On Friday, 13 November 2015 18:17:59 UTC+1, Ian wrote:
> On Fri, Nov 13, 2015 at 8:37 AM, PythonDude wrote:
> > 3) I DON'T understand why the code doesn't look like this:
> >
> > means, stds = np.column_stack([
> > for _ in xrange(n_portfolios):
&g
Hi all,
Just a quick question about this code-piece (it works, I've tested it):
means, stds = np.column_stack([
getMuSigma_from_PF(return_vec)
for _ in xrange(n_portfolios) ])
1) I understand column_stack does this (assembles vectors vertically,
side-by-side):
>>> a = np.array((1,2,3
On Thursday, 12 November 2015 22:57:21 UTC+1, Robert Kern wrote:
> On 2015-11-12 15:57, PythonDude wrote:
> > Hi all,
> >
> > I've come around a webpage with python-tutorial/description for obtaining
> > something and I'll solve this:
> >
> > R =
On Thursday, 12 November 2015 17:35:39 UTC+1, Ian wrote:
> On Thu, Nov 12, 2015 at 8:57 AM, PythonDude wrote:
> > Hi all,
> > Anyone could please explain or elaborate on exactly this (quote): "Keep in
> > mind that Python has a reversed definition of rows and column
Hi all,
I've come around a webpage with python-tutorial/description for obtaining
something and I'll solve this:
R = p^T w
where R is a vector and p^T is the transpose of another vector.
...
p is a Nx1 column vector, so p^T turns into a 1xN row vector which can be
multiplied with the
Nx1 weig
