SummaryTablePlotter#

class openstef_beam.analysis.plots.summary_table_plotter.SummaryTablePlotter(data: DataFrame)[source]

Bases: object

Creates formatted HTML tables from evaluation metrics data.

This plotter transforms evaluation metrics into HTML tables suitable for reports and dashboards. The tables help answer questions like:

  • Which model has the best overall performance across all metrics?

  • How do metric values compare between different targets or runs?

  • What are the summary statistics for forecast accuracy?

The generated tables include:

  • Styled headers and borders for professional appearance

  • Left-aligned text for readability

  • Consistent formatting across all metrics

  • HTML output suitable for embedding in reports

Example

Creating a summary table from metrics

>>> import pandas as pd
>>> metrics_data = pd.DataFrame({
...     'Model': ['XGBoost', 'Random Forest', 'LSTM'],
...     'RMSE': [0.12, 0.15, 0.14],
...     'MAE': [0.08, 0.11, 0.10],
...     'R²': [0.85, 0.78, 0.82]
... })
>>> plotter = SummaryTablePlotter(metrics_data)
>>> html_table = plotter.plot()
>>> # html_table contains styled HTML ready for display
Parameters:

data (DataFrame)

__init__(data: DataFrame)[source]

Initialize the SummaryTablePlotter with data.

Parameters:

  • data (DataFrame) – DataFrame containing the data to be plotted.

  • data

plot() → str[source]

Creates a formatted HTML table from the DataFrame.

Return type:

str

Returns:

A formatted HTML table

Return type:

str