How to check if two columns match some value

I have a dataframe:

d = {'hour': [1, 1, 2, 1, 2], 'value': ['alpha', 'beta', 'alpha', 'beta', 'gamma']}

df = pd.DataFrame(data=d)

and a dictionary:

di = {1: 'alpha', 2: 'gamma'}

How can I return a vector of True/False of rows where dictionary key (hour) matches its value in a dataframe’s column value.

The result should be:

np.array([True, False, False, False, True])

>Solution :

Are you looking for map:

df['hour'].map(di) == df['value']

output:

0     True
1    False
2    False
3    False
4     True
dtype: bool

It’s trivial to turn that series into numpy array if you really want.