Python for Data Analysis

Python for Data Analysis, second edition, Wes McKinney, O’Reilly, 2017

Python is the best language for analyzing large data sets, and Pandas is the best library for doing this. Wes is the creator of Pandas, so he has an intimate knowledge of the subject.

Contents:
Python language basics, IPython, and Jupyter notebooks
Built-in data structures, functions, and files
NumPy basics: arrays and vectorized computation
Getting started with pandas
Data loading, storage, and file formats
Data cleaning and preparation
Data wrangling: join, combine, and reshape
Plotting and visualization
Data aggregation and group operations
Time series
Advanced pandas
Introduction to modeling libraries in Python
Data analysis examples
Advanced NumPy
More on the IPython system.

New for the second edition:
Updated for Python 3.6
Updated for latest pandas (0.20.3)
Revamped intro chapters including abridged Python language tutorial, and introductions to Jupyter and IPython
Reorganized pandas content to be digested more easily
New “Advanced pandas” chapter
New “Intro to Modeling Tools” chapter
Data analysis examples collected and organized in a dedicated chapter

Get it here at OPL     Amazon Review

Carleton Library     University of Ottawa

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