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://

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

Apache Arrow has a first-class tabular file format, Feather, that the Ray Datasets IO layer should support. Combined with Ray Datasets' existing .from_arrow() and .to_arrow() APIs, this would round out our "all-Arrow" experience, which should be as nice as possible given our "distributed Arrow dataset" positioning.

Implementation Note

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

Proposed refactoring or deprecation

Rename ProgressBar callback to TQDMProgressBar (https://github.com/tqdm/tqdm)
https://github.com/daniellepintz/pytorch-lightning/blob/a49690dfa3502508c8765e6bb46ded17e561af8e/pytorch_lightning/callbacks/progress/progress.py#L55-L55

Motivation

After we added the RichProgressBar in PyTorchLightning/pytorch-lightning#8929, i

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

Steps to reproduce

• Create a test1.py file with the contents import sys; print(1, sys.argv) in the current directory
• Create a test2.py file with the contents print(2) in the current directory

Expected result

As per the IPython reference:
Both files are executed in sequence, the

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

In gensim/models/fasttext.py:

    model = FastText(
        vector_size=m.dim,
        vector_size=m.dim,
        window=m.ws,
        window=m.ws,
        epochs=m.epoch,
        epochs=m.epoch,
        negative=m.neg,
        negative=m.neg,
        # FIXME: these next 2 lines read in unsupported FB FT modes (loss=3 softmax or loss=4 onevsall,
        # or model=3 supervi

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.