python - 当 python 中数据帧的另一列中发现重复值时，如何增加新列的值？

Question

我有一个 CSV 文件，如下所示:

Timestamp  Status
1501       Normal
1501       Normal
1502       Delay
1503       Received
1504       Normal
1504       Delay
1505       Received
1506       Received
1507       Delay
1507       Received

我想向数据帧添加一个新的“Notif”列，该列显示为计数器变量，并且当遇到“状态”列中的“已接收”值时会增加。我希望输出看起来像:

Timestamp  Status     Notif
1501       Normal     N0
1501       Normal     N0
1502       Delay      N0
1503       Received   N1
1504       Normal     N1
1504       Delay      N1
1505       Received   N2
1506       Received   N3
1507       Delay      N3
1507       Received   N4

我尝试寻找此问题的解决方案，并且各种来源建议使用 arcpy 包进行编码，但我想在没有它的情况下完成这项工作，因为 PyCharm 似乎不支持 arcpy 包

还尝试使用 numpy 用作条件运算符，但这似乎不起作用

Answer 1

使用 df.iterrows 迭代行，您可以实现以下目的:

df['Notif'] = None
counter = 0
for idx, row in df.iterrows():
    if df.iloc[idx, 1] == "Received":
        counter +=1
    df.iloc[idx,-1] = "N" + str(counter)

print(df)

输出

+----+------------+-----------+-------+
|    | Timestamp  |  Status   | Notif |
+----+------------+-----------+-------+
| 0  |      1501  | Normal    | N0    |
| 1  |      1501  | Normal    | N0    |
| 2  |      1502  | Delay     | N0    |
| 3  |      1503  | Received  | N1    |
| 4  |      1504  | Normal    | N1    |
| 5  |      1504  | Delay     | N1    |
| 6  |      1505  | Received  | N2    |
| 7  |      1506  | Received  | N3    |
| 8  |      1507  | Delay     | N3    |
| 9  |      1507  | Received  | N4    |
+----+------------+-----------+-------+