A data frame is a data structure specifically designed for effective management of tabular data, conceptually similar to a spreadsheet or a database table. Originating from the statistical computing language R, it has since gained widespread adoption in the data science community with Spark as well as the Pandas Python package.

Working knowledge of data frames and how to use them is helpful for any developer, as it provides an easy way to analyze, process and visualize data from a multitude of sources.

In this session we will be exploring some everyday use case scenarios for data frames, using Pandas and Jupyter.