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| 1 | +# ***************************************************************************** |
| 2 | +# Copyright (c) 2020, Intel Corporation All rights reserved. |
| 3 | +# |
| 4 | +# Redistribution and use in source and binary forms, with or without |
| 5 | +# modification, are permitted provided that the following conditions are met: |
| 6 | +# |
| 7 | +# Redistributions of source code must retain the above copyright notice, |
| 8 | +# this list of conditions and the following disclaimer. |
| 9 | +# |
| 10 | +# Redistributions in binary form must reproduce the above copyright notice, |
| 11 | +# this list of conditions and the following disclaimer in the documentation |
| 12 | +# and/or other materials provided with the distribution. |
| 13 | +# |
| 14 | +# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" |
| 15 | +# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, |
| 16 | +# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR |
| 17 | +# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR |
| 18 | +# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, |
| 19 | +# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, |
| 20 | +# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; |
| 21 | +# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, |
| 22 | +# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR |
| 23 | +# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, |
| 24 | +# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| 25 | +# ***************************************************************************** |
| 26 | + |
| 27 | +""" |
| 28 | +Expected result: |
| 29 | + A B C |
| 30 | +1 1 2 3 |
| 31 | +4 4 5 6 |
| 32 | +""" |
| 33 | + |
| 34 | +import pandas as pd |
| 35 | +import numpy as np |
| 36 | +from numba import njit |
| 37 | + |
| 38 | + |
| 39 | +@njit |
| 40 | +def dataframe_getitem(): |
| 41 | + df = pd.DataFrame({'A': [0, 1, 2, 3, 4], |
| 42 | + 'B': [1, 2, 3, 4, 5], |
| 43 | + 'C': [2, 3, 4, 5, 6]}) |
| 44 | + arr = np.array([False, True, False, False, True]) |
| 45 | + |
| 46 | + return df[arr] |
| 47 | + |
| 48 | + |
| 49 | +print(dataframe_getitem()) |
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