3 examples of 'group by count pandas' in Python

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90def crosscount(df, col_list):
91 """
92 tools for multy thread bi_count
93 """
94 assert isinstance(col_list, list)
95 assert len(col_list) >= 2
96 name = "count_"+ '_'.join(col_list)
97 df[name] = df.groupby(col_list)[col_list[0]].transform('count')
98 return df
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91def apply_counts_to_group(group):
92 """Add the _count and _group_count fields to a group"""
93 if '_subgroup' in group:
94 subgroups = apply_counts(group['_subgroup'])
95 group['_subgroup'] = subgroups
96 group['_count'] = sum(subgroup['_count'] for subgroup in subgroups)
97 group['_group_count'] = len(subgroups)
98 return group
128def group_by(self, dataset, field_name=None):
129 if field_name is None:
130 field_name = self.field_name
131
132 items = self._get_base_set(dataset)
133
134 # Get the min and max
135 min_val, max_val = self._get_range(items, field_name)
136 if min_val is None:
137 return []
138
139 # Get a good bin size
140 bin_size = self._get_bin_size(min_val, max_val)
141
142 # Calculate a grouping variable
143 items = self._add_grouping_value(items, bin_size, field_name)
144
145 # Group by it
146 items = items.values('value')
147
148 # Count the messages in each group
149 result = self._annotate(items)
150
151 return BinnedResultSet(result, bin_size, min_val, max_val)

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