根据索引替换两个数据框之间的列值

Question

I have a dataframe named calls, each call is recorded by a date (calls)[datetime]. each call has an answer status (calls)[Status].

a =  {'datetime':['2021-11-22 18:47:02','2021-01-08 14:18:11','2021-06-08 16:40:45','2021-12-03 10:21:31','2021-12-03 15:21:31'], 
      'Status': ['P_TR_SOK', 'RS_GEN', 'P_TR_ST_','RS_GEN', 'MLR_ST']}

calls = pd.DataFrame(data = a)

A second Dataframe named NewStatus with same column ( NewStatus )[datetime] and the column ( NewStatus )[New_Status] that I want to replace in the first dataframe with a date join

b = {'datetime': ['2021-11-22 18:47:02','2021-01-08 14:18:11','2021-06-08 16:40:45','2021-12-03 10:21:31'], 
     'New_Status': ['AB_CL_NO','REP','AB_AUT','DROP']}

NewStatus = pd.DataFrame(data = b)

Desired result is the following for calls :

datetime	Status
2021-11-22 18:47:02	AB_CL_NO
2021-01-08 14:18:11	REP
2021-06-08 16:40:45	AB_AUT
2021-12-03 10:21:31	DROP
2021-12-03 15:21:31	MLR_ST

By using

calls.reset_index().set_index('datetime').join(NewStatus.drop_duplicates().set_index('datetime'), how='left', rsuffix='df2')

I am blocked how to replace the old Status by making the join with "datetime"

Answer 1

You could do it like this:

UPDATE Be aware that pd.update works inplace .

calls= calls.set_index('datetime')
calls.update(NewStatus.set_index('datetime').rename(columns={'New_Status': 'Status'}))
print(calls)

                       Status
datetime                     
2021-11-22 18:47:02  AB_CL_NO
2021-01-08 14:18:11       REP
2021-06-08 16:40:45    AB_AUT
2021-12-03 10:21:31      DROP
2021-12-03 15:21:31    MLR_ST

Old answer

calls= calls.set_index('datetime')
out = (calls.join(NewStatus.drop_duplicates()
                  .set_index('datetime')
                  .rename(columns={'New_Status':'Status'}), how='left', rsuffix='_updated')
       .rename(columns={'Status_updated': 'Replaced_Status'})
       .drop('Status', axis=1)
       .dropna())
print(out)

                    Replaced_Status
datetime                           
2021-11-22 18:47:02        AB_CL_NO
2021-01-08 14:18:11             REP
2021-06-08 16:40:45          AB_AUT
2021-12-03 10:21:31            DROP