Python dataframe count the values in a row and add status to the another row

Question

Have a df with values

name    subject  

mark     M         
mark     S
mark     P
mark     SS
staurt   M
cuban    S
cuban    P

if a usercount in name is present more once in name column then present status should be YES, if it's only once then status present status should be NO

name    subject   present status

mark     M          YES
mark     S          YES
mark     P          YES
mark     SS         YES
staurt   M          No
cuban    S          YES
cuban    P          YES

tried this:

df['present status'] = np.where(df['name'] == df['name'].shift(), 'YES', 'NO')

Answer 1

Use Series.duplicated with keep=False :

df['present status'] = np.where(df['name'].duplicated(keep=False), 'YES', 'NO')
print (df)
     name subject present status
0    mark       M            YES
1    mark       S            YES
2    mark       P            YES
3    mark      SS            YES
4  staurt       M             NO
5   cuban       S            YES
6   cuban       P            YES