This workshop will delve into common data processing and exploration techniques. We will use Pandas to perform data exploration in Python. Among others, we’ll demonstrate how to load data files, sort data, group variables, merge/join datasets and create common plots. Although not required, we recommend all participants to have a basic knowledge of Python.
This workshop introduces participants to Python’s NumPy, Pandas DataFrames, Matplotlib and StatsModels using an advertising dataset. Participants will use these tools to model (OLS) associations between advertising expenditures and product sales in example data. We will start with an introductory explanation of Anaconda and the Jupyter notebook environment (although not required for the participant, the instructor will be using these tools). We will proceed with topics including: reading data files; creation, indexing and slicing of Pandas DataFrames; creation and handling of Matplotlib objects; and creation and interpretation of models using Python’s StatsModels. Although not required, we recommend that participants have a basic knowledge of Python.
