Reshape of pandas series?
You can call reshape
on the values array of the Series:
In [4]: a.values.reshape(2,2)Out[4]: array([[1, 2], [3, 4]], dtype=int64)
I actually think it won't always make sense to apply reshape
to a Series (do you ignore the index?), and that you're correct in thinking it's just numpy's reshape:
a.reshape?
Docstring: See numpy.ndarray.reshape
that said, I agree the fact that it let's you try to do this looks like a bug.
The reshape function takes the new shape as a tuple rather than as multiple arguments:
In [4]: a.reshape?Type: functionString Form:<function reshape at 0x1023d2578>File: /Library/Frameworks/EPD64.framework/Versions/7.3/lib/python2.7/site-packages/numpy/core/fromnumeric.pyDefinition: numpy.reshape(a, newshape, order='C')Docstring:Gives a new shape to an array without changing its data.Parameters----------a : array_like Array to be reshaped.newshape : int or tuple of ints The new shape should be compatible with the original shape. If an integer, then the result will be a 1-D array of that length. One shape dimension can be -1. In this case, the value is inferred from the length of the array and remaining dimensions.
Reshape is actually implemented in Series and will return an ndarray:
In [11]: aOut[11]: 0 11 22 33 4In [12]: a.reshape((2, 2))Out[12]: array([[1, 2], [3, 4]])
you can directly use a.reshape((2,2))
to reshape a Series, but you can not reshape a pandas DataFrame directly, because there is no reshape function for pandas DataFrame, but you can do reshape on numpy ndarray:
- convert DataFrame to numpy ndarray
- do reshape
- convert back
e.g.
a = pd.DataFrame([[1,2,3],[4,5,6]])b = a.as_matrix().reshape(3,2)a = pd.DataFrame(b)