NOTE: I'd originally opened a PR to address this, but am now busy with other obligations + other PRs to respond to. So I'm opening it up as a good first issue for now, and will return to work on it if nobody takes it.

In pandas/core/groupby/generic.py::DataFrameGroupBy::_wrap_applied_output, it seems this branch is never reached:

In the PCA section there is the following quote:

We see that these 150 components account for just over 90% of the variance.

While not inaccurate (150 componen

Alexnet implementation in tensorflow has incomplete architecture where 2 convolution neural layers are missing. This issue is in reference to the python notebook mentioned below.

https://github.com/donnemartin/data-science-ipython-notebooks/blob/master/deep-learning/tensor-flow-examples/notebooks/3_neural_networks/alexnet.ipynb

I think we should keep dependencies in requirements.txt, and we should read dependencies from requirements.txt instead of keep another copy in setup.py.

What is the expected behavior for dask.array.full() for a non-scalar fill_value?

The numpy.full() signature in the documentation mentions "scalar" for fill_value.
https://docs.scipy.org/doc/numpy/reference/generated/numpy.full.html

However, it'll broadcast non-scalar values if it can:

a = np.full((3, 2), [1, 2])

Since dask.array.full() wraps this function, it

Missing functionality
Ability to have descriptions of variables alongside their descriptive statistics. Most often when EDA is being performed we are unfamiliar with a dataset. Being able to incorporate variable descriptions into the reports would be useful.

Proposed feature
Ability to provide a variable dictionary {"var_name": "description"} to the ProfileReport function. These des

Describe the problem

We should test on larger datasets that are commonly used in

If would be great if the following worked:

import cudf
df = cudf.datasets.timeseries()
df.mean()

Currently we get this

AttributeError: 'CategoricalColumn' object has no attribute 'mean'

Typically the solution in Pandas is to strip out the non-numeric columns first

df._get_numeric_data().mean()

We should consider adding t

Most of the people who start out new don't find a latest feed of community hyped resources on ML and DL topics. It would be pretty good if we add a Reddit section.
If you're fine with this suggestion I'll put up a PR with the update 😄

According to https://www.weld.rs/grizzly/ the command to get started is $ pip install grizzly however this doesn't seem to be correct. The grizzly package on PyPi is some sort of USB driver.

I believe the documentation should be: pip install pygrizzly but that is failing for me, too

This is motivated by the weirdness that is Excel's "center across selection". After playing around with Excel for a bit, I now understand how this works. And it makes complete sense that it is achieved in XlsxWriter the way it is.

However, I think it would be nice to have an additional worksheet method which makes it easier. I was thinking format_range, which would be somewhat like `merge_ran

The foreign exchange is just metadata, thus only available as json format (using the 'csv' or 'pandas' format will raise an Error)

This is incorrect

Implement Series.reindex.

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.reindex.html

It's a fairly common request to get the size of data for each symbol in VersionStore and currently I just use a Mongo js script to get it, but it would be nice to have a util in VersionStore or otherwise to do the same.

Instructions for GPU integration are absent in docs, it could be added. The tasks include:

1. DataFrame (include installing dependencies like RAPIDS)
2. Tensor
3. Distributed

I always use Pandas to deal with my neuroscience data (multi-dimension). It is annoying to stack and unstack all the time and I heard Xarray is designed for multi-dimension data.

In neuroscience research, we usually have multiple participants and we will test them different times, which means the data may look like this:

• participant A:
  • 2*5*100 matrix
• participant B:
  • 2\

The procedure for downloading the "en_vectors_web_lg" in spacy. by downloading and unzipping the file, and shifting it to the appropriate directory, as illustrated here is l

It would be nice to have some general developer documentation for potential contributors to help in cases such as #510, etc.

What are the best steps to take towards accomplishing this? Maybe something similar (albeit not all details needed) to the Pandas developer docs?

I've begun an implementation of this on my fork, basicall

Running the next code in the terminal works as expected, .count() returns the number of rows as an int, since the option interactive is set to True:

>>> import ibis
>>> print(ibis.__version__)
1.3.0+24.gd00a112.dirty
>>> ibis.options.interactive = True
>>> conn = ibis.sqlite.connect('geography.db')
>>> conn.table('countries').count()
252

But running the same exact c