How to select rows based categories in Pandas dataframe

问题

this is really trivial but can't believe I have wandered around for an hour and still can find the answer, so here you are:

    df = pd.DataFrame({"cats":["a","b"], "vals":[1,2]})
    df.cats = df.cats.astype("category")
    df

My problem is how to select the row that its "cats" columns's category is "a". I know that df.loc[df.cats == "a"] will work but it's based on equality on element. Is there a way to select based on levels of category?

回答1:

This works:

df.cats[df.cats=='a']

UPDATE

The question was updated. New solution:

df[df.cats.cat.categories == ['a']]

回答2:

You can query the categorical list using df.cats.cat.categories which prints output as

Index(['a', 'b'], dtype='object')

For this case, to select a row with category of 'a' which is df.cats.cat.categories['0'], you just use:

df[df.cats == df.cats.cat.categories[0]]

回答3:

df[df.cats.cat.categories == df.cats.cat.categories[0]]

来源：https://stackoverflow.com/questions/33468566/how-to-select-rows-based-categories-in-pandas-dataframe