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Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython [NOOK Book]

Overview

Python for Data Analysis is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you’ll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods ...

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

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Overview

Python for Data Analysis is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you’ll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.

Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It’s ideal for analysts new to Python and for Python programmers new to scientific computing.

  • Use the IPython interactive shell as your primary development environment
  • Learn basic and advanced NumPy (Numerical Python) features
  • Get started with data analysis tools in the pandas library
  • Use high-performance tools to load, clean, transform, merge, and reshape data
  • Create scatter plots and static or interactive visualizations with matplotlib
  • Apply the pandas groupby facility to slice, dice, and summarize datasets
  • Measure data by points in time, whether it’s specific instances, fixed periods, or intervals
  • Learn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples
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Product Details

  • ISBN-13: 9781449323615
  • Publisher: O'Reilly Media, Incorporated
  • Publication date: 10/8/2012
  • Sold by: Barnes & Noble
  • Format: eBook
  • Edition number: 1
  • Pages: 470
  • Sales rank: 510,575
  • File size: 7 MB

Meet the Author

Wes McKinney is the main author of pandas, the popular open source Python library for data analysis. Wes is an active speaker and participant in the Python and open source communities. He worked as a quantitative analyst at AQR Capital Management before founding an enterprise data analysis company, Lambda Foundry, in 2012. He graduated from MIT with an S.B. in Mathematics.

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Table of Contents

PrefaceChapter 1: PreliminariesChapter 2: Introductory ExamplesChapter 3: IPython: An Interactive Computing and Development EnvironmentChapter 4: NumPy Basics: Arrays and Vectorized ComputationChapter 5: Getting Started with pandasChapter 6: Data Loading, Storage, and File FormatsChapter 7: Data Wrangling: Clean, Transform, Merge, ReshapeChapter 8: Plotting and VisualizationChapter 9: Data Aggregation and Group OperationsChapter 10: Time SeriesChapter 11: Financial and Economic Data Applications Chapter 12: Advanced NumPyPython Language EssentialsColophon

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