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Learning Pandas

You're reading from   Learning Pandas Get to grips with pandas - a versatile and high-performance Python library for data manipulation, analysis, and discovery

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Product type Paperback
Published in Apr 2015
Publisher Packt
ISBN-13 9781783985128
Length 504 pages
Edition 1st 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 (14) Chapters Close

Preface 1. A Tour of pandas FREE CHAPTER 2. Installing pandas 3. NumPy for pandas 4. The pandas Series Object 5. The pandas DataFrame Object 6. Accessing Data 7. Tidying Up Your Data 8. Combining and Reshaping Data 9. Grouping and Aggregating Data 10. Time-series Data 11. Visualization 12. Applications to Finance Index

Summary


Visualizing your data is one of the best ways to quickly understand the story that is being told with the data. Python, pandas, and matplotlib (and a few other libraries) provide a means of very quickly, and with a few lines of code, getting the gist of what you are trying to discover, as well as the underlying message (and displaying it beautifully too).

In this chapter, we examined many of the most common means of visualizing data from pandas. There are also a lot of interesting visualizations that were not covered, and indeed, the concept of data visualization with pandas and/or Python is the subject of entire texts, but I believe this chapter provides a much-needed reference to get up and going with the visualizations that provide most of what is needed.

In the next and final chapter of the book, we will look at a few applied applications of pandas, which also demonstrates visualizing real-world information.

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