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data hash pandas / numpy objects
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é )Ú annotationsN)Ú TYPE_CHECKING)Úhash_object_array)Ú is_list_like)ÚCategoricalDtype)Ú ABCDataFrameÚABCExtensionArrayÚABCIndexÚ ABCMultiIndexÚ ABCSeries)ÚHashableÚIterableÚIterator)Ú ArrayLikeÚnpt)Ú DataFrameÚIndexÚ
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Parameters
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----------
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arrays : Iterator[np.ndarray]
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num_items : int
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Returns
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-------
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np.ndarray[uint64]
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Should be the same as CPython's tupleobject.c
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Return a data hash of the Index/Series/DataFrame.
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|
Parameters
|
----------
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obj : Index, Series, or DataFrame
|
index : bool, default True
|
Include the index in the hash (if Series/DataFrame).
|
encoding : str, default 'utf8'
|
Encoding for data & key when strings.
|
hash_key : str, default _default_hash_key
|
Hash_key for string key to encode.
|
categorize : bool, default True
|
Whether to first categorize object arrays before hashing. This is more
|
efficient when the array contains duplicate values.
|
|
Returns
|
-------
|
Series of uint64, same length as the object
|
|
Examples
|
--------
|
>>> pd.util.hash_pandas_object(pd.Series([1, 2, 3]))
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0 14639053686158035780
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1 3869563279212530728
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2 393322362522515241
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dtype: uint64
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Hash an MultiIndex / listlike-of-tuples efficiently.
|
|
Parameters
|
----------
|
vals : MultiIndex or listlike-of-tuples
|
encoding : str, default 'utf8'
|
hash_key : str, default _default_hash_key
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|
Returns
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ndarray[np.uint64] of hashed values
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|
|
Parameters
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----------
|
vals : ndarray or ExtensionArray
|
encoding : str, default 'utf8'
|
Encoding for data & key when strings.
|
hash_key : str, default _default_hash_key
|
Hash_key for string key to encode.
|
categorize : bool, default True
|
Whether to first categorize object arrays before hashing. This is more
|
efficient when the array contains duplicate values.
|
|
Returns
|
-------
|
ndarray[np.uint64, ndim=1]
|
Hashed values, same length as the vals.
|
|
Examples
|
--------
|
>>> pd.util.hash_array(np.array([1, 2, 3]))
|
array([ 6238072747940578789, 15839785061582574730, 2185194620014831856],
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dtype=uint64)
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