Python 使用IF条件添加多行

我有以下城市自行车旅行的数据框。但是，我在处理超过一小时的行程时遇到一些问题（我想在数据模型中使用YYYYmmDDhh作为复合键）。所以我想做的是创建一个列“keyhour”，我可以连接其他表。如果开始时间=结束时间，则根据开始时间的YYYYmmDDhh。但是，如果end_hour大于start_hour，我希望在我的数据帧中插入具有相同TORID的那么多行，以指示行程持续了几个小时

                        started_at                         ended_at  duration  start_station_id    start_station_name start_station_description  ...  end_station_description  end_station_latitude  end_station_longitude TourID start_hour  end_hour
0 2020-05-01 03:03:14.941000+00:00 2020-05-01 03:03:14.941000+00:00       635               484        Karenlyst allé            ved Skabos vei  ...      langs Drammensveien             59.914145              10.715505      0          3         3
1 2020-05-01 03:05:48.529000+00:00 2020-05-01 03:05:48.529000+00:00       141               455  Sofienbergparken sør      langs Sofienberggata  ...            ved Sars gate             59.921206              10.769989      1          3         3
2 2020-05-01 03:13:33.156000+00:00 2020-05-01 03:13:33.156000+00:00       330               550         Thereses gate   ved Bislett trikkestopp  ...    ved Kristian IVs gate             59.914767              10.740971      2          3         3
3 2020-05-01 03:14:14.549000+00:00 2020-05-01 03:14:14.549000+00:00       479               597           Fredensborg         ved rundkjøringen  ...            ved Oslo City             59.912334              10.752292      3          3         3
4 2020-05-01 03:20:12.355000+00:00 2020-05-01 03:20:12.355000+00:00       629               617  Bjerregaardsgate Øst          ved Uelands gate  ...          langs Oslo gate             59.908255              10.767800      4          3         3

因此，例如，如果开始时间=2020-05-01 03:03:14.941000+00:00，结束时间=2020-05-01 06:03:14.941000+00:00，开始时间=3，结束时间=6，并且旅游时间=1，我希望有以下行：

关键时刻；巡回演出

2020050103  ;1

2020050104   ;1

2020050105   ;1

2020050106   ;1

以及与该行程id相关的所有其他值（持续时间等）

然而，我真的找不到任何方法在熊猫身上做到这一点。是否有可能或者必须使用纯python来重新编写源csv

---

谢谢你的建议

假设您的数据帧是

df

，并且您有

导入熊猫作为pd

# convert to datetime and rounddown to hour
df['started_at'] = pd.to_datetime(df['started_at']).dt.floor(freq='H') 
df['ended_at'] = pd.to_datetime(df['ended_at']).dt.floor(freq='H')

# this creates a list of hourly datetime ranges from started_at to ended_at
df['keyhour'] = df.apply(lambda x: list(pd.date_range(x['started_at'], x['ended_at'], freq="1H")), axis='columns') 

# this just expands to row each element in the list of keyhour column
df = df.explode('keyhour') 

# conversts it to a string, of the format you specified
df['keyhour'] = df['keyhour'].dt.strftime('%Y%m%d%H') 

df

---

假设您的数据帧是

df

，并且您有

导入熊猫作为pd

# convert to datetime and rounddown to hour
df['started_at'] = pd.to_datetime(df['started_at']).dt.floor(freq='H') 
df['ended_at'] = pd.to_datetime(df['ended_at']).dt.floor(freq='H')

# this creates a list of hourly datetime ranges from started_at to ended_at
df['keyhour'] = df.apply(lambda x: list(pd.date_range(x['started_at'], x['ended_at'], freq="1H")), axis='columns') 

# this just expands to row each element in the list of keyhour column
df = df.explode('keyhour') 

# conversts it to a string, of the format you specified
df['keyhour'] = df['keyhour'].dt.strftime('%Y%m%d%H') 

df