Q:

Create multiple columns based on multiple column conditions from another dataframe

I have 2 dataframes derived from csv files
df1
 |BID    |Datetime           |TrId |Code|LineNumber|Vol  |Grade      |PId
0|1002867|2019-08-19 01:27:53|1459 |f   |10        |33.88|Vd         |4  
1|1002867|2019-08-19 01:39:05|1460 |f   |10        |18.13|EE         |5  
2|1002867|2019-08-19 01:39:55|1461 |f   |10        |21.8 |Ad         |9  
3|1002867|2019-08-19 01:39:55|1461 |f   |20        |500  |Vd         |10 
4|1002147|2019-08-19 01:26:21|2764 |f   |10        |33.86|V9         |3  
5|1002147|2019-10-19 01:31:57|2765 |f   |10        |3.48 |V9         |2  
9|1001257|2019-08-19 01:49:54|11524|f   |10        |19.93|Ul         |5  

df2
 |sId  |BID    |StartDateTime      |EndDateTime        
0|10007|1002867|2019-07-26 05:11:05|2019-10-05 21:50:55
1|10006|1002147|2019-08-18 05:11:05|2019-10-05 21:50:55
2|10006|1002147|2019-10-05 21:50:55|2019-11-06 21:50:28
3|10006|1002147|2019-10-06 21:50:28|2019-10-08 03:56:20
4|10006|1002147|2019-10-08 03:56:20|2019-10-09 03:50:35
5|10006|1002147|2019-10-09 03:50:35|2019-10-10 05:12:30
6|10006|1002147|2019-10-10 05:12:30|2019-10-11 05:12:38
7|10009|1002348|2019-09-26 04:21:12|2019-10-06 04:16:00
8|10009|1002348|2019-10-06 04:16:00|2019-10-07 04:11:38
9|10009|1002348|2019-10-07 04:11:38|2019-10-08 04:13:12

Note that both dataframes are not of same length
I want to add the column sId, StartDateTime and EndDateTime from df2 to df1 only if the following conditions match:
if df1.BID = df2.BID and df1.DateTime is between df2.StartDateTime and df2.EndDatetime
My result should look like this:
 |BID    |Datetime           |TrId |Code|LineNumber|Vol  |Grade      |PId|sId  |StartDateTime      |EndDateTime        
0|1002867|2019-08-19 01:27:53|1459 |f   |10        |33.88|Vd         |4  |10007|2019-07-26 05:11:05|2019-10-05 21:50:55
1|1002867|2019-08-19 01:39:05|1460 |f   |10        |18.13|EE         |5  |10007|2019-07-26 05:11:05|2019-10-05 21:50:55
2|1002867|2019-08-19 01:39:55|1461 |f   |10        |21.8 |Ad         |9  |10007|2019-07-26 05:11:05|2019-10-05 21:50:55
3|1002867|2019-08-19 01:39:55|1461 |f   |20        |500  |Vd         |10 |10007|2019-07-26 05:11:05|2019-10-05 21:50:55
4|1002147|2019-08-19 01:26:21|2764 |f   |10        |33.86|V9         |3  |10006|2019-08-18 05:11:05|2019-10-05 21:50:55
5|1002147|2019-10-19 01:31:57|2765 |f   |10        |3.48 |V9         |2  |10006|2019-10-05 21:50:55|2019-11-06 21:50:28
9|1001257|2019-08-19 01:49:54|11524|f   |10        |19.93|Ul         |5  |NA   |NA                 |NA                 

I have tried using the method from this post: 
Create column based on multiple column conditions from another dataframe
however I get only the Site Id in my result and not the StartDateTime and EndDateTime
How can i get these columns in my result
Tried code:
for key, grp in df2.groupby('sId'):
    cols = ['BID', 'StartDateTime', 'EndDateTime']
    masks = (df1['BID'].eq(bid) & df1['Datetime'].between(start, end) for bid, start, end in grp[cols].itertuples(index=False))
    df1.loc[pd.concat(masks, axis=1).any(1), 'sId'] = key

df1['sId'] = df1['sId'].fillna('NA')
print(df1)

This prints out only:
 |BID    |Datetime           |TrId |Code|LineNumber|Vol  |Grade      |PId|sId  
0|1002867|2019-08-19 01:27:53|1459 |f   |10        |33.88|Vd         |4  |10007
1|1002867|2019-08-19 01:39:05|1460 |f   |10        |18.13|EE         |5  |10007
2|1002867|2019-08-19 01:39:55|1461 |f   |10        |21.8 |Ad         |9  |10007
3|1002867|2019-08-19 01:39:55|1461 |f   |20        |500  |Vd         |10 |10007
4|1002147|2019-08-19 01:26:21|2764 |f   |10        |33.86|V9         |3  |10006
5|1002147|2019-10-19 01:31:57|2765 |f   |10        |3.48 |V9         |2  |10006
9|1001257|2019-08-19 01:49:54|11524|f   |10        |19.93|Ul         |5  |NA   

A:

Assuming that 'sId' in df2 is always filled with value, than code below provides exactly the desired result:
df3 = pd.merge(df1, df2, on='BID', how="left")
result = df3[df3['Datetime'].between(df3.StartDateTime, df3.EndDateTime) | df3.sId.isna()]

