How to use the libpysal.weights.distance.KNN.from_dataframe function in libpysal

clusters = []
    gdf[model_name] = np.nan

    # loop over each time period, standardize the data and build a weights matrix
    for time in times:
        df = data.loc[time].dropna(how="any", subset=columns).reset_index()
        df[time_var] = time

        if scaler:
            df[columns] = scaler.fit_transform(df[columns].values)

        if weights_kwargs:
            w0 = W.from_dataframe(df, **weights_kwargs)
        else:
            w0 = W.from_dataframe(df)
        w1 = KNN.from_dataframe(df, k=1)
        ws = [w0, w1]

        if threshold_variable and threshold_variable != "count":
            data[threshold_variable] = gdf[threshold_variable]
            threshold_var = data.threshold_variable.values
            ws[0] = attach_islands(ws[0], ws[1])

        elif threshold_variable == "count":
            threshold_var = np.ones(len(data.loc[time]))
            ws[0] = attach_islands(ws[0], ws[1])

        else:
            threshold_var = None

        model = specification[method](
            df[columns],