Pandas/ Python list values of one column based on string value of another column

Question

I have a .csv file like this:

Receipt ID	Name	Quantity	Category Type
135135	Croissant	1.0	Food
135135	Cappucino	1.0	Drink
143143	Salad	1.0	Food
154134	Americano	1.0	Drink
178781	Cappucino	1.0	Drink
169071	Muffin	1.0	Food
169071	Latte	1.0	Drink
169071	Brownie	1.0	Food

I want to get the Receipt IDs where the Category Type is "Food".

I've tried a few methods but none of them work. For example,

df1 = df.query('Category Type == Food')['Receipt ID'].unique()

I've also tried setting Category Type as index:

df1 = df.set_index('Category Type').eq('Food')
print (df1.index[df1['Receipt ID']].tolist())

which gave me an empty list.

The Receipt IDs are not necessarily unique, although I want the outputs to be unique, and the final goal is to find the Receipt ID that contains both "Food" and "Drink". Could any expert please give me some help? Thank you!

Answer 1

df.where(df['Category Type'] == 'Food')['Receipt ID'].dropna().values.tolist()

if you want unique:

df.where(df['Category Type'] == 'Food')['Receipt ID'].dropna().unique().astype(int).tolist()

or

df.loc[df['Category Type'] == 'Food', 'Receipt ID'].unique().tolist()

for all types:

df.groupby('Category Type').agg({'Receipt ID': 'unique'}).to_dict()