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Flattening Nested Dictionaries: Compressing Keys
In the realm of data manipulation, encountering nested dictionaries can often pose a challenge when it comes to accessing data. One common scenario is the need to flatten these complex dictionaries, creating a simpler structure with compressed keys. Understanding how to perform this task effectively is crucial for efficient data analysis and management.
Consider a nested dictionary in the following format:
{'a': 1, 'c': {'a': 2, 'b': {'x': 5, 'y' : 10}}, 'd': [1, 2, 3]}
Our goal is to transform this dictionary into a flattened version where keys are compressed to reflect their hierarchical structure:
{'a': 1, 'c_a': 2, 'c_b_x': 5, 'c_b_y': 10, 'd': [1, 2, 3]}
To achieve this, we can leverage a flattening algorithm. The approach involves iterating through the dictionary, creating new keys by concatenating parent keys with child keys and a separator, and ultimately generating a new flattened dictionary.
Implementing this algorithm in Python involves utilizing the collections.abc.MutableMapping base class to handle different dictionary types. Here's a Python implementation:
def flatten(dictionary, parent_key='', separator='_'): items = [] for key, value in dictionary.items(): new_key = parent_key + separator + key if parent_key else key if isinstance(value, MutableMapping): items.extend(flatten(value, new_key, separator=separator).items()) else: items.append((new_key, value)) return dict(items) >>> flatten({'a': 1, 'c': {'a': 2, 'b': {'x': 5, 'y' : 10}}, 'd': [1, 2, 3]}) {'a': 1, 'c_a': 2, 'c_b_x': 5, 'd': [1, 2, 3], 'c_b_y': 10}
By utilizing this algorithm, we can effectively flatten nested dictionaries, compressing keys to provide a simplified data structure for more efficient data management and analysis.
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