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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 2. NumPy Arrays FREE CHAPTER 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

What you need for this book

The code examples in this book should work on most modern operating systems. For all chapters, Python 2 and pip is required. To install Python, go to https://wiki.python.org/moin/BeginnersGuide/Download. To install pip, go to http://pip.readthedocs.org/en/latest/installing.html. Instructions to install software are given throughout the chapters. Most of the time, we need to run the following command with admin privileges:

    $ pip install <some software>

The following is a list of software used for the examples and versions used for testing purposes:

  • NumPy 1.8.1
  • SciPy 0.14.0
  • matplotlib 1.3.1
  • IPython 2.0.0
  • pandas Version 0.13.1
  • tables 3.1.1
  • numexpr 2.4
  • openpyxl 2.0.3
  • XlsxWriter 0.5.5
  • xlrd 0.9.3
  • feedparser 5.1.3
  • Beautiful Soup 4.3.2
  • StatsModels 0.6.0
  • SQLAlchemy 0.9.6
  • Pony 0.5.1
  • dataset 0.5.4
  • MongoDB 2.6.3
  • PyMongo 2.7.1
  • Redis server 2.8.12
  • Redis 2.10.1
  • Cassandra 2.0.9
  • Java 7
  • NLTK 2.0.4
  • scikit-learn 0.15.0
  • NetworkX 1.9
  • DEAP 1.0.1
  • theanets 0.2.0
  • Graphviz 2.36.0
  • pydot2 1.0.33
  • Octave 3.8.0
  • R 3.1.1
  • rpy2 2.4.2
  • JPype 0.5.5.2
  • Java 7
  • SWIG 3.02
  • PCRE 8.35
  • Boost 1.56.0
  • gfortran 4.9.0
  • GAE for Python 2.7
  • gprof2dot 2014.08.05
  • line_profiler beta
  • Cython 0.20.0
  • cytoolz 0.7.0
  • Joblib 0.8.2
  • Bottleneck 0.8.0
  • Jug 0.9.3
  • MPI 1.8.1
  • mpi4py 1.3.1

Of course, it's not necessary for you to have the same version of the software. Usually, the latest version available should work.

Note

Some of the software listed are used for a single example; therefore, please check first whether the example is relevant for you before installing the software.

To uninstall Python packages installed with pip, use the following command:

   $ pip uninstall <some software>
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