ydata-eda-profiling

Generate reproducible EDA reports for a pandas DataFrame by running a script that uses ydata-profiling with fixed seeds and optional sampling, ensuring consistent results across runs.

The best way to compare two datasets using ydata-profiling is to generate ProfileReport outputs for each dataset and save the results as HTML files for auditing and direct comparison.

Yes, you can use sampling to speed up ydata-profiling on large datasets; the script applies sampling with deterministic seeds to create consistent and manageable EDA reports.

Yes, this EDA reporting tool requires pandas to process your data, as it relies on pandas DataFrames as the input format for generating ydata-profiling reports.

You can export a ydata-profiling ProfileReport to HTML by using the provided script to process your pandas DataFrame and save the generated EDA summary as an HTML file.

You should use fixed seeds when generating data profiling reports to ensure reproducibility, keeping the sampling consistent and the EDA outputs identical across multiple runs.