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Hands-On Data Science with Anaconda

You're reading from   Hands-On Data Science with Anaconda Utilize the right mix of tools to create high-performance data science applications

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788831192
Length 364 pages
Edition 1st Edition
Languages
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Authors (2):
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James Yan James Yan
Author Profile Icon James Yan
James Yan
Yuxing Yan Yuxing Yan
Author Profile Icon Yuxing Yan
Yuxing Yan
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Table of Contents (15) Chapters Close

Preface 1. Ecosystem of Anaconda FREE CHAPTER 2. Anaconda Installation 3. Data Basics 4. Data Visualization 5. Statistical Modeling in Anaconda 6. Managing Packages 7. Optimization in Anaconda 8. Unsupervised Learning in Anaconda 9. Supervised Learning in Anaconda 10. Predictive Data Analytics – Modeling and Validation 11. Anaconda Cloud 12. Distributed Computing, Parallel Computing, and HPCC 13. References 14. Other Books You May Enjoy

Introduction to the Python pandas package

The Python pandas package is very useful when dealing with data. The pandas package is a wonderful tool for data preprocessing, which is essential for data analysis. There is a humorous way of describing the importance of data cleaning: "A data scientist spends 80% of their time cleaning the data and the other 20% complaining about cleaning the data". To test if the package is preinstalled, we can type import pandas as pd after we launch Python. If we don't see any error messages, it means that the package was preinstalled. If we do, then we can use conda install pandas to install the package. To find all available functions, we could use the following three lines of Python code:

To find out about the usage or examples of individual functions, the help() function can be used. For example, for the to_pickle functionality...

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