Python pandas._libs.lib.count_level_2d() Examples

The following are 5 code examples of pandas._libs.lib.count_level_2d(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module pandas._libs.lib , or try the search function .
Example #1
Source File: generic.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def count(self):
        """ Compute count of group, excluding missing values """
        from pandas.core.dtypes.missing import _isna_ndarraylike as _isna

        data, _ = self._get_data_to_aggregate()
        ids, _, ngroups = self.grouper.group_info
        mask = ids != -1

        val = ((mask & ~_isna(np.atleast_2d(blk.get_values())))
               for blk in data.blocks)
        loc = (blk.mgr_locs for blk in data.blocks)

        counter = partial(
            lib.count_level_2d, labels=ids, max_bin=ngroups, axis=1)
        blk = map(make_block, map(counter, val), loc)

        return self._wrap_agged_blocks(data.items, list(blk))
Example #2
Source File: groupby.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def count(self):
        """ Compute count of group, excluding missing values """
        from pandas.core.dtypes.missing import _isna_ndarraylike as isna

        data, _ = self._get_data_to_aggregate()
        ids, _, ngroups = self.grouper.group_info
        mask = ids != -1

        val = ((mask & ~isna(np.atleast_2d(blk.get_values())))
               for blk in data.blocks)
        loc = (blk.mgr_locs for blk in data.blocks)

        counter = partial(count_level_2d, labels=ids, max_bin=ngroups, axis=1)
        blk = map(make_block, map(counter, val), loc)

        return self._wrap_agged_blocks(data.items, list(blk))
Example #3
Source File: generic.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def count(self):
        """ Compute count of group, excluding missing values """
        from pandas.core.dtypes.missing import _isna_ndarraylike as _isna

        data, _ = self._get_data_to_aggregate()
        ids, _, ngroups = self.grouper.group_info
        mask = ids != -1

        val = ((mask & ~_isna(np.atleast_2d(blk.get_values())))
               for blk in data.blocks)
        loc = (blk.mgr_locs for blk in data.blocks)

        counter = partial(
            lib.count_level_2d, labels=ids, max_bin=ngroups, axis=1)
        blk = map(make_block, map(counter, val), loc)

        return self._wrap_agged_blocks(data.items, list(blk))
Example #4
Source File: groupby.py    From Splunking-Crime with GNU Affero General Public License v3.0 6 votes vote down vote up 
def count(self):
        """ Compute count of group, excluding missing values """
        from functools import partial
        from pandas.core.dtypes.missing import _isna_ndarraylike as isna

        data, _ = self._get_data_to_aggregate()
        ids, _, ngroups = self.grouper.group_info
        mask = ids != -1

        val = ((mask & ~isna(np.atleast_2d(blk.get_values())))
               for blk in data.blocks)
        loc = (blk.mgr_locs for blk in data.blocks)

        counter = partial(count_level_2d, labels=ids, max_bin=ngroups, axis=1)
        blk = map(make_block, map(counter, val), loc)

        return self._wrap_agged_blocks(data.items, list(blk))
Example #5
Source File: groupby.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up 
def count(self):
        """ Compute count of group, excluding missing values """
        from functools import partial
        from pandas.core.dtypes.missing import _isna_ndarraylike as isna

        data, _ = self._get_data_to_aggregate()
        ids, _, ngroups = self.grouper.group_info
        mask = ids != -1

        val = ((mask & ~isna(blk.get_values())) for blk in data.blocks)
        loc = (blk.mgr_locs for blk in data.blocks)

        counter = partial(count_level_2d, labels=ids, max_bin=ngroups, axis=1)
        blk = map(make_block, map(counter, val), loc)

        return self._wrap_agged_blocks(data.items, list(blk))