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

© Robert Johansson 2019

Robert JohanssonNumerical Python https://doi.org/10.1007/978-1-4842-4246-9_12

12. Data Processing and Analysis

Robert Johansson¹ 

(1)

Urayasu-shi, Chiba, Japan

 

In the last several chapters, we have covered the main topics of traditional scientific computing. These topics provide a foundation for most computational work. Starting with this chapter, we move on to explore data processing and analysis, statistics, and statistical modeling. As the first step in this direction, we look at the data analysis library pandas. 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 process¹ of cleansing ...