crandas.string_metrics

String metrics for approximate string matching or comparison and in fuzzy string searching.

`edit_distance(left, right, distance_type='levenshtein', **type_opts)`

Computes the edit distance between two string columns.

By default, the Levenshtein edit distance is computed using function levenshtein_distance.

PARAMETER	DESCRIPTION
`left`	The string columns to compare. TYPE: `CSeries or str`
`right`	The string columns to compare. TYPE: `CSeries or str`
`distance_type`	The type of edit distance to compute. Currently, the types `levenshtein`, `jaro` and `jaro-winkler` are supported. TYPE: `str` DEFAULT: `'levenshtein'`
`**type_opts`	Additional options for the edit distance type. DEFAULT: `{}`

RETURNS	DESCRIPTION
`CSeries`	CSeries with the edit distances.

`jaro_distance(left, right)`

Computes the Jaro distance between two string columns.

The Jaro distance is defined as $1 - \text{jaro similarity}$.

For more information about the Jaro similarity/distance, see here

PARAMETER	DESCRIPTION
`left`	The string columns to compare. TYPE: `CSeries or str`
`right`	The string columns to compare. TYPE: `CSeries or str`

RETURNS	DESCRIPTION
`CSeries`	CSeries with the Jaro distances (fixed-points in [0, 1]).

`jaro_similarity(left, right)`

Computes the Jaro similarity between two string columns.

For more information about the Jaro similarity/distance, see here

PARAMETER	DESCRIPTION
`left`	The string columns to compare. TYPE: `CSeries or str`
`right`	The string columns to compare. TYPE: `CSeries or str`

RETURNS	DESCRIPTION
`CSeries`	CSeries with the Jaro similarities (fixed-points in [0, 1]).

`jaro_winkler_distance(left, right, prefix_length=4, prefix_weight=0.1)`

Computes the Jaro-Winkler distance between two string columns.

The Jaro-Winkler distance is defined as $1 - \text{jaro winkler similarity}$.

For more information about the Jaro-Winkler similarity/distance, see here

PARAMETER	DESCRIPTION
`left`	The string columns to compare. TYPE: `CSeries or str`
`right`	The string columns to compare. TYPE: `CSeries or str`
`prefix_length`	Integer denoting the length of the string prefix to take into account. This needs to be a non-negative integer TYPE: `int` DEFAULT: `4`
`prefix_weight`	Weight assigned to the string prefixes matching. This should be a float between 0 and $\frac{1}{prefix length}$. TYPE: `float` DEFAULT: `0.1`

RETURNS	DESCRIPTION
`CSeries`	CSeries with the Jaro-Winkler distances (fixed-points in [0, 1]).

`jaro_winkler_similarity(left, right, prefix_length=4, prefix_weight=0.1)`

Computes the Jaro-Winkler similarity between two string columns.

For more information about the Jaro-Winkler similarity/distance, see here

PARAMETER	DESCRIPTION
`left`	The string columns to compare. TYPE: `CSeries or str`
`right`	The string columns to compare. TYPE: `CSeries or str`
`prefix_length`	Integer denoting the length of the string prefix to take into account. This needs to be a non-negative integer TYPE: `int` DEFAULT: `4`
`prefix_weight`	Weight assigned to the string prefixes matching. This should be a float between 0 and $\frac{1}{prefix length}$. TYPE: `float` DEFAULT: `0.1`

RETURNS	DESCRIPTION
`CSeries`	CSeries with the Jaro-Winkler similarities (fixed-points in [0, 1]).

`levenshtein_distance(left, right, score_cutoff=None)`

Computes the edit distance between two string columns.

Compute the Levenshtein edit distance between two string columns, i.e., the minimum number of character insertions, deletions and substitutions required to transform one string into the other.

PARAMETER	DESCRIPTION
`left`	The string columns to compare. TYPE: `CSeries or str`
`right`	The string columns to compare. TYPE: `CSeries or str`
`score_cutoff`	Maximum edit distance to consider. If the edit distance is larger than `score_cutoff`, `score_cutoff + 1` is returned. If `None`, no cutoff is applied. A lower value improves performance. TYPE: `int` DEFAULT: `None`

RETURNS	DESCRIPTION
`CSeries`	CSeries with the edit distances (integers).