Question

客户具有多个订阅时，该客户被复制。我想为整个客户状态而不是为每个订阅生成一个new_status：给已重新激活订阅的客户以及已取消一个订阅但仍具有另一个有效订阅的客户。

df：

Customer | Status  | Canceled_at | Created  | New_status
 X       | Active  |             |8/9/2017  |
 X       |Canceled |  8/3/2017   |6/19/2017 |             
 Y       | Active  |             |2/13/2019 |
 Y       |Canceled | 11/28/2018  |10/14/2018|
 Z       | Active  |             |3/29/2018 |
 Z       |Canceled | 8/8/2018    |7/10/2018 |
 A       |Canceled | 9/2/2018    |7/10/2018 |          
 A       |Canceled | 9/29/2018   |7/12/2018 |
 A       |Active   |             |5/31/2018 |

这些情况的条件是：如果已取消重复的“取消日期”>活动日期的“创建”日期：新的_status将为“降级” 如果已取消重复的“ canceled_at”日期< 有效：new_status将为“重新激活”

所需的输出：

Customer | Status  | Canceled_at | Created  | New_status
 X       | Active  |             |8/9/2017  |Reactivate
 X       |Canceled |  8/3/2017   |6/19/2017 |Reactivate              
 Y       | Active  |             |2/13/2019 |Reactivate
 Y       |Canceled | 11/28/2018  |10/14/2018|Reactivate
 Z       | Active  |             |3/29/2018 |Downgrade
 Z       |Canceled | 8/8/2018    |7/10/2018 |Downgrade
 A       |Canceled | 9/2/2018    |7/10/2018 |Downgrade           
 A       |Canceled | 9/29/2018   |7/12/2018 |Downgrade
 A       |Active   |             |5/31/2018 |Downgrade

Answer 1

我太新了，无法评论，但是我需要更多信息，为什么“ Y”个客户重新激活？也许我不理解您的解释，因为客户“ A”处于类似情况，而您给了它“降级”。也许只是重新输入您的问题，但装作一个8岁的孩子即可阅读（我）。

这是您想要的代码，它可以工作：

#convert columns to dates
df['Canceled_at'] = pd.to_datetime(df['Canceled_at'])
df['Created'] = pd.to_datetime(df['Created'])

#make customer a list so we can loop through it
customer = list(df['Customer'].drop_duplicates())

#super awesome for loop that give us the largest date (this is the part where maybe your logic is different than what I read it as)
for c in customer:
    df.loc[(df['Customer'] == c), 'Most Recent Cancel'] = df.loc[(df['Customer'] == c)]['Canceled_at'].max()
    df.loc[(df['Customer'] == c), 'Most Recent Created'] = df.loc[(df['Customer'] == c)]['Created'].max()

#Make 'New_status' column
df.loc[(df['Most Recent Created'] > df['Most Recent Cancel']), 'New_status'] = 'Reactivate'
df.loc[(df['New_status'] != 'Reactivate'), 'New_status'] = 'Downgrade'

通过不同列在重复值之间有条件

1 个答案: