Why not use the actual month? With a simple x/y canvas in Tkinter you could
plot by the months with polygon coordinates as your data visualization, or
in 30 day /etc windows, just the price(y) being a derivative of x(the
frequency of changes), and create simple line segments with polygon
coordinat
You could also begin a little stats(I think steven D'aprano did pystats),
which would show rhythms within those particular frequency windows, using y
as a basis for your model
On Sat, Jul 20, 2013 at 1:10 AM, David Hutto wrote:
> Why not use the actual month? With a simple x/y canvas in Tkinter
On 07/20/2013 01:00 AM, Sivaram Neelakantan wrote:
On Sat, Jul 20 2013,Dave Angel wrote:
These are small,fixed line extracts.
Once you determine the offset in the file for those 180, 90, and 30
day points, it's a simple matter to just seek to one such spot and
process all the records
On 07/19/2013 04:00 PM, Peter Otten wrote:
Sivaram Neelakantan wrote:
I've got some stock indices data that I plan to plot using matplotlib.
The data is simply date, idx_close_value and my plan is to plot the
last 30 day, 90, 180 day & all time graphs of the indices.
a) I can do the date compu
Hi,
On 19 July 2013 20:24, Sivaram Neelakantan wrote:
>
> I've got some stock indices data that I plan to plot using matplotlib.
> The data is simply date, idx_close_value and my plan is to plot the
> last 30 day, 90, 180 day & all time graphs of the indices.
>
> a) I can do the date computation
