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Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
book

Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

by Robert Johansson
September 2024
Intermediate to advanced content levelIntermediate to advanced
501 pages
17h 6m
English
Apress
Content preview from Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2024
R. JohanssonNumerical Pythonhttps://doi.org/10.1007/979-8-8688-0413-7_12

12. Data Processing and Analysis

Robert Johansson1  
(1)
Urayasu-shi, Chiba, Japan
 

The last several chapters covered the main topics of traditional scientific computing. These topics provide a foundation for most computational work. Starting with this chapter, let’s move on to explore data processing and analysis, statistics, and statistical modeling. First, we look at the Pandas data analysis library. This library provides convenient data structures for representing series and tables of data and makes it easy to transform, split, merge, and convert data. These are important steps in the ...

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