Python 按唯一列拆分CSV

我在尝试将我的CSV拆分为CSV文件的最小值时遇到了一个问题，因此每个文件中只有唯一的ID

通过运行

count = df['id'].value_counts().max()

我已经知道我应该创建多少个csv文件（file1、file2、file3、file4）

我的预期产出应该是

文件1

文件2

文件3

文件4

用于计数器系列，然后在循环中写入文件：

g = df.groupby('id').cumcount() + 1

for i, df in df.groupby(g):
    df.to_csv(f'file{i}.csv', index=False)

使用样本数据进行测试：

for i, df in df.groupby(g):
    print (df)

      person_name     id    Total  Paid        Date          No
    0      Deniss  55227  1191,75  0,00  21/08/2019  15/06/2018
    4     RINALDS  56002   169,00  0,00  21/08/2019  15/06/2018
    7        OLGA  54689   812,90  0,00  21/08/2019  15/05/2018
      person_name     id    Total  Paid        Date        No
    1      Deniss  55227  1191,75  0,00  21/08/2019  20180615
    5     RINALDS  56002   169,00  0,00  21/08/2019  20180615
    8        OLGA  54689   812,90  0,00  21/08/2019  20180515
      person_name     id    Total  Paid        Date        No
    2      Deniss  55227  1191,75  0,00  21/08/2019  20180613
    6     RINALDS  56002   169,00  0,00  21/08/2019  20180614
      person_name     id    Total  Paid        Date        No
    3      Deniss  55227  1191,75  0,00  21/08/2019  20180612

person_name     id    Total  Paid        Date          No
Deniss  55227  1191,75  0,00  21/08/2019    20180613
RINALDS  56002   169,00  0,00  21/08/2019    20180614

person_name     id    Total  Paid        Date          No
Deniss  55227  1191,75  0,00  21/08/2019    20180612

g = df.groupby('id').cumcount() + 1

for i, df in df.groupby(g):
    df.to_csv(f'file{i}.csv', index=False)

for i, df in df.groupby(g):
    print (df)

      person_name     id    Total  Paid        Date          No
    0      Deniss  55227  1191,75  0,00  21/08/2019  15/06/2018
    4     RINALDS  56002   169,00  0,00  21/08/2019  15/06/2018
    7        OLGA  54689   812,90  0,00  21/08/2019  15/05/2018
      person_name     id    Total  Paid        Date        No
    1      Deniss  55227  1191,75  0,00  21/08/2019  20180615
    5     RINALDS  56002   169,00  0,00  21/08/2019  20180615
    8        OLGA  54689   812,90  0,00  21/08/2019  20180515
      person_name     id    Total  Paid        Date        No
    2      Deniss  55227  1191,75  0,00  21/08/2019  20180613
    6     RINALDS  56002   169,00  0,00  21/08/2019  20180614
      person_name     id    Total  Paid        Date        No
    3      Deniss  55227  1191,75  0,00  21/08/2019  20180612