["python","pandas"]
Filter data frame based on index value in Python

I have a data frame df with thousands of rows, and a sample is this: 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"] and I want to filter the df based on this list, therefore I want to keep the rows for which the index value is in the list 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: 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
To check if row indices are in my_list: Filter_df = df[df.index.isin(my_list)]