I will certainly give it a try, it
sounds like it could really add to what I want to do. Thanks! I’ll be
in touch if I have questions about timeseries.
On Fri, Mar 21, 2008 at 9:39 AM, Pierre GM <pgmdevlist@…287…> wrote:
On Thursday 20 March 2008 23:39:53 you wrote:
I was interested in learning more about TimeSeries, and had a few
Your data is indexed in time, right ? Your x-axis is a date object ?
Just to be clear on the language: “indexed in time” means data for which
the x-axis is a series of dates, correct? But I am not sure what is meant
by the “x-axis being a date object” --wouldn’t it be a axis object with the
values comprising it being date objects? I’m not trying to split hairs,
I’m just unclear about the way this is typically described and it would be
useful for me to be clear about it.
Sorry, I wasn’t clear enough: by x-axis, I was not referring to any python
object, but generic abscissae, as in “plot rain vs time”.
By indexed in time, I mean that you would have something like:
yourdata[one_date] = some_value
That’s what scikits.timeseries was designed to do: handle data indexed in
time, giving the possibility to access the data directly by dates (instead of
using an index in an array). We made sure we could handle gaps in your data
(viz, data not regularly spaced in time…)
I’ve looked at the link. Could you explain what TimeSeries does that the
mpl modules dates and dateutil don’t do, or when one would use one versus
Not so much useful for plotting (even if there are some cool tricks) than for
simplifying the analysis of your data: getting for example monthly averages
from daily data is a breeze
For my part, I need to simply plot values with dates (and yes with some
dates missing no doubt) as the x-axis and am looking for various ways to do
You can just stick to mpl, using plot_dates instead of plot. But you may want
to give timeseries a try.