this has the built docs: https://pandas.pydata.org/pandas-docs/dev/ rather than https://dev.pandas.io/, so need to update the contributing docs.

When merging a dask dataframe, the resulting index is duplicated - seems to be because of the number of partitions. See example below:

import pandas as pd
import dask.dataframe as dd

a = dd.from_pandas(pd.DataFrame({'a': [1,2,3,4]}), npartitions=2)
b = pd.DataFrame({'a': [1,2,3,4], 'b': [2,3,4,5]})

a.merge(b, on='a').compute()

Returns

|

Improve readability of thread id based branches by giving them more descriptive names.

e.g.

if (!t) // is actually a t == 0

and

https://github.com/rapidsai/cudf/blob/57ef76927373d7260b6a0eda781e59a4c563d36e/cpp/src/io/statistics/column_stats.cu#L285
Is actually a lane_id == 0
As demonstrated in rapidsai/cudf#6241 (comment), pr

Support Series.median()

What happened:
xr.DataArray([1], coords=[('onecoord', [2])]).sel(onecoord=2).to_dataframe(name='name') raise an exception ValueError: no valid index for a 0-dimensional object

What you expected to happen:

the same behavior as: xr.DataArray([1], coords=[('onecoord', [2])]).to_dataframe(name='name')

Anything else we need to know?:

I see that the array after the select