Now I have dataframe and list.
A B
1 a
2 b
3 c
4 d
5 e
list=[a,b,c]
I would like to drop rows by df.B refering to list.
I would like to below df
A B
4 d
5 e
How can I get this result?
To remove duplicates of only one or a subset of columns, specify subset as the individual column or list of columns that should be unique. To do this conditional on a different column's value, you can sort_values(colname) and specify keep equals either first or last .
You can use isin
with inverted mask by ~
.
I think list
is not good name in python
, better is L
, because list
is code word and if assign variable you override it:
L= ['a','b','c']
print (df[~df.B.isin(L)])
A B
3 4 d
4 5 e
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