plotting

Currently the polling_interval is only used as an initial configuration and can not be dynamically changed.

The following is a discourse link where I have asked the question whether this is a supported feature.
https://discourse.bokeh.org/t/dynamically-changing-bokeh-ajaxdatasource-polling-interval/7737

Problem

3d axes don't support the data kwarg:

gcf().add_subplot(projection="3d").scatter("a", "b", "c", data={"a": [0], "b": [1], "c": [2]})

results in

ValueError: could not convert string to float: 'a'

Proposed solution

I think it's "mostly" a matter of adding a bunch of @_preprocess_data decorators to 3D plotting methods similarly to what's done for 2D plots

it's becoming more time-consuming and error-prone to manually re-test all the demos following internal refactorings and API adjustments.

now that the API is fleshed out a bit, it's possible to test a large amount of code (non-granularly) without having to simulate all interactions via Puppeteer or similar.

a lot of code can already be regression-tested by simply running all the demos and val

https://readthedocs.org/projects/chartify/builds/

What's your use case?
In other words, what's your pain point?

Variable names and their icons are shown as vertical header. This

• is ugly,
• doesn't show the selection properly,
• doesn't allow sorting by variable names,
• doesn't allow selection by dragging across a range of variables (though one can drag across rows in the table itself),
• and possibly something else.

<img wi

It is currently a pain to use an OxyPlot.WinfowsForms.PlotView with a transparent background: it throws if you set its BackColor to transparent. To avoid this, it is necessary to set the ControlStyles.SupportsTransparentBackColor style to true on the PlotView; however, Control.SetStyle is protected, so consumers must resort to reflection or extending PlotView to do so. This could be

I think it could be useful, when one wants to plot only e.g. class 1, to have an option to produce consistent plots for both plot_cumulative_gain and plot_roc

At the moment, instead, only plot_roc supports such option.

Thanks a lot

I don't think this is a duplicate ticket, even though it's quite an obvious feature after that cat demo at SciPy2018.

The code that selects and renders the different geos is here in the THREE.js code
https://github.com/maartenbreddels/ipyvolume/blob/master/js/src/scatter.js#L57

I don't know quite where/how to inject the mesh definition compatible with the data file of this form, but i

What is the feature ?

I'm trying out this library for the first time and there's some places where it would be delightful to have shorthand functions:

1. Shorthand functions for Pos: Pos::top_right, Pos::bottom_right, Pos::bottom_center etc..
2. Short way to set colors for components. Currently, lots of boilerplate is required for e.g. white-on-black plotos
   • a cool start would b

Details

(This is related to JuliaPlots/Plots.jl#1706)

For example scatter(skipmissing([1.0, 2.0, missing, 1.0])) fails with Cannot convert Base.SkipMissing{Vector{Union{Missing, Float64}}} to series data for plotting.

Generally skipmissing is not required but it seems odd to see this fail.

Also I stumbled on this while trying to make a histogram, e.g.

The following code gives a segfault with Makie 0.15 and Julia 1.6.1 (also reproduced with 1.7-beta2):

using Makie

xs = range(150, 160, length=100)
ys = range(7, 9, length=100)
points = [(x, y, 0.0) for x in xs for y in ys]
x, y, z = map(i -> getindex.(points, i), 1:3)

flags = (153 .< x .< 153.5) .& (7 .< y .< 7.3)
surface(y[flags], x[flags], z[flags]);

Starting Julia

About 50% of our docstrings in PyVista have examples. This is fairly good, especially considering that many of these objects are not publicly exposed.

However, for modules like pyvista.plotting.plotting, it would be great to see nearly 100% coverage considering how important it is to be able to demonstrate the individual methods of the Plotting class.

This is a great first issue since it

the README says "Every plot has a mutating variant that ends with a exclamation mark." but this is not the case for histogram. :( would be a useful feature to have.

We don't currently demonstrate how to:

• Use bounds and colors
• Pass in a custom norm and colormap