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reconciler\n\n\u003c!-- badges: start --\u003e\n[![license](https://img.shields.io/badge/license-BSD%202--Clause-green)](https://github.com/jvfe/reconciler/blob/master/LICENSE)\n[![pytest status](https://github.com/jvfe/reconciler/workflows/pytest/badge.svg)](https://github.com/jvfe/reconciler/actions)\n[![documentation status](https://github.com/jvfe/reconciler/workflows/docs/badge.svg)](https://jvfe.github.io/reconciler/)\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4088488.svg)](https://doi.org/10.5281/zenodo.4088488)\n\u003c!-- badges: end --\u003e\n\n`reconciler` is a python package to reconcile tabular data with various reconciliation services, such as \n[Wikidata](https://www.wikidata.org/wiki/Wikidata:Main_Page), working similarly to what [OpenRefine](https://openrefine.org/) \ndoes, but entirely within Python, using Pandas.\n\n## Quickstart\n\nYou can install the latest version of reconciler from PyPI with:\n\n``` bash\npip install reconciler\n```\n\nThen to use it:\n\n```python\nfrom reconciler import reconcile\nimport pandas as pd\n\n# A DataFrame with a column you want to reconcile.\ntest_df = pd.DataFrame(\n    {\n        \"City\": [\"Rio de Janeiro\", \"São Paulo\", \"São Paulo\", \"Natal\"],\n        \"Country\": [\"Q155\", \"Q155\", \"Q155\", \"Q155\"]\n    }\n)\n\n# Reconcile against type city (Q515), getting the best match for each item.\nreconciled = reconcile(test_df[\"City\"], type_id=\"Q515\")\n```\n\nThe resulting dataframe would look like this:\n\n| id      | match   | name           |   score | type                   | type_id   | input_value    |\n|:--------|:--------|:---------------|--------:|:-----------------------|:-----------|:---------------|\n| Q8678   | True    | Rio de Janeiro |     100 | city                   | Q515       | Rio de Janeiro |\n| Q174    | True    | São Paulo      |     100 | city                   | Q515       | São Paulo      |\n| Q131620 | True    | Natal          |     100 | municipality of Brazil | Q3184121   | Natal          |\n\nIn case you want to ensure the results are cities from Brazil, you can specify the property_mapping argument with\na specific property-value pair:\n\n```python\n# Reconcile against type city (Q515) and items have the country (P17) property equals to Brazil (Q155)\nreconciled = reconcile(test_df[\"City\"], type_id=\"Q515\", property_mapping={\"P17\": test_df[\"Country\"]})\n```\n\n## Options\nThe `reconcile()` function accepts several options.\n\n* `type_id` - The type of items to reconcile against per the [API specification](https://reconciliation-api.github.io/specs/latest/#structure-of-a-reconciliation-query).\n* `top_res` - Either the number of results to return per entry or the string 'all' to return all results.\n* `property_mapping` - A list of properties to filter results on per the [API specification](https://reconciliation-api.github.io/specs/latest/#structure-of-a-reconciliation-query).\n* `reconciliation_endpoint` - The reconciliation service to connect to.  Defaults to `https://wikidata.reconci.link/en/api`.\n\n## Other very useful packages\n\nAlthough my opinion may be biased, I think `reconciler` is a pretty nice package.\nBut the thing is, it probably won't fulfill all your Wikidata-related needs.\nHere are other packages that could help with that:\n\n* [WikidataIntegrator](https://github.com/SuLab/WikidataIntegrator) has a lot of very nice, low-level, functions \n    for dealing with various wikidata-related activities, such as item acquisition and programmatic editing.\n\n* [wikidata2df](https://github.com/jvfe/wikidata2df) is a very simple utility package for quickly and easily\n    turning wikidata SPARQL queries into Pandas DataFrames.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjvfe%2Freconciler","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjvfe%2Freconciler","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjvfe%2Freconciler/lists"}