(metrics_table)
return axs
Plot performance of all benchmarks for all metrics.

    Parameters
    ----------
    metrics_table : pd.DataFrame
        Table with the following columns - 'metric', 'timestamp', 'benchmark' and 'value'.

    Returns
    -------
    return_ax : 'matplotlib.axes._subplots.AxesSubplot
        Axes with number of subaxes equal to number of metrics.
Plot performance of all benchmarks for all metrics.
Plot performance of all benchmarks for all metrics .
def plot_metrics(metrics_table):
    """Plot performance of all benchmarks for all metrics.

    Parameters
    ----------
    metrics_table : pd.DataFrame
        Table with the following columns - 'metric', 'timestamp', 'benchmark' and 'value'.

    Returns
    -------
    return_ax : 'matplotlib.axes._subplots.AxesSubplot
        Axes with number of subaxes equal to number of metrics.

    """
    all_metrics = metrics_table['metric'].unique()
    n_metrics = len(all_metrics)

    _, axs = plt.subplots(n_metrics)

    for i, metric_name in enumerate(all_metrics):
        df = pd.pivot_table(metrics_table[metrics_table['metric'] == metric_name],
                            values='value',
                            columns='benchmark',
                            index='timestamp').sort_index()
        df.plot(ax=axs[i])
        axs[i].set_title(metric_name)

    plt.tight_layout()

    return axs
def plot_metrics ( metrics_table ) : all_metrics = metrics_table [ 'metric' ] . unique ( ) n_metrics = len ( all_metrics ) _ , axs = plt . subplots ( n_metrics ) for i , metric_name in enumerate ( all_metrics ) : df = pd . pivot_table ( metrics_table [ metrics_table [ 'metric' ] == metric_name ] , values = 'value' , columns = 'benchmark' , index = 'timestamp' ) . sort_index ( ) df . plot ( ax = axs [ i ] ) axs [ i ] . set_title ( metric_name ) plt . tight_layout ( ) return axs