no that didn't work and I am back to thinking it is not the dates fault,
this is because if I only choose a section of my array that I know doesn't
have any NANs it works fine. Is there a way to tell is to skip/ignore these?
On Sat, Nov 5, 2011 at 8:50 AM, Stan West wrote:
> **
>
> *From:* quest
From: questions anon [mailto:questions.a...@gmail.com]
Sent: Wednesday, November 02, 2011 17:17
Thanks, I think you are right about the datetimes for the x axis causing the
problem.
Does anyone have any ideas how to resolve this?
Does it help to call ax.xaxis_date() before your calls to plt.plo
Thanks, I think you are right about the datetimes for the x axis causing
the problem.
Does anyone have any ideas how to resolve this?
On Thu, Nov 3, 2011 at 4:11 AM, Benjamin Root wrote:
> I have seen situations when using datetimes for the x axis where if all
> the data being viewed is masked (
I have seen situations when using datetimes for the x axis where if all the
data being viewed is masked (or nans, or whatever) then it errors out
because the axis range can't be determined. Maybe that is what is
happening here?
Ben Root
On Wed, Nov 2, 2011 at 11:48 AM, Michael Droettboom wrote:
matplotlib should handle both masked arrays and arrays with NaNs and
treat both the same. Can you reduce the script to something that can be
run independently without data? It's not clear to me yet why this is
failing.
Mike
On 11/01/2011 05:24 PM, questions anon wrote:
Hi All,
I am trying
Hi All,
I am trying to plot time against mean daily temperature values. The problem
is temperature contains no data in a few areas. I want to be able to ignore
this and continue plotting.
When I run the below script on my data that has all normal numbers it works
fine but when I run the script on m
