Data visualization

Currently, we use Native filter on Superset version 1.2, but looks like The actual time range does not show correctly with SIP-15 (in the SIP-15 the time range must is [inclusive, exclusive) ). So that mean the actual time range and the tool tip must show label as: from_date <= col < to_date.

Expected results

![image](https://user-images.githubusercontent.com/37523968/130939207-7ff847a

Summary

If you use a slider in the sidebar with a long description text, the slider value and the description text overlap. See screenshot:

Steps to reproduce

Code snippet:

import streamlit as st

topn_ranking = st.sidebar.s

In recent versions (can't say from exactly when), there seems to be an off-by-one error in dcc.DatePickerRange. I set max_date_allowed = datetime.today().date(), but in the calendar, yesterday is the maximum date allowed. I see it in my apps, and it is also present in the first example on the DatePickerRange documentation page.

E

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

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 seems like http://www.electricitymap.org/map is serving.
Consider adding an automatic redirect to https://www.electricitymap.org/map.

This is considered a best practice.

If the website is served via web/server.js, a middleware could be added to Express to implement this redirect.

If it's served via another method in production, it's also usual for web frontends to allow setting thi

Currently, the color palette is hardcoded in visuals.py:
https://github.com/MLWave/kepler-mapper/blob/0dfa7f736bd4218e8996888785b9d2adc63d5344/kmapper/visuals.py#L8-L15

and again in kmapper.js

https://github.com/MLWave/kepler-mapper/blob/0dfa7f736bd4218e8996888785b9d2adc63d5344/kmapper/static/kmapper.js#L25-L32

I'd like to see this

• duplication fixed and
• allow the palette

Hi,

I'm new to plotly dash and I've googled but I don't see a way to make a filter a dropdown akin to excel filters.

I've seen people do "hacks" but this should be the default behaviour out of the box (or at least a setting).

I'm currently evaluating plotly dash vs tools such as metabase and metabase has this out of the box.

From a UX pov, filters with a dropdown is a huge win and impo

The way it is now:

If collecting commit data fails due to a git checkout error (e.g. permissions error on the repo directory, missing git executable, etc.), the Repo nevertheless gets marked as "Update" and no attempt is made to ever check out the repo again.

The way it should be:

If a worker can't check out a git repo, or can't extract data from it, it should keep retrying until the situ