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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

Summary

In this chapter, we installed the Anaconda Scientific version of Python. This also installs pandas and Jupyter Notebook, setting you right up with an environment for performing data manipulation and analysis, along with creating notebooks to visualize, present, and share your analyses.

We also took an introductory look at the pandas Series and DataFrame objects, demonstrating some of the fundamental capabilities. This exposition showed you how to perform a few basic operations that you can use to get up and running with pandas prior to diving in and learning all the details.

In the next several chapters, we will dive deep into the operations of the Series and DataFrame, with the next chapter focusing specifically on the Series.

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