Master Data Analysis with Python – Selecting Subsets of Data

Master Data Analysis with Python – Selecting Subsets of Data targets those who want to completely master doing data analysis with pandas. This is the second course in the Master Data Analysis with Python series and provides extremely detailed coverage of how to do any type of subset selection within a pandas DataFrame or Series.

Exercises and a Free Certification Exam

Over 100 exercises with detailed solutions are available for you to practice. Additionally, there is a free challenging certification exam offered for those who want to validate their knowledge gained.

Expert Instructor

This course is taught by expert instructor Ted Petrou, author of the highly-rated text books Pandas Cookbook and Master Data Analysis with Python. Ted has taught over 1,000 hours of live in-person data science courses that use the pandas library. Pandas is a difficult library to use effectively and is often taught incorrectly with poor practices. Ted is extremely adept at using pandas and is known for developing best practices on how to use the library.

All of the material and exercises are written in Jupyter Notebooks available for you to download. This allows you to read the notes, run the code, and write solutions to the exercises all in a single place.

Become an Expert

This course targets those who have an interest in becoming experts and completely mastering the pandas library for data analysis in a professional environment. 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 in a professional environment.

The Master Data Analysis with Python Series

Selecting Subsets of Data is second in the Master Data Analysis with Python series which includes the following sequence of courses:

• Intro to Pandas

• Selecting Subsets of Data with Pandas

• Essential Pandas Commands

• Grouping Data with Pandas

• Time Series with Pandas

• Cleaning Data with Pandas

• Joining Data with Pandas

• Data Visualization

• Advanced Pandas

• Exploratory Data Analysis

This course assumes no previous pandas experience. The only prerequisite knowledge is to understand the fundamentals of Python.