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Getting Started with Python Data Analysis

You're reading from   Getting Started with Python Data Analysis Learn to use powerful Python libraries for effective data processing and analysis

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781785285110
Length 188 pages
Edition 1st Edition
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introducing Data Analysis and Libraries FREE CHAPTER 2. NumPy Arrays and Vectorized Computation 3. Data Analysis with Pandas 4. Data Visualization 5. Time Series 6. Interacting with Databases 7. Data Analysis Application Examples 8. Machine Learning Models with scikit-learn Index

An overview of the Pandas package

Pandas is a Python package that supports fast, flexible, and expressive data structures, as well as computing functions for data analysis. The following are some prominent features that Pandas supports:

  • Data structure with labeled axes. This makes the program clean and clear and avoids common errors from misaligned data.
  • Flexible handling of missing data.
  • Intelligent label-based slicing, fancy indexing, and subset creation of large datasets.
  • Powerful arithmetic operations and statistical computations on a custom axis via axis label.
  • Robust input and output support for loading or saving data from and to files, databases, or HDF5 format.

Related to Pandas installation, we recommend an easy way, that is to install it as a part of Anaconda, a cross-platform distribution for data analysis and scientific computing. You can refer to the reference at http://docs.continuum.io/anaconda/ to download and install the library.

After installation, we can use it like other Python...

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