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Indexing

Migrating from recordlinkage<=0.8.2 to recordlinkage>=0.9? Click here

The indexing module is used to make pairs of records. These pairs are called candidate links or candidate matches. There are several indexing algorithms available such as blocking and sorted neighborhood indexing. See the following references for background information about indexation.

[christen2012]Christen, P. (2012). Data matching: concepts and techniques for record linkage, entity resolution, and duplicate detection. Springer Science & Business Media.
[christen2008]Christen, P. (2008). Febrl - A Freely Available Record Linkage System with a Graphical User Interface.
 
.. automodule:: recordlinkage.indexing


.. autoclass:: FullIndex
        :members:
        :inherited-members:


.. autoclass:: BlockIndex
        :members:
        :inherited-members:


.. autoclass:: SortedNeighbourhoodIndex
        :members:
        :inherited-members:


.. autoclass:: RandomIndex
        :members:
        :inherited-members:

Migrating

Version 0.9 of the Python Record Linkage Toolkit uses a new indexing API. The new indexing API uses a different syntax. With the new API, each algorithm has it's own class. See the following example to migrate a blocking index:

Old (linking):

cl = recordlinkage.Pairs(df_a, df_b)
cl.block('given_name')

New (linking):

cl = recordlinkage.BlockIndex('given_name')
cl.index(df_a, df_b)

Old (deduplication):

cl = recordlinkage.Pairs(df_a)
cl.block('given_name')

New (deduplication):

cl = recordlinkage.BlockIndex('given_name')
cl.index(df_a)