Table of Contents

• Introduction to Pandas
  • • Introduction to Pandas
    • Series
    • Data Frames
    • Missing Data
    • GroupBy
    • Merging,Joining,and Concatenating
    • Operations
    • Data Input and Output
  • Background
  • Features

Introduction to Pandas

In this section of the course we will learn how to use pandas for data analysis. You can think of pandas as an extremely powerful version of Excel, with a lot more features. In this section of the course, you should go through the notebooks in this order:

• Introduction to Pandas

• Series

• Data Frames

• Missing Data

• GroupBy

• Merging,Joining,and Concatenating

• Operations

• Data Input and Output

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Background

Panda is named after "Panel-Data" and was created by Wes McKinney. Pandas was first created to help working with datasets in Python for McKinney's work in finance at his place of employment.

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Features

• A fast and efficient DataFrame object for data manipulation with integrated indexing.
• Tools for reading and writing data between in-memory data structures and different formats:
  • CSV and text files, Microsoft Excel, SQL databases, and the fast HDF5 format, and much more!
• Great interaction with Python Data Visualization libraries
• Highly optimized for performance, with critical code path written in Cython or C
• Aggregating or transforming data with a powerful group by engine

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