update pandas dataframe based on column from other dataframe

Question

I have first dataframe dffieldnames . it has only one column FIELD_NAME

FIELD_NAME
MKEY
reporting_entity
provision_amount
ORIG_country
RCA_check
EWA_check

I have 2nd dataframe dfdata where all above rows are displayed as columns with actual values. so it looks like below. it could be case that field name in 1st dataframe may or may not present as column in 2nd dataframe. for example - EWA check is only present in 1st dataframe but not present in 2nd dataframe.

MKEY | reporting_entity |provision_amount | ORIG_country | RCA_check | adj_id
123  |  1234556         | 400.2344        |   NE         |           | ADJ02020
254  |  8484849         |                 |   NE         |  YES      | ADJ84848

I want to add new column(name = VALUE) in dataframe dffieldname . I will be using adj_id as filter -

if adj_id='ADJ02020',dataframe dffieldname output will be -

FIELD_NAME       |  VALUES
MKEY             |  123
reporting_entity |  1234556         
provision_amount |  400.2344
ORIG_country     |  NE
RCA_check        | 
EWA_check        | 

if adj_id = 'ADJ84848',dataframe dffieldname output will be -

FIELD_NAME       |  VALUES
MKEY             |  254
reporting_entity |  8484849
provision_amount |  
ORIG_country     |  NE
RCA_check        |  YES
EWA_check        |

Answer 1

You can do this using the index.

Make FIELD_NAME the index.

dffieldnames.set_index('FIELD_NAME', inplace=True)

Then use that index to match values to the index of the Series created by squeeze() from the specific row selected:

dffieldnames['VALUE'] = dfdata[dfdata['adj_id']=='ADJ02020'].squeeze()
dffieldnames.fillna('')


                     VALUE
FIELD_NAME                
MKEY                   123
reporting_entity   1234556
provision_amount  400.2344
ORIG_country            NE
RCA_check                 
EWA_check                

If you don't want FIELD_NAME to remain as the index you could reset the index:

dffieldnames.reset_index()

         FIELD_NAME     VALUE
0              MKEY       123
1  reporting_entity   1234556
2  provision_amount  400.2344
3      ORIG_country        NE
4         RCA_check          
5         EWA_check