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IMAGE DETAILS Image size 2500x3726px 2.08 MB Show More Published : Feb 26, 2017Q: Why do i get the “ValueError: the truth value of a DataFrame is ambiguous” when doing this in Python and Pandas? df = pd.DataFrame({‘A’ : [‘foo’, ‘bar’], ‘B’ : [‘asdf’, ‘qwer’], ‘C’ : [1.0, 2.1]}) df = df[[‘A’, ‘B’, ‘C’]].rename(columns = {‘A’ : ‘key’, ‘B’ : ‘value’, ‘C’ : ‘other’}) This code will result in the following error message: ValueError: the truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all() I dont understand why this error is happening here, and why isnt it happening at other lines? A: Pandas is being “clever”, and tries to warn you that renaming and indexing in this way will render some transformations ambiguous. This is due to the different semantics of renaming and indexing. renaming does not modify the dataframe itself, while indexing does. In [11]: pd.DataFrame({‘A’ : [1], ‘B’ : [2]}, index=[‘foo’]) Out[11]: A B foo 1 2 In [12]: pd.DataFrame({‘A’ : [‘foo’, ‘bar’], ‘B’ : [‘asdf’, ‘qwer’], ‘C’ : [1.0, 2.1]}, index=[‘foo’]) Out[12]: A B C foo bar 1.0 1 2.1 2 Note that the column ‘A’ is also called ‘foo’ in the 2nd example, since the name of the column is implicitly important. Indexing the same values will rename them (and mark the original row as “previous”), but not generally index them. In [13]: df Out[13]: A

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