Be able to effectively plot visualizations of different metrics

[simonhkswan]

Say you have a Metric and you only know what its Abstract Type is (i.e., Column, TwoColumn, etc.)

• You also have Two Data Frames:

• df_a, df_b

Can you write some functions to evaluate the metric. on the dataframes and then provide useful plots of the metrics.

class AvgColumnMetric(DataFrameMetric):
    """Adapter class"""
    def __init__(self, metric: ColumnMetric):
        self._metric = metric
        self.name = f"avg_{self._metric.name}"

    def call(df: pd.DataFrame):
        values = [self._metric(df[col]) for col in df.columns]
        return np.mean(values)

Column -> value for each column, a colour for each dataframe as a bar chart TwoColumn:

• comparing df_a[col] to df_b[col] for col in df_aorb.columns. -> bar chart one colour -> a plot for each column showing the two distributions
• comparing df_a[col1] to df_a[col2] -> confusion matrix -> two of them.
• df_b[col1] to df_b[col2]

[simonhkswan]

https://datalore.jetbrains.com/notebook/e3ikUrmZAwbbY4rGVg19po/xAkBAmHTr1reqAGXOvhxBB/