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# Group Management
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Functions for creating and managing hierarchical group structures. Groups provide organizational capabilities for complex datasets with multiple related arrays and enable hierarchical data organization.
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## Capabilities
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### Group Creation
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```python { .api }
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def group(
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    store: StoreLike = None,
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    overwrite: bool = False,
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    chunk_store: StoreLike = None,
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    cache_attrs: bool = True,
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    synchronizer: Any = None,
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    path: str = None,
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    **kwargs
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) -> Group
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```
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Create or open a zarr group.
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```python { .api }
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def create_group(
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    store: StoreLike,
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    path: str = None,
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    overwrite: bool = False,
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    chunk_store: StoreLike = None,
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    cache_attrs: bool = True,
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    synchronizer: Any = None,
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    **kwargs
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) -> Group
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```
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Create a new zarr group in specified storage.
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```python { .api }
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def create_hierarchy(
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    path: str,
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    *args,
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    **kwargs
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) -> None
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```
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Create a hierarchical directory structure for zarr groups.
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## Usage Examples
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### Basic Group Operations
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```python
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import zarr
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# Create group
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grp = zarr.group()
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# Add arrays to group  
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grp.create_array('temperature', shape=(365, 100, 100))
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grp.create_array('pressure', shape=(365, 100, 100))
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# Create nested groups
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weather = grp.create_group('weather_data')
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weather.create_array('daily_temp', shape=(365,))
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```
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### Persistent Group Storage
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```python
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# Create group in storage
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grp = zarr.create_group('experiment_data.zarr')
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# Organize data hierarchically
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raw_data = grp.create_group('raw')
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processed = grp.create_group('processed')
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results = grp.create_group('results')
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# Add arrays at different levels
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raw_data.create_array('sensor1', shape=(1000, 10))
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processed.create_array('filtered', shape=(1000, 10))
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results.create_array('summary', shape=(10,))
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```