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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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Table of Contents (16) Chapters Close

Preface 1. Getting Started with Python Libraries FREE CHAPTER 2. NumPy Arrays 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

Installing and exploring Pandas

The minimal dependency set requirements for Pandas is given as follows:

  • NumPy: This is the fundamental numerical array package that we installed and covered extensively in the preceding chapters
  • python-dateutil: This is a date handling library
  • pytz: This handles time zone definitions

This list is the bare minimum; a longer list of optional dependencies can be located at http://pandas.pydata.org/pandas-docs/stable/install.html. We can install Pandas via PyPI with pip or easy_install, using a binary installer, with the aid of our operating system package manager, or from the source by checking out the code. The binary installers can be downloaded from http://pandas.pydata.org/getpandas.html.

The command to install Pandas with pip is as follows:

$ pip3 install pandas rpy2

rpy2 is an interface to R and is required because rpy is being deprecated. You may have to prepend the preceding command with sudo if your user account doesn't have sufficient rights...

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