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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 2. Installing pandas FREE CHAPTER 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

Chapter 5. The pandas DataFrame Object

The pandas DataFrame object extends the capabilities of the Series object into two-dimensions. A Series object adds an index to a NumPy array but can only associate a single data item per index label, a DataFrame integrates multiple Series objects by aligning them along common index labels. This automatic alignment by index label provides a seamless view across all the Series at each index label that has the appearance of a row in a table.

A DataFrame object can be thought of as a dictionary-like container of one or more Series objects, or as a spreadsheet, probably the best description for those new to pandas is to compare a DataFrame object to a relational database table. However, even that comparison is limited, as a DataFrame object has very distinct qualities (such as automatic data alignment of series) that make it much more capable for exploratory data analysis than either a spreadsheet or relational database table.

Because of the increased...

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