Show raw data in Reports

How to change data aggregation in plots.

Pre-requisites:

• You know how to generate Reports with default parameters.

• You know how to pass custom parameters for Reports or Metrics.

Code example

You can refer to an example How-to-notebook:

https://github.com/evidentlyai/evidently/blob/main/examples/how_to_questions/how_to_use_aggregated_data_option.ipynbgithub.com

Default

Starting from version 0.3.2, all visualizations in Reports are aggregated by default. This helps reduce the size of the resulting HTML.

For example, you can create a custom Report:

report = Report(metrics=[
    RegressionPredictedVsActualScatter(),
    RegressionPredictedVsActualPlot()
])
report.run(reference_data=housing_ref, current_data=housing_cur)
report

Here is how the Scatter Plot in this Report will look:

RegressionPredictedVsActualScatter()

This does not affect Test Suites. All visualizations in Test Suites are already aggregated.

Non-aggregated plots for Reports

If you want to see non-aggregated plots, you can set the raw_data parameter as True in the render options.

You can set it on the Report level:

report = Report(
    metrics=[
      RegressionPredictedVsActualScatter(),
      RegressionPredictedVsActualPlot()
    ],
    options={"render": {"raw_data": True}}
  )
report.run(reference_data=housing_ref, current_data=housing_cur)
report

All plots in the Report will be non-aggregated. Here is how the Scatter Plot in this Report will look:

RegressionPredictedVsActualScatter()

Consider the data size. We recommend setting this option for smaller datasets or when you apply sampling. With non-aggregated plots, the HTML will contain all the data on individual data points. They may take significant time to load and be large in size.

Non-aggregated plots for Metrics

If you want to generate non-aggregated plots only for some visualizations, you can pass the option to the chosen Metrics:

report = Report(
    metrics=[
      RegressionPredictedVsActualScatter(options={"render": {"raw_data": True}}),
      RegressionPredictedVsActualPlot()
    ],
  )
report.run(reference_data=housing_ref, current_data=housing_cur)
report