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Selecting Subset of Pairs with Pandas/Numpy
I am working with a Python pandas dataframe df with a set of unique values in column A. I want to create a new subset of pairs in column A where the value in one column and the value in another column are different (not identical).
df.loc[df[‘A’].isin([‘X’, ‘Y’], inplace = True)]
df.loc[df[‘A’].isin([‘Z’], inplace = True)]
In this example, the new subset of pairs would be
A B
X Y
Z Z
Currently my code is returning the error:
KeyError: False
I want to stick with the method I have because I am still learning Pandas, but I’m hoping to learn a better way to code this.
A:
You can use duplicated() to select only those rows where duplicates are not present.
For your example:
In [9]: df = pd.DataFrame({‘A’: [‘X’, ‘Y’, ‘Z’]})
In [10]: df[df.A.ne(df.A.duplicated())]
Out[10]:
f30f4ceada
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