· python pandas data-science

Pandas: ValueError: The truth value of a Series is ambiguous.


import pandas as pd

>>> df = pd.DataFrame({"a": [1,2,3,4,5], "b": [2,3,4,5,6]})
>>> df
   a  b
0  5  2
1  6  6
2  0  8
3  3  2
4  1  6

>>> divmod(df["a"], 2)[1] > 0
0     True
1    False
2     True
3    False
4     True
Name: a, dtype: bool

>>> divmod(df["b"], 2)[1] > 0
0    False
1     True
2    False
3     True
4    False
Name: b, dtype: bool

>>> df["anyOdd"] = (divmod(df["a"], 2)[1] > 0) or (divmod(df["b"], 2)[1] > 0)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/markneedham/projects/kaggle/house-prices/a/lib/python3.6/site-packages/pandas/core/generic.py", line 953, in __nonzero__
    .format(self.__class__.__name__))
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

>>> df["anyOdd"] = (divmod(df["a"], 2)[1] > 0) | (divmod(df["b"], 2)[1] > 0)
>>> df
   a  b  anyOdd
0  1  2    True
1  2  3    True
2  3  4    True
3  4  5    True
4  5  6    True

>>> df["bothOdd"] = (divmod(df["a"], 2)[1] > 0) & (divmod(df["b"], 2)[1] > 0)
>>> df
   a  b  anyOdd  bothOdd
0  1  2    True    False
1  2  3    True    False
2  3  4    True    False
3  4  5    True    False
4  5  6    True    False
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