Welcome to PyMinHash documentation¶
MinHashing is a very efficient way of finding similar records in a dataset based on Jaccard similarity. PyMinHash implements efficient minhashing for Pandas dataframes. See instructions below or look at the example notebook to get started.
Installation¶
Install directly from PyPI:
pip install pyminhash
or using conda-forge:
conda install -c conda-forge pyminhash
Usage¶
Apply record matching to column name of your Pandas dataframe df as follows:
myHasher = MinHash(n_hash_tables=10)
myHasher.fit_predict(df, 'name')
This will return the row pairs from df that have non-zero Jaccard similarity.
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