如何在Pandas数据框中选择基于行的类别 [英] How to select rows based categories in Pandas dataframe

问题描述

这真的很琐碎，但不敢相信我已经徘徊了一个小时，仍然可以找到答案，所以您在这里:

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

我的问题是如何选择其猫"列类别为"a"的行.我知道df.loc[df.cats == "a"]可以工作，但是它基于元素上的相等性.有没有一种基于类别级别进行选择的方法?

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?

推荐答案

这有效:

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

更新

问题已更新.新解决方案:

The question was updated. New solution:

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

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