text: # *****************************************************************************
  # Copyright (c) 2020, Intel Corporation All rights reserved.
  #
  # Redistribution and use in source and binary forms, with or without
  # modification, are permitted provided that the following conditions are met:
  #
  #     Redistributions of source code must retain the above copyright notice,
  #     this list of conditions and the following disclaimer.
  #
  #     Redistributions in binary form must reproduce the above copyright notice,
  #     this list of conditions and the following disclaimer in the documentation
  #     and/or other materials provided with the distribution.
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  # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
  # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
  # THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
  # PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
  # CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
  # EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
  # PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
  # OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
  # WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
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  # *****************************************************************************
  
  """
  Expected result:
     A  B  C
  1  1  2  3
  4  4  5  6
  """
  
  import pandas as pd
  import numpy as np
  from numba import njit
  
  
  @njit
  def dataframe_getitem():
      df = pd.DataFrame({'A': [0, 1, 2, 3, 4],
                         'B': [1, 2, 3, 4, 5],
                         'C': [2, 3, 4, 5, 6]})
      arr = np.array([False, True, False, False, True])
  
      return df[arr]
  
  
  print(dataframe_getitem())
  