CDVS Workshop: Python for Data Science: Pandas 103
Data exploration In Python using grouping and aggregation. This is an intermediate-level, live teaching session where you will learn how to use the Pandas module for exploring tablular (spreadsheet) data using the groupby() and pivot_table() functions, as well as some visualizations of results. Python can be a great option for exploration, analysis and visualization of tabular data, such as spreadsheets and CSV files, if you know which tools to use and how to get started. This workshop builds upon the introductory Pandas workshops I gave in Fall 2019 and Spring 2020. (Code repository. See below for recordings.) In Pandas 101, I covered the very basics of how to access your data in a Panda DataFrame and do some basic plotting. In Pandas 102, I introduced how to get data into a "tidy" form, and merge datasets (like doing an SQL JOIN). In this Pandas 103, I will show you some of the way you can explore patterns in data by aggretating across categories and time. This is similar to the process of data exploration in Tableau, but here with Python, Pandas and JupyterLab.