compute_metrics

compute_metrics(data, date_var, period, metric_set, truth, estimate, **kw)

Compute metrics for given time period

Parameters

Name	Type	Description	Default
data	DataFrame	Pandas dataframe	required
date_var	str	Column in data containing dates	required
period	timedelta	Defining period to group by	required
metric_set	list	List of metrics to compute, that have the parameters y_true and y_pred	required
truth	str	Column name for true results	required
estimate	str	Column name for predicted results	required

Examples

>>> from datetime import timedelta
>>> import pandas as pd
>>> from sklearn.metrics import mean_squared_error, mean_absolute_error
>>> df = pd.DataFrame(
...   {
...        "index": ["2021-01-01", "2021-01-02", "2021-01-03"],
...        "truth": [200, 201, 199],
...        "pred": [198, 200, 199],
...   }
... )
>>> td = timedelta(days = 1)
>>> metric_set = [mean_squared_error, mean_absolute_error]
>>> metrics = compute_metrics(df, "index", td, metric_set, "truth", "pred")