pandas
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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
| a | b |
|---|
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Improve readability of thread id based branches by giving them more descriptive names.
e.g.
if (!t) // is actually a t == 0and
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
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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
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in this PR: pandas-dev/pandas#36346
we updated
.searchsorted()on the datetimelike indexes to accept string and a list-like, we should add some examples to the doc-string.cc @jbrockmendel