本文介绍了如何在Pandas数据框中选择基于行的类别的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
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']]更多推荐
如何在Pandas数据框中选择基于行的类别
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