pandas 1.4.2

ParametersReturns
hash_array(vals: 'ArrayLike', encoding: 'str' = 'utf8', hash_key: 'str' = '0123456789123456', categorize: 'bool' = True) -> 'np.ndarray'

Parameters

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.

Given a 1d array, return an array of deterministic integers.

Examples

See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


File: /pandas/core/util/hashing.py#254
type: <class 'function'>
Commit: