Python Data Analytics: With Pandas, NumPy, and Matplotlib

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2023

F. NelliPython Data Analyticshttps://doi.org/10.1007/978-1-4842-9532-8_6

6. pandas in Depth: Data Manipulation

Fabio Nelli¹  

(1)

Rome, Italy

 

In the previous chapter, you saw how to acquire data from data sources such as databases and files. Once you have the data in the dataframe format, they are ready to be manipulated. It’s important to prepare the data so that they can be more easily subjected to analysis and manipulation. Especially in preparation for the next phase, the data must be ready for visualization.

This chapter goes in depth into the functionality that the pandas library offers for this stage of data analysis. The three phases of data manipulation ...