sdc/examples/dataframe/dataframe_count.py at master · IntelPython/sdc

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# *****************************************************************************

# 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.

# 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

# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,

# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

# *****************************************************************************

# result

# A 4

# B 4

# C 3

# dtype: int64

import pandas as pd

import numpy as np

from numba import njit

@njit

def dataframe_count():

df = pd.DataFrame({"A": [.2, .0, .6, .2],

"B": [2, 0, 6, 2],

"C": [-1, np.nan, 1, np.inf]})

return df.count()

print(dataframe_count())

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