rc1 comment.

[Carreau]

As per @ellisonbg testing RC1 and commenting, apologies for shortness, I'll assume you want efficiencies and quick review for SciPy.

It looks really great ! Here are what goes through my mind as explore. Sorry if it's all over the place.

Altair requires the following dependencies:

numpy
pandas
py.test

If this is true, it should be in setup.py install_requires, or don't say it.
You also requires traitlets in setup.py , which is an indirect dependency, I suggest removing.

I suggest making a

extras_require = dict(
 'test' = [...],
 'notebook' = [...]
 'jupyter' = [...]
)

if you want to.

Does it needs jupyter nbextension enable vega --py --sys-prefix as said during the installation step (a word on that might be good)

Installation when smoothly ; It works.

• I was confuse the docs in notebooks, I was searching for docs/notebook.
• I'm confused by the dotted line around graph, and the fact that save freeze the graph as PNG (but I might have bad ipywidgets)
• The colors and style looks great.
• The PNGs looks blurry to me
  • I registed altair.readtehdocs.io, made Brian and Jake maintainer/owner.
• .encode(...) has a strong bytes/unicode meaning to me.
• Same case kwargs feel weird timeUnit, labelAngle
• Examples implicitely display things as they are last cells statements, I guess people might get confused.
• I still like the color.
• rename notebook with leading number, Introduction / index are not the firsts.

[Carreau]

Out[1].to_dict is extremely confusing

Why all the mark_ prefix ? I'm sure there is a reason.

I like the extreme terseness, and expresiveness.

[Carreau]

I would avoid the from altair import *, but personal taste.

[Carreau]

Note most of that is not relevant for RC, I'll keep adding it here, and might edit/open separate issues/thread later.

The introduction to encode and the x='a:N' notation might need to be a bit expanded. If I had not been here at DS4DS I would be highly confused.

[Carreau]

You can explore the other available mark_*() methods using IPython's tab-completion. is unacurate if one does not have Greedy completion, as Chart(data) will not be evaluated.
I suggest assigning chart, once in Introduction.ipynb and reusing it.

[ellisonbg]

Thanks!

• Will fix the dependencies in some way like you described. Great point.
• Rename the notebook with numeric prefix for sorting.
• @jakevdp what do you think about renaming the directory docs?
• Dotted line comes from the vega-lite renderer.
• We generate both a PNG and the live JS render, the auto-freeze from the PNG is form the buggy ipywidgets.
• PNGs are a bit blurry. @domoritz is it possible to create higher resolution PNGs from ipyvega?
• We are autogenerating most of the API from the JSON, which comes from JavaScript, so we are inheriting the nonPythonicCase of attributes.
• Great points about autocompletion, Out[1] and the mark_ methods, will address that now.

[Carreau]

question:

in this example:

Chart(cars).mark_circle().encode(
    x='Horsepower',
    y='Miles_per_Gallon',
    color='Origin',
    size='Acceleration'
)

would it be possible at some future point to use:

Chart(cars).mark_circle().encode(
    x='Horsepower',
    y='Miles_per_Gallon',
    color='Origin',
    size=cars.Acceleration
)

to be smart and figure back the name of the column ?

you use the _.<attributes> in some places as well.

The more I read the more I like it.

[Carreau]

Vega-Lite thing comment:

for me a "circle" is not filled, a "disk" is. So the default mark_point/mark_circle looks backward.
I understand that you match vega spec. I just was confused for a few seconds.

[ellisonbg]

Yes, that should be possible. It would be nice to do that as you can
autocomplete most of those and avoid typing quotes. Great idea. I will try
that now...

On Sat, Jul 9, 2016 at 5:57 PM, Matthias Bussonnier <
notifications@github.com> wrote:

question:

in this example:

Chart(cars).mark_circle().encode(
x='Horsepower',
y='Miles_per_Gallon',
color='Origin',
size='Acceleration'
)

would it be possible at some future point to use:

Chart(cars).mark_circle().encode(
x='Horsepower',
y='Miles_per_Gallon',
color='Origin',
size=cars.Acceleration
)

to be smart and figure back the name of the column ?

you use the _. in some places as well.

The more I read the more I like it.

—
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Brian E. Granger
Associate Professor of Physics and Data Science
Cal Poly State University, San Luis Obispo
@ellisonbg on Twitter and GitHub
bgranger@calpoly.edu and ellisonbg@gmail.com

[Carreau]

it is possible to make module dynamically in Python, you could make the dataset one like that, so that users can directly use dataset.<tab> and dynamically fetch it on use.

[domoritz]

PNGs are a bit blurry. @domoritz is it possible to create higher resolution PNGs from ipyvega?

PNGs are generated with a higher resolution if you have a high resolution screen. See vega/vega#528

[ellisonbg]

@domoritz just to clarify - I am already using a retina screen and the PNGs are blurry still. Are you saying it should already work or is there something needed to get it to work?

[ellisonbg]

Releasing 1.0 now, closing...

[Carreau]

Releasing 1.0 now, closing...

Not all things have been fixed , I for example still have blurry PNGs.