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        "author": "Stefan Wehrmeyer",
        "author_email": "mail@stefanwehrmeyer.com",
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        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.5",
            "Topic :: Scientific/Engineering"
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        "description": "# pandas-linker\n\n`pandas-linker` runs comparison windows over different sortings of a pandas DataFrame and links the rows via assigned UUIDs. This library does not actually do any duplicate detection. Instead it provides a harness to run your own comparison functions on your data.\n\nThis library is meant for datasets of a size where comparing every row with every other is undesirable. Instead you can decide on a sorting order of the DataFrame and only compare every row with every other inside a sliding window.\n\n## Install\n\n```\npip install pandas-linker\n```\n\n## Example\n\nLet's say you have a DataFrame like this:\n\n [ix] | name | country\n------|------|--------\n   0  | Pete | Spain\n   1  | Mary | USA\n   2  | Bart | US\n   3  | Mary | US\n\nand you want to detect similar rows and mark them as such. Here's how to do that:\n\n```python\nfrom pandas_linker import get_linker\n\n\ndef compare_rows(a, b):\n    ''' Example function that decides if two rows represent same entity.'''\n    return a['name'] in b['name'] or b['name'] in a['name']\n\n# df is a pandas.DataFrame with a unique index\n\nwith get_linker(df, field='uid') as linker:\n\n    print('Comparing in 10 row window sorted by name')\n    linker(sort_cols=['name'], window_size=10, cmp=compare_rows)\n\n    print('Comparing in 15 row window sorted by country')\n    linker(sort_cols=['country'], window_size=15, cmp=compare_rows)\n\n```\n\nAfter running the linker the process is complete\n\n [ix] | name | country | uid\n------|------|---------|----\n   0  | Pete | Spain   | 7509781940fc471cad5dc32944652d70\n   1  | Mary | USA     | 8f8dccd91568472daf740e9160349d6c\n   2  | Bart | US      | 12b55fbe80f64d378193acd727b0e051\n   3  | Mary | US      | 8f8dccd91568472daf740e9160349d6c\n\nNote that both \"Mary\" rows in the DataFrame have been identified as representing\nthe same entity and were assigned the same UUID.",
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        "license": "MIT",
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        "name": "pandas-linker",
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        "summary": "Linking rows of pandas dataframes",
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