How do I use a dictionary to add a category column in a dataframe?

Question

So I have a dictionary:

dict = {'apple':'fruit', 'grape':'fruit', 'chickpea':'beans','coffee cup':'tableware'}

And I was wondering how to use it to make a new column that categorizes this dataframe with strings of text:

Item	Cost
apple from happy orchard	15
grape from random vineyard	20
chickpea and black bean mix	10
coffee cup with dog decal	14

Into something like

Item	Cost	Category
apple from happy orchard	15	fruit
grape from random vineyard	20	fruit
chickpea and black bean mix	10	beans
coffee cup with dog decal	14	tableware

Any help would be appreciated!

I've made my dictionary, and I've tried

dict = {'apple':'fruit', 'grape':'fruit', 'chickpea':'beans','coffee cup':'tableware'}
df[category] = 'a'
df['category'] = df['Item'].map(dict)

but I don't know what to do with the string

Answer 1

You are on the right path, it's just left with a few tweaks. You can use apply to map each item in the Item column to its respective category like this:

# Your dictionary
dict = {'apple': 'fruit', 'grape': 'fruit', 'chickpea': 'beans', 'coffee cup': 'tableware'}

# Your DataFrame
data = {'Item': ['apple from happy orchard', 'grape from random vineyard', 'chickpea and black bean mix', 'coffee cup with dog decal'],
        'Cost': [15, 20, 10, 14]}

df = pd.DataFrame(data)

# Mapping the 'Item' column to 'Category'
df['Category'] = df['Item'].apply(lambda x: next((value for key, value in category_dict.items() if key in x), None))

print(df)