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Learning pandas

You're reading from   Learning pandas High performance data manipulation and analysis using Python

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Product type Paperback
Published in Jun 2017
Publisher
ISBN-13 9781787123137
Length 446 pages
Edition 2nd Edition
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Author (1):
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Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
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Table of Contents (16) Chapters Close

Preface 1. pandas and Data Analysis FREE CHAPTER 2. Up and Running with pandas 3. Representing Univariate Data with the Series 4. Representing Tabular and Multivariate Data with the DataFrame 5. Manipulating DataFrame Structure 6. Indexing Data 7. Categorical Data 8. Numerical and Statistical Methods 9. Accessing Data 10. Tidying Up Your Data 11. Combining, Relating, and Reshaping Data 12. Data Aggregation 13. Time-Series Modelling 14. Visualization 15. Historical Stock Price Analysis

IPython and Jupyter Notebook

So far we have executed Python from the command line or Terminal. This is the default Read-Eval-Print-Loop (REPL) that comes with Python. This can be used to run all the examples in this book, but the book will use IPython for statements in the text and the code package Jupyter Notebook. Let's take a brief look at both.

IPython

IPython is an alternate shell for interactively working with Python. It provides several enhancements to the default REPL provided by Python.

If you want to learn about IPython in more detail, check out the documentation at https://ipython.org/ipython-doc/3/interactive/tutorial.html

To start IPython, simply execute the ipython command from the command line/Terminal...

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