Abstract
One of the really big growth areas for Python is in the sciences, where data analysis is a huge component. Happily, Python includes a Swiss Army tool for data analysis, namely the pandas package, which can be installed from the PyPi repository with pip. pandas provides a lot of the data handling and data processing tools that you may be accustomed to if you come from an R background. Several new data types are introduced, along with additional functionality to handle the actual data processing in a very efficient manner. It achieves this efficiency by building on the functionality provided by the numpy package.
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© 2016 Joey Bernard
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Bernard, J. (2016). Python Data Analysis with pandas. In: Python Recipes Handbook. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-0241-8_5
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DOI: https://doi.org/10.1007/978-1-4842-0241-8_5
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Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-0242-5
Online ISBN: 978-1-4842-0241-8
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