Python Data Analytics: With Pandas, NumPy, and Matplotlib

© Fabio Nelli 2018

Fabio NelliPython Data Analyticshttps://doi.org/10.1007/978-1-4842-3913-1_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.

In this chapter you will go in depth into the functionality that the pandas library offers for this stage of data analysis. The three phases of data manipulation will be treated individually, illustrating the various operations ...