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doc/source/ecosystem.rst

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@@ -445,6 +445,12 @@ provides a familiar ``DataFrame`` interface for out-of-core, parallel and distri
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Dask-ML enables parallel and distributed machine learning using Dask alongside existing machine learning libraries like Scikit-Learn, XGBoost, and TensorFlow.
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`Ibis <https://ibis-project.org/docs/>`__
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Ibis offers a standard way to write analytics code, that can be run in multiple engines. It helps in bridging the gap between local Python environments (like pandas) and remote storage and execution systems like Hadoop components (like HDFS, Impala, Hive, Spark) and SQL databases (Postgres, etc.).
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`Koalas <https://koalas.readthedocs.io/en/latest/>`__
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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pandas/tests/scalar/timedelta/test_arithmetic.py

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import numpy as np
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import pytest
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from pandas.compat import is_numpy_dev
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from pandas.errors import OutOfBoundsTimedelta
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import pandas as pd
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from pandas import (
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NaT,
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Timedelta,
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Timestamp,
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compat,
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offsets,
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)
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import pandas._testing as tm
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"nan",
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[
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np.nan,
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pytest.param(
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np.float64("NaN"),
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marks=pytest.mark.xfail(
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# Works on numpy dev only in python 3.9
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is_numpy_dev and not compat.PY39,
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raises=RuntimeWarning,
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reason="https://github.com/pandas-dev/pandas/issues/31992",
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),
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),
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np.float64("NaN"),
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float("nan"),
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],
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)

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