Form a column out of a Datetime field python [duplicate]

This question already has an answer here:

• Pandas conditional creation of a series/dataframe column 6 answers

Here is the DataFrame column and its datatype

df['Hours'].head()
OutPut: 

0   00:00:00
1   00:00:00
2   11:38:00
3   08:40:00
Name: Hours, dtype: timedelta64[ns]

I want to conditionally form anaother column from it, such that it will look like.

Hours        Test
00:00:00     N/A
00:00:00     N/A
11:38:00     02:38:00
08:40:00     Under Worked

Where ,

if df['Hours'] == '00:00:00':
  df[Test] = 'N/A'
elif (df['Hours'].dt.total_seconds()//3600) < 9:
  df['Test'] = 'Under Worked' 
else:
  df['Test'] = (df['Hours'].dt.total_seconds()//3600)-9

But it gives me error

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

How can it be solved?