Comparing values between two columns

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I have a dataframe df I want check each value in Age column and compare it with diff column and finally assign Yes, No or other to Is_dob column.

Age  diff(DOB-today)   Is_dob
54   54                Yes
27   27                Yes
43   44                No
68   70                No
NA   NA                Other

I have tried below code:

for i, j in df['Age'].iteritems():
    for k, m in df['diff'].iteritems()
       if pd.isnull(j) or pd.isnull(m):
          df['Is_dob']='other'
       elif(m==j):
          df['Is_dob']='Yes'
       else:
          df['Is_dob']='No'

But not getting expected output. Can anyone suggest solution?

dataframe pandas python
1 Answers

Use numpy.select with 2 conditions and default value:

df['Is_dob'] = np.select([df['Age'].isna() | df['diff'].isna(),
                          df['Age'].eq(df['diff'])], ['Other','Yes'], default='No')
print (df)
    Age  diff Is_dob
0  54.0  54.0    Yes
1  27.0  27.0    Yes
2  43.0  44.0     No
3  68.0  70.0     No
4   NaN   NaN  Other

Or subtract values and then test:

sub = df['Age'].sub(df['diff'])
df['Is_dob'] = np.select([sub.isna(), sub.eq(0)], ['Other','Yes'], default='No')
print (df)
    Age  diff Is_dob
0  54.0  54.0    Yes
1  27.0  27.0    Yes
2  43.0  44.0     No
3  68.0  70.0     No
4   NaN   NaN  Other
jezrael0
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