pandas Python中根据索引值过滤数据框
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Filter data frame based on index value in Python
提问by RGRGRG
I have a data frame dfwith thousands of rows, and a sample is this:
我有一个df包含数千行的数据框，示例如下：
Index A B C D E F
EX-A.1.A.B-1A 18 7 2 2 9 8
EX-A.1.A.B-1C 0 0 0 0 0 0
EX-A.1.A.B-4A 6 4 8 6 1 1
EX-A.1.A.B-4C 0 0 0 0 0 0
EX-A.1.A.B-4F 0 0 0 0 0 0
I also have a list my_list = ["EX-A.1.A.B-1A","EX-A.1.A.B-4A","EX-A.1.A.B-4F"]
我也有一份清单 my_list = ["EX-A.1.A.B-1A","EX-A.1.A.B-4A","EX-A.1.A.B-4F"]
and I want to filter the dfbased on this list, therefore I want to keep the rows for which the index value is in the list my_list.
并且我想df根据此列表过滤，因此我想保留索引值在列表中的行my_list。
I tried this in order to create a new filtered df: Filter_df = df[df.index in my_list]and I get this error:
我尝试这样做是为了创建一个新的过滤 df:Filter_df = df[df.index in my_list]并且我收到此错误：
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all().
Any ideas on how I could do this? Thanks
关于我如何做到这一点的任何想法？谢谢
回答by Alla Tarighati
try this:
尝试这个：
Filter_df = df[df.index.isin(my_list)]
