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Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

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Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process.

Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.

  • Use the IPython shell and Jupyter notebook for exploratory computing
  • Learn basic and advanced features in NumPy (Numerical Python)
  • Get started with data analysis tools in the pandas library
  • Use flexible tools to load, clean, transform, merge, and reshape data
  • Create informative visualizations with matplotlib
  • Apply the pandas groupby facility to slice, dice, and summarize datasets
  • Analyze and manipulate regular and irregular time series data
  • Learn how to solve real-world data analysis problems with thorough, detailed examples
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Practical Data Wrangling: Expert techniques for transforming your raw data into a valuable source for analytics
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  • Work with different types of datasets, and reshape the layout of your data to make it easier for analysis
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We, NumPy users, live in exciting times. New NumPy-related developments seem to come to our attention every week or maybe even daily. When this book was being written, NumPy Foundation of Open Code for Usable Science was created. The Numba project—NumPy-aware, dynamic Python compiler using LLVM—was announced. Also,...
Python Data Analysis Cookbook
Python Data Analysis Cookbook

Key Features

  • Analyze Big Data sets, create attractive visualizations, and manipulate and process various data types
  • Packed with rich recipes to help you learn and explore amazing algorithms for statistics and machine learning
  • Authored by Ivan Idris, expert in python programming and proud...
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