prateek-malhotra / fuzzy_pandas

Fuzzy matches and merging of datasets in pandas using csvmatch

fuzzy_pandas

A razor-thin layer over csvmatch that allows you to do fuzzy matching with pandas dataframes.

Installation

pip install fuzzy_pandas

Usage

To borrow 100% from the original repo, say you have one CSV file such as:

name,location,codename
George Smiley,London,Beggerman
Percy Alleline,London,Tinker
Roy Bland,London,Soldier
Toby Esterhase,Vienna,Poorman
Peter Guillam,Brixton,none

And another such as:

Person Name,Location
Maria Andreyevna Ostrakova,Russia
Otto Leipzig,Estonia
George SMILEY,London
Peter Guillam,Brixton
Konny Saks,Oxford

You can then use fdp.fuzzy_merge to see which names are in both files:

import pandas as pd
import fuzzy_pandas as fpd

df1 = pd.read_csv("data1.csv")
df2 = pd.read_csv("data2.csv")

fpd.fuzzy_merge(df1, df2,
                left_on=['name'],
                right_on=['Person Name'],
                ignore_case=True,
                keep='match')

.	name	Person Name
0	George Smiley	George SMILEY
1	Peter Guillam	Peter Guillam

That's a terrible, non-fuzzy example, though. Maybe you should hop to the next section if you want something more meaningful?

Examples

You can find examples, including different types of matches (edit distance, phonetic, etc), in this notebook from the examples folder.

Options

All of these options can be sent as arguments to fpd.fuzzy_merge.

• left : DataFrame
• right : DataFrame - Object to merge left with
• on : str or list - Column names to compare. These must be found in both DataFrames.
• left_on : str or list - Column names to compare in the left DataFrame.
• right_on : str or list - Column names to compare in the right DataFrame.
• keep : str { 'all', 'match' } - Overrides keep_left and keep_right
• keep_left : str or list, default 'all' - List of columns to preserve from the left DataFrame. - If 'all', preserve all columns. - If 'match', preserve left_on matching) column. - If any other string, just keeps that one column.
• keep_right : str or list, default 'all' - List of columns to preserve from the right DataFrame. - If 'all', preserve all columns. Defaults to right_on. - If 'match', preserve right_on (matching) column. - If any other string, just keeps that one column.
• method : str or list, default 'exact' - Perform a fuzzy match, and an optional specified algorithm. - Multiple algorithms can be specified which will apply to each field respectively. - Options: * exact: exact matches * levenshtein: string distance metric * jaro: string distance metric * metaphone: phoenetic matching algorithm * bilenko: prompts for matches
• threshold : float or list, default 0.6 - The threshold for a fuzzy match as a number between 0 and 1 - Multiple numbers will be applied to each field respectively
• ignore_case : bool, default False - Ignore case (default is case-sensitive)
• ignore_nonalpha : bool, default False - Ignore non-alphanumeric characters
• ignore_nonlatin : bool, default False - Ignore characters from non-latin alphabets - Accented characters are compared to their unaccented equivalent
• ignore_order_words : bool, default False - Ignore the order words are given in
• ignore_order_letters : bool, default False - Ignore the order the letters are given in, regardless of word order
• ignore_titles : bool, default False - Ignore a predefined list of name titles (such as Mr, Ms, etc)
• join : { 'inner', 'left-outer', 'right-outer', 'full-outer' }

For more how-to information, check out the examples folder or the the original repo.