
Introducing plotly.py 3.0.0 - nicolaskruchten
https://medium.com/@plotlygraphs/introducing-plotly-py-3-0-0-7bb1333f69c6
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ggm
I use plotly to make SVG outcomes which then help show people things moving to
pptx. The nice thing about the plotly svg is how well its written: it works
perfectly as the icon form or the real view. (its also significantly nicer
than the analogous design elements inside powerpoint, but I can't take people
direct to SVG elements on projected things at meetings just yet)

brilliant, simple to use s/w. thank you.

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kugestu
Good suggestion! Unfortunately I found SVG in ppt problematic/slow when
plotting many objects (think 1mio points) and sometimes details can be messed
up - so rendering to bitmaps is still preferred.

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xioxox
You could try Veusz [1], which can export in EMF format, which is useful for
Microsoft Office and Powerpoint. (I am the lead author of Veusz)

[1] [https://veusz.github.io/](https://veusz.github.io/)

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minimaxir
I did a dataviz livestream yesterday where a couple people asked if they
should learn d3 for interactive data visualization.

I strongly suggested using plotly instead (either this Python API or the
R/ggplot2 API) as it saved a lot of headaches. The native Notebook
capabilities are very nice too. (the hard part is extracting the interactive
visualization to use elsewhere)

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jjoonathan
I want to use plotly so badly but I don't want to sink an investment into
another sticky commercial ecosystem -- I've had to do that with Mathematica
and Matlab, I don't want to do it again. How good/bad is plotly in comparison?

Obviously python itself is open, I mean the API :-)

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jmmease
Actually, you don't need to sink any investment into a commercial ecosystem
here!

plotly.py and the plotly.js rendering library are both MIT licensed, developed
in the open on GitHub, and totally self-contained.

Everything in the technology stack used in the announcement post is free, open
source, self-contained, usable offline, and doesn't require an account. The
plot.ly cloud integration is totally optional.

~~~
jjoonathan
Cool! I'll have to give it a look then!

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kugestu
Really good stuff and addresses many issues I had, eg documentation and
jupyter compatibility. I hope the static image export gets a bit streamlined -
being able to quickly & programmatically export graphs to png is really
something I did not find easy from python with plotly so far. Yet it is
definitely crucial eg to send a high quality image to the boss for a
PowerPoint slide or to save 100s of png images for quick visual quality
checks.

So I am really looking forward to give the new version a spin!

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jmmease
Rock solid export of high-quality static images is really important to me too.
Fortunately the hard part is already done (in orca). Integrating orca into
plotly.py is the very next feature I'm going to start working on after I get
through SciPy next week, so hopefully it won't be _too_ much longer...

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kugestu
I am really happy to hear that, thanks a lot for your efforts!

I really think having interactive plots for rapid prototyping/outlier
inspection/plot design and then being able to use the same code to produce
static, publication grade graphs or doing batch processing, will allow for a
really efficient workflow!

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lorenzfx
I really like plotly, but I'm wondering if anyone has some experience with
plotly AND with some other interactive plotting libraries for python (e.g.,
bokeh or altair). Where are the strengths and weaknesses? Which package to you
prefer?

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joshvm
It seems that the new version of plotly addresses most of my annoyances, but
I've yet to play with it.

I really like Bokeh. It's still quite young (0.13) and some things aren't
quite there yet. For general plotting, pretty much everything you need is
already there. The documentation is excellent.

Plotly is very powerful, but if you have a use-case that's beyond the examples
it can be hard to find. I ran into some annoying issues - for example you
can't embed JSON metadata into a plot before sending to the browser because
the parser can't deal with unexpected keys.

I also don't (didn't?) like how everything in Plotly is done via dictionaries
and (for the newcomer, somewhat abstract) graph objects. Graph object
definitions in plotly get very busy and long if you need to do anything
complicated. The new imperative options seem to have fixed this.

Bokeh feels much more similar to Matplotlib and I think produces far more
readable code.

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peatmoss
Plotly for R has the neat feature whereby you can take a ggplot plot and
render it with plotly. Same definition; perhaps more web-appropriate output. I
think if I were to try and extend a grammar of graphics plotting system for
another language, I might start with Plotly... or perhaps vega-lite.

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Tarq0n
Altair does grammar of graphics on top of Vega-lite.

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punnerud
Already posted:
[https://news.ycombinator.com/item?id=17418081](https://news.ycombinator.com/item?id=17418081)

~~~
dang
Yes, we marked this as a dupe, but on second thought I had a feeling that much
of the community didn't see it and—to judge by the comments in the first
thread—might like to. So we'll change the URL from
[https://github.com/plotly/plotly.py/blob/master/CHANGELOG.md](https://github.com/plotly/plotly.py/blob/master/CHANGELOG.md)
to the more-informative blog post and give this one a second chance. We do
that sometimes with borderline cases.

~~~
StavrosK
FWIW I agree with this, I missed it the first time around and found it very
useful this time.

