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Python Data Analysis, Second Edition

You're reading from   Python Data Analysis, Second Edition Data manipulation and complex data analysis with Python

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787127487
Length 330 pages
Edition 2nd Edition
Languages
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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 (16) Chapters Close

Preface 1. Getting Started with Python Libraries 2. NumPy Arrays FREE CHAPTER 3. The Pandas Primer 4. Statistics and Linear Algebra 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

What you need for this book

The code examples in this book should work on most modern operating systems. For all chapters, Python > 3.5.0 and pip3 is required. You can download Python 3.5.x from https://www.python.org/downloads/. On this webpage, you can find installers for Windows and Mac OS X as well as source archives for Linux, Unix, and Mac OS X. You can find instructions for installing and using python for various operating systems on this webpage: https://docs.python.org/3/using/index.html. Most of the time, we need to run the following command with admin privileges to install various python libraries needed for the content of the book:

$ pip3 install <some library>

The following is a list of python libraries used for the examples:

  • numpy
  • scipy
  • pandas
  • matplotlib
  • ipython
  • jupyter
  • notebook
  • readline
  • scikit-learn
  • rpy2
  • Quandl
  • statsmodels
  • feedparser
  • beautifulsoup4
  • lxml
  • numexpr
  • tables
  • openpyxl
  • xlsxwriter
  • xlrd
  • pony
  • dataset
  • pymongo
  • redis
  • python3-memcache
  • cassandra-driver
  • sqlalchemy
  • nltk
  • networkx
  • theanets
  • nose_parameterized
  • pydot2
  • deap
  • JPype1
  • gprof2dot
  • line_profiler
  • cython
  • cytoolz
  • joblib
  • bottleneck
  • jug
  • mpi4py

Apart from python libraries we also need the following software:

  • Redis server
  • Cassandra
  • Java 8
  • Graphviz
  • Octave
  • R
  • SWIG
  • PCRE
  • Boost
  • gfortran
  • MPI

Usually, the latest version available should work for the above mentioned libraries and software.

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:

   $ pip3 uninstall <some library>
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