Description
Now that we have all the arithmetic methods, there's no reason to keep it as before. Not having this means that operating on an int column with missing values switches operation result from floordiv to truediv.
@wesm You had, at one point, said that you would consider this. I believe this change would iron over a long-standing Python wart and make pandas easier to use:
Existing behavior (note how the future import doesn't affect div at all because it's defined in a separate file, but does affect division because Python will call __truediv__ instead of __div__):
In [22]: from __future__ import division
In [23]: ser1 / ser2
Out[23]:
0 0.0
1 0.5
2 1.0
3 1.5
dtype: float64
In [24]: ser1.div(ser2)
Out[24]:
0 0
1 0
2 1
3 1
dtype: int64And missing values immediately causes this behavior to change (because coerces to float)
In [11]: from pandas import Series
In [12]: ser1 = Series([0, 1, 2, 3])
In [13]: ser2 = Series([2, 2, 2, 2])
In [14]: ser1.div(ser2)
Out[14]:
0 0
1 0
2 1
3 1
dtype: int64
In [15]: ser1[0] = np.nan
In [16]: ser1.div(ser2)
Out[18]:
0 NaN
1 0.5
2 1.0
3 1.5
dtype: float64And this distinction is totally eliminated in Python 3:
In [11]: from pandas import Series
In [12]: ser1 = Series([0, 1, 2, 3])
In [13]: ser2 = Series([2, 2, 2, 2])
In [14]: ser1.div(ser2)
Out[14]:
0 0.0
1 0.5
2 1.0
3 1.5
dtype: float64
In [15]: ser1[0] = np.nan
In [16]: ser1.div(ser2)
Out[18]:
0 NaN
1 0.5
2 1.0
3 1.5
dtype: float64Trivial to fix and, while slightly backwards incompatible, would mostly just make things simpler. We should still leave a / b to be dependent upon the future import.