Create DataFrame from df1 and df2 and take empty value from df2 for column value if not exist in df1 column value

Question

df1 = pd.DataFrame({'call_sign': ['ASD','BSD','CDSF','GFDFD','FHHH'],'frn':['123','124','','656','']})

df2 = pd.DataFrame({'call_sign': ['ASD','CDSF','BSD','GFDFD','FHHH'],'frn':['1234','','124','','765']})

need to get a new df like

df2 = pd.DataFrame({'call_sign': ['ASD','BSD','CDSF','GFDFD','FHHH'],'frn':['123','','124','656','765']})

I need to take frn from df2 if it’s missing in df1 and create a new df

Asked By: abhi krishnan

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Source

Answer 1

Replace empty strings to missing values and use DataFrame.set_index with DataFrame.fillna, because need ordering like df2.call_sign add DataFrame.reindex:

df = (df1.set_index('call_sign').replace('', np.nan)
          .fillna(df2.set_index('call_sign').replace('', np.nan))
         .reindex(df2['call_sign']).reset_index())
print(df)
  call_sign  frn
0       ASD  123
1      CDSF  NaN
2       BSD  124
3     GFDFD  656
4      FHHH  765

Answered By: jezrael

Answer 2

If you want to update df2 you can use boolean indexing:

# is frn empty string?
m = df2['frn'].eq('')
# update those rows from the value in df1
df2.loc[m, 'frn'] = df2.loc[m, 'call_sign'].map(df1.set_index('call_sign')['frn'])

Updated df2:

  call_sign   frn
0       ASD  1234
1      CDSF      
2       BSD   124
3     GFDFD   656
4      FHHH   765

Answered By: mozway

Answer 3

temp = df1.merge(df2,how='left',on='call_sign')
df1['frn']=temp.frn_x.where(temp.frn_x!='',temp.frn_y)

    call_sign   frn
0   ASD         123
1   BSD     
2   CDSF        124
3   GFDFD       656
4   FHHH        765

Answered By: Mazhar

Create DataFrame from df1 and df2 and take empty value from df2 for column value if not exist in df1 column value

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