Course Contents

  • 14 Jupyter Notebooks with text, code, exercises, case studies, and solutions

  • 7 hours of video

  • 85 exercises with detailed solutions

  • 170-page pdf of all course material

What you'll learn

Extremely thorough coverage of the most essential DataFrame and Series attributes and methods

  • Aggregation and Non-Aggregation Methods

  • String-only methods with the str accessor

  • Datetime-only methods with the dt accessor

  • Complete coverage of the many available data types

  • How to handle missing values

  • Nuisance columns, assigning subsets of data, uniqueness, and much, much more

Course Description

Master Data Analysis with Python - Essential Pandas Commands is part of the book Master Data Analysis with Python by Ted Petrou.

This course provides some of the most comprehensive and rigorous coverage available on how to best use the most essential commands of the Series and DataFrame in the pandas library to do data analysis.

This course targets those who have an interest in becoming experts and completely mastering the pandas library for data analysis in a professional environment. The pandas library is easy to misuse as it has an abundance of quirks that are not covered well in other courses. Tutorials abound with incorrect or misleading information on how to use pandas properly. This course provides best practices for each command and has 85 exercises to test your ability and reinforce your knowledge.

This course does not cover all of the pandas library, just a small and fundamental portion of it. If you are looking for a brief introduction of the entire pandas library, this course is not it. It takes many dozens of hours, lots of practice, and rigorous understanding to be successful using pandas for data analysis.

This course is one part of the 10 total parts of the Master Data Analysis with Python series. You may purchase all 10 parts along with the book Exercise Python for $100. This is a 50% reduction in price over what the cost would be if each part were purchased individually. 

This course is taught by expert instructor Ted Petrou, author of Pandas Cookbook, Master Data Analysis with Python, and Exercise Python.

Get Maximum Value with the Bundle!

  • Free

    FreeComplete Master Data Analysis with Python Bundle

    Purchase the entire bundle which includes Exercise Python, Master Data Analysis with Python and all video courses for each for only $100. (Some videos are still being created)
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Course Curriculum

  • 1
    Introduction
  • 2
    Series Attributes and Methods
  • 3
    DataFrame Attributes and Methods
    • 06 Dataframe Attributes and Methods
    • 06_Exercise Solutions
    • 07_1 DataFrame Aggregation Methods
    • 07_2 DataFrame Non-Aggregation Methods
    • 07_3 Nuisance Columns
    • 07_Exercise Solutions
    • 08_1 DataFrame Methods More - Handling Missing Data
    • 08_2 DataFrame Methods More 2 Sorting
    • 08_3 Finding the index of the maximum or minimum
    • 08_4 Dropping and Renaming Columns and Rows
    • 08_5 Adding New Columns
    • 08_Exercise Solutions
    • 09_1 DataFrame Methods more II
    • 09_2 The copy method
    • 09_3 Inserting and Popping Columns
    • 09_4 The replace Method
    • 09_5 Finding the Maximum per Group
    • 09_Exercise Solutions
  • 4
    Changing Data Types
    • 10_1 Numeric and Boolean Data Types
    • 10_2 Object Data Types
    • 10_3 Datetime64 Data Type
    • 10_4 Converting Strings to Numeric
    • 10_5 DataFrame Data Type Conversion
    • 10_6 Reading in Data with Known Missing Values
    • 10_7 Timedelta64 Data Type
    • 10_8 Data Type Summary Table
    • 10_Exercise Solutions
  • 5
    Assigning Subsets of Data
    • 11_1 Assigning Subsets with loc and iloc
    • 11_2 Boolean Selection Assignment
    • 11_Exercise Solutions
  • 6
    Case Studies
    • Case Study - Calculating Normality of Stock Market Returns
    • Case Study - Do Employees with More Experience make more Money?

Master Data Analysis with Python - Essential Pandas Commands

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