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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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Tools
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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

Chapter 6. Accessing Data

pandas is a tool that is used to manipulate and analyze data. But where does this data come from? It is almost universal that any pandas application will start by loading data from an outside source. As pandas is built on Python, you can use any means available in Python to retrieve data from outside the application. This really makes the possibility of the data that can be accessed unlimited, including files, excel spreadsheets, web sites and services, databases, and cloud services.

However, using Python to load data will require you to convert Python objects into pandas Series or DataFrame objects, increasing the complexity of your code. Fortunately, over the evolution of pandas, it has become apparent that there is a frequently used set of data access patterns, as well as data formats that were so commonly used, that direct support for them was added into the core of pandas. These often make retrieving data from outside sources, directly as a pandas...

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