Learn how to perform various data science tasks on real-world datasets using pandas. Discover best practices for tasks such as removing columns, comparing groups, handling missing values, using string methods, and more. The course aims to teach you how to avoid common pandas and data science pitfalls. Intended for individuals interested in enhancing their data science skills using pandas.
Overview
Syllabus
pandas best practices (1/10): Introducing the dataset.
pandas best practices (2/10): Removing columns.
pandas best practices (3/10): Comparing groups.
pandas best practices (4/10): Examining relationships.
pandas best practices (5/10): Handling missing values.
pandas best practices (6/10): Using string methods.
pandas best practices (7/10): Combining dates and times.
pandas best practices (8/10): Plotting a time series.
pandas best practices (9/10): Creating useful plots.
pandas best practices (10/10): Fixing bad data.
Taught by
Data School
