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Python Data Mining Quick Start Guide

Python Data Mining Quick Start Guide

By : Greeneltch
5 (10)
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Python Data Mining Quick Start Guide

Python Data Mining Quick Start Guide

5 (10)
By: Greeneltch

Overview of this book

Data mining is a necessary and predictable response to the dawn of the information age. It is typically defined as the pattern and/ or trend discovery phase in the data mining pipeline, and Python is a popular tool for performing these tasks as it offers a wide variety of tools for data mining. This book will serve as a quick introduction to the concept of data mining and putting it to practical use with the help of popular Python packages and libraries. You will get a hands-on demonstration of working with different real-world datasets and extracting useful insights from them using popular Python libraries such as NumPy, pandas, scikit-learn, and matplotlib. You will then learn the different stages of data mining such as data loading, cleaning, analysis, and visualization. You will also get a full conceptual description of popular data transformation, clustering, and classification techniques. By the end of this book, you will be able to build an efficient data mining pipeline using Python without any hassle.
Table of Contents (9 chapters)
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Popular types of plots for visualizing data

This section will introduce some of the most common plotting routines that are used by analysts in the data mining field. These are the plot types that I see projected on screens in conference rooms on a daily basis at my workplace. The routines in Seaborn all follow similar arguments, conventions, and usage, so after reading through the examples in this section, you should easily be able to build any plot that Seaborn has to offer with ease.

I recommend that you take a look at the example gallery on Seaborn's website. It's a good way to find the plot that you're looking for. The front page includes fully-rendered versions of each plot type and it is available at https://seaborn.pydata.org/examples/index.html.

Scatter plots...

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