資料探索_相關系數矩陣圖繪制

data_temp = data_sample
#相關系數矩陣繪制
def cor_matrix(cor):
    ax = plt.figure(figsize=(10,10)).add_subplot(111)
    col_num = len(cor)
    columns = cor.columns
    step = 0.0625*10/col_num
    start_pos_1_x = 0.15-(0.0625-step)/2
    start_pos_1_y = 0.15
    start_pos_2_x = 0.10-(0.0625-step)/2
    start_pos_2_y = 0.215-(0.0625-step)/2
    for i in range(col_num):
        plt.figtext(x=start_pos_1_x+i*step,y=start_pos_1_y,s=columns[i],rotation='vertical')
        plt.figtext(x=start_pos_2_x,y=start_pos_2_y+i*step,s=columns[-i-1],horizontalalignment='right')
    #for i in range(col_num):
    #    for j in range(col_num):
    #        plt.figtext(x=start_pos_1_x+i*step,y=start_pos_2_y+j*step,s = '%0.2f'%cor.iloc[i,col_num-j-1],horizontalalignment='center')
    im = ax.imshow(cor,)
    plt.colorbar(im)

columns = data_temp.columns.drop(['last_etl_acg_dt','cust_isn','bel_org'])

temp = data_temp[columns]
cor = temp.corr()
cor_matrix(cor)