Polars plugin for pair-wise distance functions

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Project description

Hellooo :)

This plugin is a work-in progress, main goal is to provide distance metrics on list, arrays and string datatypes.

The plugin provides three namespaces:

  • dist_str
    • hamming
    • levenshtein
  • dist_arr
    • euclidean
    • cosine
    • chebyshev
    • canberra
  • dist_list (these act as set similary metrics)
    • jaccard_index
    • sorensen_index
    • overlap_coef
    • cosine

Examples

import polars
import polars_distance as pld

df = pl.DataFrame({
    "foo":"hello",
    "bar":"hella world"
})

df.select(
    pld.col("foo").dist_str.hamming('bar').alias('dist')
)
┌──────┐
│ dist │
│ ---  │
│ u32  │
╞══════╡
│ 1    │
└──────┘


df.select(
    pld.col('foo').dist_str.levenshtein('bar').alias('dist')
)
┌──────┐
│ dist │
│ ---  │
│ u32  │
╞══════╡
│ 6    │
└──────┘



df = pl.DataFrame(
    {
        "arr": [[1, 2, 10]],
        "arr2": [[2, 5, 9]],
    },
    schema={
        "arr": pl.Array(inner=pl.Float64, width=3),
        "arr2": pl.Array(inner=pl.Float64, width=3),
    },
)
df.select(pld.col('arr').dist_arr.euclidean('arr2').alias('dist'))
shape: (1, 1)
┌──────────┐
│ dist     │
│ ---      │
│ f64      │
╞══════════╡
│ 3.316625 │
└──────────┘

Project details

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0.5.0

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0.2.0

0.1.5

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