Coerce expression #1137
Coerce expression #1137
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| assert str(s.coerce('int64')) == "s.coerce(to='int64')" | ||
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| @pytest.mark.xfail(raises=AttributeError, reason='Should this be valid?') |
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Is the question here if we should be able to cast down from float64 to float32? I think the idea of casting records like this is pretty cool.
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The question is: Is casting an entire set of rows on a subset of columns (possibly all the columns as well) useful? How often is it the case that you want to change the type of a set of columns? I honestly don't know. I know that I do this in one particular case when I'm shoving a DataFrame that contains strings into a bcolz ctable in Python3.4.
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This would be nice because there are some places that I have tz-aware datetimes in dataframes so the type is object and I would like to coerce all of the columns to datetime instead of object.
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In the case of tz-aware datetimes they are cast to object because pandas doesn't have a way to manage a contiguous array of tz-aware datetimes (yet).
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Oh actually, I see what you mean ... they might be inferred as object, but you want whatever you're sending them to to see that they are datetimes
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Can you add a series coerce? |
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yep, just haven't gotten to it yet |
| @@ -705,6 +705,21 @@ def dshape(self): | |||
| return dshape(self._dshape) | |||
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| class Coerce(Expr): | |||
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can we add a docstring here with some examples?
| @@ -22,7 +22,7 @@ | |||
| __all__ = ['Expr', 'ElemWise', 'Field', 'Symbol', 'discover', 'Projection', | |||
| 'projection', 'Selection', 'selection', 'Label', 'label', 'Map', | |||
| 'ReLabel', 'relabel', 'Apply', 'Slice', 'shape', 'ndim', 'label', | |||
| 'symbol'] | |||
| 'symbol', 'Coerce', 'coerce'] | |||
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Should the coerce function be available as a standalone function from the top level package or do you think this is most useful as a method
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I think I'll just leave it as a method for now and remove it from __all__
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Just had one comment on the visibility of the coerce function; but, this looks good to me |
closes #1050