Data Manipulation in Python

This Track is taught using Python. You will learn how to use Python libraries such as pandas and NumPy to manipulate data in DataFrames to perform data analysis.

This Track will help those who are working in positions such as data analysts, data engineers, software developers, and machine learning engineers who need to work with and analyze data.

This Track will teach you many skills related to manipulating and analyzing data with Python, such as extracting, filtering, transforming, joining, merging, and creating visualizations. By the end of the Track, you will be able to use pandas and NumPy to quickly and accurately analyze data.

This track is self-paced so users can spend as long or as little time as they like working through exercises and courses. However, the Track usually takes 16 hours to complete, as it consists of several courses.

A skill track is designed to teach users how to use a specific programming language, library, or technology to develop skills. A career track is designed to teach users specific job skills and prepare them for job interviews and roles in a specific field.

The datasets used will be mostly created from real-world examples, and they will always be provided as part of the Track.

The Track courses will cover topics such as extracting, filtering, transforming data in DataFrames; combining, merging, and creating visualizations; and working with NumPy arrays and using New York City's tree census data to create, sort, filter, and update arrays.