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Python Data Analysis

You're reading from   Python Data Analysis Learn how to apply powerful data analysis techniques with popular open source Python modules

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Product type Paperback
Published in Oct 2014
Publisher
ISBN-13 9781783553358
Length 348 pages
Edition 1st Edition
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Toc

Table of Contents (17) Chapters Close

Preface 1. Getting Started with Python Libraries FREE CHAPTER 2. NumPy Arrays 3. Statistics and Linear Algebra 4. pandas Primer 5. Retrieving, Processing, and Storing Data 6. Data Visualization 7. Signal Processing and Time Series 8. Working with Databases 9. Analyzing Textual Data and Social Media 10. Predictive Analytics and Machine Learning 11. Environments Outside the Python Ecosystem and Cloud Computing 12. Performance Tuning, Profiling, and Concurrency A. Key Concepts
B. Useful Functions C. Online Resources
Index

A tour of scikit-learn

In the previous chapter, Chapter 9, Analyzing Textual Data and Social Media, we installed scikit-learn. With the pkg_check.py file in this book's code bundle, we can print the following scikit-learn module descriptions:

sklearn version 0.15.0
sklearn.__check_build DESCRIPTION Module to give helpful messages to the user that did not compile the scikit properly. PACKAGE CONTENTS _check_build setup FUNCTI
sklearn.cluster DESCRIPTION The :mod:`sklearn.cluster` module gathers popular unsupervised clustering algorithms. PACKAGE CONTENTS _feature_agglomeration _h
sklearn.covariance DESCRIPTION The :mod:`sklearn.covariance` module includes methods and algorithms to robustly estimate the covariance of features given a set
sklearn.cross_decomposition 
sklearn.datasets DESCRIPTION The :mod:`sklearn.datasets` module includes utilities to load datasets, including methods to load and fetch popular reference da
sklearn.decomposition DESCRIPTION The :mod:`sklearn.decomposition...
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