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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

Up and Running with pandas

In this chapter, we will cover how to install pandas and start using its basic functionality. The content of the book is provided as IPython and Jupyter notebooks, and hence we will also take a quick look at using both of those tools.

This book will utilize the Anaconda scientific Python distribution from Continuum. Anaconda is a popular Python distribution with both free and paid components. Anaconda provides cross-platform support, including Windows, Mac, and Linux. The base distribution of Anaconda installs pandas, IPython and Jupyter Notebook, thereby making it almost trivial to get started.

In this chapter will cover the following topics:

  • Installation of Anaconda, pandas, and IPython/Jupyter Notebook
  • Using IPython and Jupyter Notebook
  • Jupyter and its notebooks
  • Setting up your pandas environments
  • A quick introduction to the pandas Series and DataFrame...
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