3 examples of 'group by count pandas' in Python

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def crosscount(df, col_list):
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    """
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    tools for multy thread bi_count
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    """
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    assert isinstance(col_list, list)
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    assert len(col_list) >= 2
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    name = "count_"+ '_'.join(col_list)
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    df[name] = df.groupby(col_list)[col_list[0]].transform('count')
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    return df

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def apply_counts_to_group(group):
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    """Add the _count and _group_count fields to a group"""
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    if '_subgroup' in group:
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        subgroups = apply_counts(group['_subgroup'])
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        group['_subgroup'] = subgroups
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        group['_count'] = sum(subgroup['_count'] for subgroup in subgroups)
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        group['_group_count'] = len(subgroups)
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    return group

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def group_by(self, dataset, field_name=None):
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    if field_name is None:
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        field_name = self.field_name
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    items = self._get_base_set(dataset)
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    # Get the min and max
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    min_val, max_val = self._get_range(items, field_name)
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    if min_val is None:
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        return []
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    # Get a good bin size
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    bin_size = self._get_bin_size(min_val, max_val)
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    # Calculate a grouping variable
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    items = self._add_grouping_value(items, bin_size, field_name)
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    # Group by it
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    items = items.values('value')
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    # Count the messages in each group
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    result = self._annotate(items)
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    return BinnedResultSet(result, bin_size, min_val, max_val)