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correct doc for DF.mean (#688)
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# *****************************************************************************
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# Copyright (c) 2020, Intel Corporation All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are met:
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#
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# Redistributions of source code must retain the above copyright notice,
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# this list of conditions and the following disclaimer.
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#
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# Redistributions in binary form must reproduce the above copyright notice,
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# this list of conditions and the following disclaimer in the documentation
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# and/or other materials provided with the distribution.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
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# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
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# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
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# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
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# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
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# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
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# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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# *****************************************************************************
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"""
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Expected result:
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A 0.25
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B 2.50
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C inf
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dtype: float64
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"""
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import pandas as pd
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import numpy as np
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from numba import njit
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@njit
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def dataframe_mean():
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df = pd.DataFrame({"A": [.2, .0, .6, .2],
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"B": [2, 0, 6, 2],
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"C": [-1, np.nan, 1, np.inf]})
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return df.mean()
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print(dataframe_mean())

sdc/datatypes/hpat_pandas_dataframe_functions.py

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@sdc_overload_method(DataFrameType, 'mean')
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def mean_overload(df, axis=None, skipna=None, level=None, numeric_only=None):
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"""
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Pandas DataFrame method :meth:`pandas.DataFrame.mean` implementation.
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Intel Scalable Dataframe Compiler User Guide
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********************************************
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.. only:: developer
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Pandas API: pandas.DataFrame.mean
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Test: python -m sdc.runtests -k sdc.tests.test_dataframe.TestDataFrame.test_mean*
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Limitations
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-----------
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Parameters ``axis``, ``level`` and ``numeric_only`` are unsupported.
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Parameters
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-----------
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df: :class:`pandas.DataFrame`
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input arg
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axis:
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*unsupported*
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skipna:
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*unsupported*
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level:
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*unsupported*
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numeric_only:
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*unsupported*
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Examples
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--------
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.. literalinclude:: ../../../examples/dataframe/dataframe_mean.py
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:language: python
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:lines: 35-
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:caption: Return the mean of the values for the columns.
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:name: ex_dataframe_mean
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Returns
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-------
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:obj:`pandas.Series` or `pandas.DataFrame`
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return the mean of the values for the requested axis.
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"""
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.. command-output:: python ./dataframe/dataframe_mean.py
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:cwd: ../../../examples
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.. seealso::
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:ref:`Series.mean <pandas.Series.mean>`
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Return the mean of the values for the Series.
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Intel Scalable Dataframe Compiler Developer Guide
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*************************************************
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Pandas DataFrame method :meth:`pandas.DataFrame.mean` implementation.
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.. only:: developer
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Test: python -m sdc.runtests -k sdc.tests.test_dataframe.TestDataFrame.test_mean*
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"""
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name = 'mean'
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