition 1st Edition

Languages

Python

Tools

Pandas

Concepts

Data Analysis

Author (1):

Stefanie Molin

View More author details

Table of Contents (21) Chapters

Preface

1. Section 1: Getting Started with Pandas FREE CHAPTER

2. Introduction to Data Analysis

3. Working with Pandas DataFrames

4. Section 2: Using Pandas for Data Analysis

5. Data Wrangling with Pandas

6. Aggregating Pandas DataFrames

7. Visualizing Data with Pandas and Matplotlib

8. Plotting with Seaborn and Customization Techniques

9. Section 3: Applications - Real-World Analyses Using Pandas

10. Financial Analysis - Bitcoin and the Stock Market

11. Rule-Based Anomaly Detection

12. Section 4: Introduction to Machine Learning with Scikit-Learn

13. Getting Started with Machine Learning in Python

14. Making Better Predictions - Optimizing Models

15. Machine Learning Anomaly Detection

16. Section 5: Additional Resources

17. The Road Ahead

18. Solutions

19. Other Books You May Enjoy

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Appendix

Further reading

The following are some interesting links from the pandas documentation:

Styling DataFrames: https://pandas.pydata.org/pandas-docs/stable/style.html
The pandas ecosystem: https://pandas.pydata.org/pandas-docs/stable/ecosystem.html

Those with an R and/or SQL background may find it helpful to see how the pandas syntax compares:

Comparison with R / R Libraries: https://pandas.pydata.org/pandas-docs/stable/comparison_with_r.html
Comparison with SQL: https://pandas.pydata.org/pandas-docs/stable/comparison_with_sql.html
SQL Queries: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#sql-queries

Some resources for learning more about regular expressions are as follows:

Mastering Python Regular Expressions by Félix López, Víctor Romero: https://www.packtpub.com/application-development/mastering-python-regular-expressions
Regular Expression...

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Authors (1)

Stefanie Molin

Stefanie Molin

Stefanie Molin is a data scientist and software engineer at Bloomberg LP in NYC, tackling tough problems in information security, particularly revolving around anomaly detection, building tools for gathering data, and knowledge sharing. She has extensive experience in data science, designing anomaly detection solutions, and utilizing machine learning in both R and Python in the AdTech and FinTech industries. She holds a B.S. in operations research from Columbia University's Fu Foundation School of Engineering and Applied Science, with minors in economics, and entrepreneurship and innovation. In her free time, she enjoys traveling the world, inventing new recipes, and learning new languages spoken among both people and computers.

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Hands-On Data Analysis with Pandas

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Apr 2021 26h 16m

Hands-On Data Analysis with Pandas

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Knowing how to work with data to extract insights generates significant value. This book will help you to develop data analysis skills using a hands-on approach and real-world data. You'll get up to speed with pandas 1.x in no time and build some software engineering skills in the process, vastly expanding your data science toolbox.

Apr 2021 26h 16m

Hands-On Data Analysis with Pandas

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Knowing how to work with data to extract insights generates significant value. This book will help you to develop data analysis skills using a hands-on approach and real-world data. You'll get up to speed with pandas 1.x in no time and build some software engineering skills in the process, vastly expanding your data science toolbox.

Apr 2021 26h 16m

Hands-On Data Analysis with Pandas

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Knowing how to work with data to extract insights generates significant value. This book will help you to develop data analysis skills using a hands-on approach and real-world data. You'll get up to speed with pandas 1.x in no time and build some software engineering skills in the process, vastly expanding your data science toolbox.

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Hands-On Data Analysis with Pandas

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Hands-On Data Analysis with Pandas

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Hands-On Data Analysis with Pandas

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Hands-On Data Analysis with Pandas

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