Hey everyone,
Just a quick plug for a super small module I wrote to extend matplotlib a
bit.
mpl-probscale provides a probability scale for matplotlib axes. You can
install it through my channel on conda:
conda install --channel=phobson mpl-probscale.
Python 2.7, 3.4, and 3.5 are supported.
Documentation: http://phobson.github.io/mpl-probscale/
Github: https://github.com/phobson/mpl-probscale
Anaconda: https://anaconda.org/phobson/mpl-probscale
-paul
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Hi,
This is very interesting. I've looked at your docs and "kind of"
understand what the does but I miss a more formal definition of this
scale and a clear usage example (without the "readymade plot functions"
because they hide to much what's going on).
Also, do you think some of your probplot function could interest
Graphics - statsmodels 0.14.0 ?
best,
Pierre
Le 04/01/2016 06:11, Paul Hobson a ?crit :
Hey everyone,
Just a quick plug for a super small module I wrote to extend
matplotlib a bit.
mpl-probscale provides a probability scale for matplotlib axes. You
can install it through my channel on conda:
conda install --channel=phobson mpl-probscale.
Python 2.7, 3.4, and 3.5 are supported.
Documentation: http://phobson.github.io/mpl-probscale/
Github: GitHub - phobson/mpl-probscale: Real probability scales for matplotlib
Anaconda: Mpl Probscale :: Anaconda.org
-paul
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Matplotlib-users mailing list
Matplotlib-users at python.org
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Hey Pierre,
Thanks for the question and PR. Basically, all a probability scale is, is a
Q-Q plot, but with probabilities displayed instead of Z-scores.
See the especially the last figure here:
In statistics, a Q–Q plot (quantile–quantile plot) is a probability plot, a graphical method for comparing two probability distributions by plotting their quantiles against each other. A point (x, y) on the plot corresponds to one of the quantiles of the second distribution (y-coordinate) plotted against the same quantile of the first distribution (x-coordinate). This defines a parametric curve where the parameter is the index of the quantile interval.
If the two distributions being compared a...
As for statsmodels: I've helped them out with their probplot functionality
in the past. I have a stale PR still open about aimed at cleaning things up
a bit.
-paul
···
On Mon, Jan 4, 2016 at 12:09 AM, Pierre Haessig <pierre.haessig at crans.org> wrote:
Hi,
This is very interesting. I've looked at your docs and "kind of"
understand what the does but I miss a more formal definition of this scale
and a clear usage example (without the "readymade plot functions" because
they hide to much what's going on).
Also, do you think some of your probplot function could interest
Graphics - statsmodels 0.14.0 ?
best,
Pierre
Le 04/01/2016 06:11, Paul Hobson a ?crit :
Hey everyone,
Just a quick plug for a super small module I wrote to extend matplotlib a
bit.
mpl-probscale provides a probability scale for matplotlib axes. You can
install it through my channel on conda:
conda install --channel=phobson mpl-probscale.
Python 2.7, 3.4, and 3.5 are supported.
Documentation: http://phobson.github.io/mpl-probscale/
Github: GitHub - phobson/mpl-probscale: Real probability scales for matplotlib
Anaconda: Mpl Probscale :: Anaconda.org
-paul
_______________________________________________
Matplotlib-users mailing listMatplotlib-users at python.orghttps://mail.python.org/mailman/listinfo/matplotlib-users
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Matplotlib-users mailing list
Matplotlib-users at python.org
Matplotlib-users Info Page
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Le 04/01/2016 20:41, Paul Hobson a ?crit :
Basically, all a probability scale is, is a Q-Q plot, but with
probabilities displayed instead of Z-scores.
See the especially the last figure here:
Q–Q plot - Wikipedia
Ok I see. Can be pretty useful indeed.
At first I thought your probability scale was related to the new logit
scale (because it's also about "probabilities"), but now I understand
it's completely different.
best,
Pierre