two_sigma_financial_modelling.py 文件源码

def dendrogram(df, number_of_clusters=int(df.shape[1] / 1.2)):
        # Create Dendrogram
        agglomerated_features = FeatureAgglomeration(n_clusters=number_of_clusters)
        used_networks = np.arange(0, number_of_clusters, dtype=int)

        # Create a custom palette to identify the networks
        network_pal = sns.cubehelix_palette(len(used_networks),
                                            light=.9, dark=.1, reverse=True,
                                            start=1, rot=-2)
        network_lut = dict(zip(map(str, df.columns), network_pal))

        # Convert the palette to vectors that will be drawn on the side of the matrix
        networks = df.columns.get_level_values(None)
        network_colors = pd.Series(networks, index=df.columns).map(network_lut)
        sns.set(font="monospace")
        # Create custom colormap
        cmap = sns.diverging_palette(h_neg=210, h_pos=350, s=90, l=30, as_cmap=True)
        cg = sns.clustermap(df.astype(float).corr(), cmap=cmap, linewidths=.5, row_colors=network_colors,
                            col_colors=network_colors)
        plt.setp(cg.ax_heatmap.yaxis.get_majorticklabels(), rotation=0)
        plt.setp(cg.ax_heatmap.xaxis.get_majorticklabels(), rotation=90)
        plt.show()