Python pandas dataframe slicing, with if condition

Question

I have a DataFrame object, with multiple columns: business_id, categories, type_of_business...

I have managed to create a smaller DataFrame with only business_id and categories by column indexing on the original DataFrame object.

categories is a list of certain strings.Example: ['Restaurant, 'food', 'bakery'] - for each business_id.

One of the categories is Restaurants. How would I retrieve only those business ids where the word Restaurants is in the categories list.

Pseudocode:

for row in smaller_DataFrame:
    if 'Restaurants' in row['categories']:
        add this business_id to some dictionary.

I am interested in how I would incorporate the if condition in a DataFrame object.

Thanks in advance.

Dan Allan · Accepted Answer · 2013-09-13 15:43:27Z

4

Selecting rows according to a boolean condition is called masking in the documentation.

df[df['categories'].isin(['Restaurant', 'food', 'bakery'])]

As an aside, I see you've been downvoted. It's better if you include a few sample rows of your DataFrame and an example of your desired result.

To make it case insensitive, stick .str.lowercase() before .isin, and make the list of categories all lowercase.

answered Sep 13, 2013 at 15:43

Dan Allan

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3 Comments

Viktor Kerkez Over a year ago

I think that his categories column contain lists, not single values.

Viktor Kerkez Over a year ago

Yup, whatever it is he will have an answer :)

anonuser0428 Over a year ago

no the categories is a list of string as in each row contains a list of string categories. I think @DanAllan misunderstood me? Sorry for the confusion. I will be more descriptive in the future.

Viktor Kerkez · Accepted Answer · 2013-09-13 15:43:16Z

2

You can do it with map:

df[df.categories.map(lambda cats: 'Restaurants' in cats)]

answered Sep 13, 2013 at 15:43

Viktor Kerkez

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1 Comment

anonuser0428 Over a year ago

I had used this lambda expression form before but it completely slipped my mind. Thanks for your help Viktor.

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