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Mastering pandas

You're reading from   Mastering pandas A complete guide to pandas, from installation to advanced data analysis techniques

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Product type Paperback
Published in Oct 2019
Publisher
ISBN-13 9781789343236
Length 674 pages
Edition 2nd Edition
Languages
Tools
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Author (1):
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Ashish Kumar Ashish Kumar
Author Profile Icon Ashish Kumar
Ashish Kumar
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Table of Contents (21) Chapters Close

Preface 1. Section 1: Overview of Data Analysis and pandas FREE CHAPTER
2. Introduction to pandas and Data Analysis 3. Installation of pandas and Supporting Software 4. Section 2: Data Structures and I/O in pandas
5. Using NumPy and Data Structures with pandas 6. I/Os of Different Data Formats with pandas 7. Section 3: Mastering Different Data Operations in pandas
8. Indexing and Selecting in pandas 9. Grouping, Merging, and Reshaping Data in pandas 10. Special Data Operations in pandas 11. Time Series and Plotting Using Matplotlib 12. Section 4: Going a Step Beyond with pandas
13. Making Powerful Reports In Jupyter Using pandas 14. A Tour of Statistics with pandas and NumPy 15. A Brief Tour of Bayesian Statistics and Maximum Likelihood Estimates 16. Data Case Studies Using pandas 17. The pandas Library Architecture 18. pandas Compared with Other Tools 19. A Brief Tour of Machine Learning 20. Other Books You May Enjoy

pandas-datareader

We can use pandas to not only read data from local CSV or text files but also from various popular remote data sources such as Yahoo Finance, World Bank, and so on. Without any support from pandas, this would have been tedious and we would have to resort to web scraping. This simple and powerful functionality is provided through the pandas-datareader.

It provides us with a direct way of connecting through various data sources from the comfort of the pandas ecosystem without having to delve into the complexity of HTML/JavaScript code where data is enmeshed. These data sources can be accessed by providing the source name and data code. Only a subset of the data can be obtained.

Let's delve deeper and see how we can use it:

  1. Install pandas-datareader through pip using the following command:
pip install pandas-datareader  

You can also install it through conda...

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