记录下数据比赛可以使用的一些小 trick ,但反正也没人看也就无所谓了


  •   np.set_printoptions(precision=2)  # reduced display precision on numpy arrays
    
    ## 绘制箱图(盒图)
    
    fig = plt.figure(figsize = (4, 6)) ## 指定绘图对象的宽度和高度
    sns.boxplot(tran_data['V0'], orient = "v", width = o.5)
    
    # ---------
    column = train_data.columns.tolist()[:39]
    fig = plt.figure(figsize = (80, 60), dpi = 75)
    for i in range(38):
        plt.subplot(7, 8, i + 1)
        sns.boxplot(train_data[column[i]], orient = "v", width = 0.5)
        plt.ylable(column[i], frontsize=36)
    plt.show