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文件名:  Mastering pandas - Femi Anthony.pdf
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Master the features and capabilities of pandas, a data analysis toolkit for PythonAbout This Book
  • Master and optimally utilize the capabilities of Pandas for data analysis using IPython a rich interactive environment for Python
  • Understand data visualization by plotting data with matplotlib
  • Learn predictive analytics and machine learning using pandas and scikit-learn in a pragmatic manner

Who This Book Is ForThis book is intended for Python programmers, mathematicians, and analysts who already have a basic understanding of Python and wish to learn about its data analysis capabilities in depth.
What You Will Learn
  • Download, install, and set up Python, pandas, and related tools to perform data analysis for different operating environments
  • Practice using IPython as an interactive environment for doing data analysis using pandas
  • Master the core features of pandas used in data analysis
  • Get to grips with the more advanced features of pandas
  • Understand the basics of using matplotlib to plot data analysis results
  • Analyze real-world datasets using pandas
  • Acquire knowledge of using pandas for basic statistical analysis

In DetailPython is a ground breaking language for its simplicity and succinctness, allowing the user to achieve a great deal with a few lines of code, especially compared to other programming languages. The pandas brings these features of Python into the data analysis realm, by providing expressiveness, simplicity, and powerful capabilities for the task of data analysis. By mastering pandas, users will be able to do complex data analysis in a short period of time, as well as illustrate their findings using the rich visualization capabilities of related tools such as IPython and matplotlib.
This book is an in-depth guide to the use of pandas for data analysis, for either the seasoned data analysis practitioner or the novice user. It provides a basic introduction to the pandas framework, and takes users through the installation of the library and the IPython interactive environment. Thereafter, you will learn basic as well as advanced features, such as MultiIndexing, modifying data structures, and sampling data, which provide powerful capabilities for data analysis.

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