Python for data analysis : data wrangling with pandas, NumPy, and IPython / Wes McKinney

Format:

Book

Author/Creator:

McKinney, Wes, author.

Language:

English

Subjects (All):

Python (Computer program language).

Programming languages (Electronic computers).

Data mining.

Physical Description:

1 online resource (529 pages)

Edition:

Second edition.

Other Title:

Data wrangling with Pandas, NumPy, and IPython

Place of Publication:

Beijing : O'Reilly, [2018]

System Details:

text file

Summary:

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

Contents:

Preliminaries

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 libraies in Python

Data analysis examples

Advanced NumPy

More on the IPython system.

Notes:

Includes bibliographical references and index.

based on online resource; title from PDF title page (ebrary, viewed October 6, 2017).

ISBN:

9781491957615

1491957611

9781491957653

1491957654

9781491957660

1491957662

9781491957639

1491957638

OCLC:

1005138881