Replace values in one column with values from another column omitting nans python

Question

I have a df like this

     Estado         Estado_OMM
     SUSPENDIDA     CLAUSURADA
     SUSPENDIDA     CLAUSURADA
     OPERATIVA      nan 
     PARCIALMENTE   nan
     OPERATIVA      nan
     OPERATIVA      OPERATIVA

I want to replace (only the values that are not nan) df['Estado'] to df['Estado_OMM'] (same row).

I tried this

for i in df['Estado_OMM']!=np.nan:
   df['Estado']=df['Estado_OMM']

Also i tried this

if df['Estado_OMM']!=np.nan:
   df['Estado']=df['Estado_OMM']

Noone works. Can you help me please?

Mayank Porwal · Accepted Answer · 2020-05-14 18:57:25Z

1

You can use np.where:

df['replaced_Estado'] = np.where(df['Estado_OMM'].notna(), df['Estado_OMM'], df['Estado'])

Output:

         Estado  Estado_OMM
0    CLAUSURADA  CLAUSURADA
1    CLAUSURADA  CLAUSURADA
2     OPERATIVA         NaN
3  PARCIALMENTE         NaN
4     OPERATIVA         NaN
5     OPERATIVA   OPERATIVA

edited May 14, 2020 at 18:57

answered May 14, 2020 at 18:52

Mayank Porwal

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r.ook · Accepted Answer · 2020-05-14 18:49:20Z

1

>>> mask = df['Estado_OMM'].notna()
>>> df.loc[mask, 'Estado'] = df.loc[mask, 'Estado_OMM']
>>> df

         Estado  Estado_OMM
0    CLAUSURADA  CLAUSURADA
1    CLAUSURADA  CLAUSURADA
2     OPERATIVA         NaN
3  PARCIALMENTE         NaN
4     OPERATIVA         NaN
5     OPERATIVA   OPERATIVA

Alternatively you could do it the other way around:

>>> df['Estado'] = df['Estado_OMM'].fillna(df['Estado'])
>>> df
         Estado  Estado_OMM
0    CLAUSURADA  CLAUSURADA
1    CLAUSURADA  CLAUSURADA
2     OPERATIVA         NaN
3  PARCIALMENTE         NaN
4     OPERATIVA         NaN
5     OPERATIVA   OPERATIVA

answered May 14, 2020 at 18:49

r.ook

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