Setting 1 or 0 to new Pandas column conditionally [duplicate]

Answer 1

You can have a vectorized approach (the minus operator is here to negate the boolean mask):

df['lunch'] = (-df.hour.isin(range(2,11))).astype(int)

Out[368]:
   hour  lunch
0     0      1
1     1      1
2     1      1
3     2      0
4     2      0

Answer 2

Try:

>>> df['lunch']=df['hour'].apply(lambda x: 1 if x >= 11 or x <= 1 else 0)
>>> df
   hour  lunch
0     0      1
1     1      1
2     1      1
3     2      0
4     2      0

Answer 3

You could

In [231]: df['lunch'] = (df['hour']<=11) & (df['hour']<=1)

In [232]: df['lunch']
Out[232]:
0     True
1     True
2     True
3    False
4    False
Name: lunch, dtype: bool

In [233]: df['lunch'].astype(int)
Out[233]:
0    1
1    1
2    1
3    0
4    0
Name: lunch, dtype: int32