Book Image

Python Data Science Essentials

By : Alberto Boschetti, Luca Massaron
Book Image

Python Data Science Essentials

By: Alberto Boschetti, Luca Massaron

Overview of this book

The book starts by introducing you to setting up your essential data science toolbox. Then it will guide you across all the data munging and preprocessing phases. This will be done in a manner that explains all the core data science activities related to loading data, transforming and fixing it for analysis, as well as exploring and processing it. Finally, it will complete the overview by presenting you with the main machine learning algorithms, the graph analysis technicalities, and all the visualization instruments that can make your life easier in presenting your results. In this walkthrough, structured as a data science project, you will always be accompanied by clear code and simplified examples to help you understand the underlying mechanics and real-world datasets.
Table of Contents (13 chapters)

Selected graphical examples with pandas

Though many machine learning algorithms, with appropriately set hyper-parameters, can optimally learn how to map your data with respect to your target outcome, their performance can be further improved by knowing about hidden and subtle problems in data. It is not simply a matter of detecting any missing or outlying case. Sometimes, it is paramount to clarify whether there are any groups or unusual distributions in the data(for instance, multimodal distributions). Clear data plots that explicate the relationship between variables can also lead to the creation of newer and better features that can predict more than the existing ones.

The practice that was just described is called Explorative Data Analysis, which can be effective if it has the following characteristics:

  • It should be fast, allowing you to explore, develop new ideas and test them, and restart with a new exploration and fresh ideas.

  • It should be graphic in order to better represent data as...