Data Science

Describe the issue linked to the documentation

The "20 newsgroups text" dataset can be accessed within scikit-learn using defined functions. The dataset contains some text which is considered culturally insensitive.

Suggest a potential alternative/fix

Add a section in the dataset documentation, possibly above the "Recommendation" section called "Data Considerations".
https://

To help test PRs like apache/superset#16393

We should create multiple databases & schemas for the ephemeral test environment.

From a slack message:

Hi, So I observed that if you deploy a deployment with more replicas than the available resources serve keeps trying to allocate them waiting for autoscaler.

(pid=125021) 2021-09-07 20:52:42,899    INFO http_state.py:75 -- Starting HTTP proxy with name 'pfaUeM:SERVE_CONTROLLER_ACTOR:SERVE_PROXY_ACTOR-node:192.168.1.13-0' on node 'node:192.168.1.13-0' listening on '12

We currently print a warning as shown below when a user sets both a widget default value in the function defining the widget as well as a widget value via the widget's key in st.session_state

While we certainly want to do this by default since doing both is not recommended, we should provide a

🚀 Feature

Motivation

With the recent ability to log hyperparameters on the datamodule, this exception was introduced in case the keys had overlaps between the lightning module and datamodule
https://github.com/PyTorchLightning/pytorch-lightning/blob/ec828b826717cd3b5beabcb6d0cacf41b2320a98/pytorch_lightning/trainer

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

Minor, non-breaking issue found during review of #13094.

If path of the active virtualenv is a substring of another virtualenv, IPython started from the second one will not fire up any warning.

Example:

virtualenv aaa
virtualenv aaaa
. aaaa/bin/activate
python -m pip install ipython
. aaa/bin/activate
aaaa/bin/ipython

Expected behavior after executing aaaa/bin/ipython:

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

Is your feature request related to a problem? Please describe.
I typically used compressed datasets (e.g. gzipped) to save disk space. This works fine with AllenNLP during training because I can write my dataset reader to load the compressed data. However, the predict command opens the file and reads lines for the Predictor. This fails when it tries to load data from my compressed files.