The fg-data-profiling package generates an exploratory data analysis (EDA) report with a few lines of code. The report provides a dataset and column-level analysis, including plots and summary statistics, to help you quickly understand your dataset. These reports can be exported to HTML or JSON so you can share them with other stakeholders.

By the end of this video course, you’ll understand that:

  • fg-data-profiling generates interactive reports containing EDA results, including summary statistics, visualizations, correlation matrices, and data quality warnings from DataFrames.
  • ProfileReport creates a profile you can save with .to_file() for HTML or JSON export, or display inline with .to_notebook_iframe().
  • Setting tsmode=True and specifying a date column with sortby enables time series analysis, including stationarity tests and seasonality detection.
  • The .compare() method generates side-by-side reports highlighting distribution shifts and statistical differences between datasets.

To get the most out of this course, you’ll benefit from having knowledge of pandas.

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