Description
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Up to date for Python 3.6, the second one 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 can learn the up to date versions of pandas, NumPy, IPython, and Jupyter in the process., Written by Wes McKinney, the writer of the Python pandas project, this book is a practical, brand new 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 to be had on GitHub., Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get began with data analysis tools in the pandas library Use flexible tools to load, clean, change into, 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 Discover ways to solve real-world data analysis problems with thorough, detailed examples
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