Question

我想在索引之后，百分位数值之前生成一列，以打印我要在Var1中循环的变量。有任何想法吗？

dropped_df基本上是同一件事，但是在使用qcut查找百分位数值之前，它将删除所有0。

抱歉，idk如何编辑期望的输出。但基本上此列：['A_Spend'，'A_Spend_drop'，'B_Spend'，............，'score'，'score_drop']是预期的列在10％列的左侧。

Var1 = ['A_Spend','B_Spend', 'C_Spend', 'D_Spend', 'completed_count', 'score']

df_drop_percentile_total= pd.DataFrame(columns=["10%", "20%", "30%", "40%", "50%", "60%", "70%", "80%", "90%", "100%"])

for i in Var1:
    a = pd.qcut(df_drop[i], 10, duplicates= 'drop').cat.categories.right
    df_drop_percentile_total = df_drop_percentile_total.append(pd.DataFrame([a]).rename(columns={0: "10%", 1: "20%", 2: "30%", 3: "40%", 4: "50%", 5: "60%", 6: "70%", 7: "80%", 8: "90%", 9: "100%"}), ignore_index=True, sort=False)

    dropped_df = df_drop[df_drop[i] != 0]
    a = pd.qcut(dropped_df[i], 10, duplicates= 'drop').cat.categories.right
    df_drop_percentile_total = df_drop_percentile_total.append(pd.DataFrame([a]).rename(columns={0: "10%", 1: "20%", 2: "30%", 3: "40%", 4: "50%", 5: "60%", 6: "70%", 7: "80%", 8: "90%", 9: "100%"}), ignore_index=True, sort=False)

    10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0   3.39    5.887   8.829   12.415  17.05   23.434  32.978  49.039  85.088  2963.267
1   3.524   6.02    8.963   12.574  17.223  23.626  33.208  49.318  85.477  2963.267
2   9.18    1207.051                                
3   3.843   5.284   7.109   9.146   11.548  14.929  19.55   27.424  43.493  1207.051
4   1   2   3   4   5   7   11  19  5499    
5   2   3   4   5   7   11  19  5499        
6   393 427 449 463 476 488 502 525 556 756
7   393 427 449 463 476 488 502 525 556 756
8   31.394  62.76   95.253  128.522 164.541 204.317 252.899 316.975 425.442 2963.267
9   31.481  62.879  95.352  128.602 164.632 204.359 252.985 317.03  425.598 2963.267
10  7.493   16.16   34.357  572.296

在for循环中为标题添加额外的列

0 个答案: