I'm using numpy 1.6.2, pandas 0.9.1, and Python 2.7.2. I see strange behavior when using numpy.logical_and() depending on how I create a Series object. For example:
>>> import numpy
>>> import pandas
>>> series = pandas.Series([1, 2, 3])
>>> x = pandas.Series([True]).reindex_like(series).fillna(True)
>>> y = pandas.Series(True, index=series.index)
>>> series
0 1
1 2
2 3
>>> x
0 True
1 True
2 True
>>> y
0 True
1 True
2 True
>>> numpy.logical_and(series, y)
0 True
1 True
2 True
>>> numpy.logical_and(series, x)
Traceback (most recent call last):
File "<ipython-input-10-e2050a2015bf>", line 1, in <module>
numpy.logical_and(series, x)
AttributeError: logical_and
What is the difference between x and y here that is causing the AttributeError?
Also, I originally posted this as a question on stackoverflow. There are comments saying this works with pandas 0.9.0 and numpy 1.8. I haven't verified this for myself yet. However, my scenario is using the most recent stable releases of both projects.
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