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Mastering pandas. - Second Edition

You're reading from  Mastering pandas. - Second Edition

Product type Book
Published in Oct 2019
Publisher
ISBN-13 9781789343236
Pages 674 pages
Edition 2nd Edition
Languages
Author (1):
Ashish Kumar Ashish Kumar
Profile icon Ashish Kumar

Table of Contents (21) Chapters

Preface Section 1: Overview of Data Analysis and pandas
Introduction to pandas and Data Analysis Installation of pandas and Supporting Software Section 2: Data Structures and I/O in pandas
Using NumPy and Data Structures with pandas I/Os of Different Data Formats with pandas Section 3: Mastering Different Data Operations in pandas
Indexing and Selecting in pandas Grouping, Merging, and Reshaping Data in pandas Special Data Operations in pandas Time Series and Plotting Using Matplotlib Section 4: Going a Step Beyond with pandas
Making Powerful Reports In Jupyter Using pandas A Tour of Statistics with pandas and NumPy A Brief Tour of Bayesian Statistics and Maximum Likelihood Estimates Data Case Studies Using pandas The pandas Library Architecture pandas Compared with Other Tools A Brief Tour of Machine Learning Other Books You May Enjoy

Supervised learning algorithms

We will take a brief tour of some well-known supervised learning algorithms and see how we can apply them to the Titanic survival prediction problem described earlier.

Constructing a model using Patsy for scikit-learn

Before we start our tour of the machine learning algorithms, we need to know a little bit about the Patsy library. We will make use of Patsy to design features that will be used in conjunction with scikit-learn. Patsy is a package for creating what is known as design matrices. These design matrices are transformations of the features in our input data. The transformations are specified by expressions known as formulas, which correspond to a specification of what features we wish...

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