{
    "info": {
        "author": "Keith Lyons",
        "author_email": "lyonk71@gmail.com",
        "bugtrack_url": null,
        "classifiers": [],
        "description": "# pandas-usaddress\nThe usaddress library made easy with Pandas.\n\nAlso supports standardizing addresses to meet USPS standards.\n\n# Installation\n\npip install pandas-usaddress\n\n# Usage\n\n### Basic Parsing\n\n    import pandas as pd\n    import pandas_usaddress\n\n    #load dataframe\n    df = pd.read_csv('test_file.csv')\n\n    #initiate usaddress\n    df = pandas_usaddress.tag(df, ['address_field'])\n\n    #send output to csv\n    df.to_csv('parsed_output.csv')\n\n\n    #------------------------------additional details------------------------------\n\n    #Output and fields will be identical to usaddress\n\n### Parsing with Address Standardization\n\n    import pandas as pd\n    import pandas_usaddress\n\n    #load dataframe\n    df = pd.read_csv('test_file.csv')\n\n    #initiate usaddress\n    df = pandas_usaddress.tag(df, ['address_field'], granularity='medium', standardize=True)\n\n    #send output to csv\n    df.to_csv('parsed_output.csv')\n\n\n    #------------------------------additional details------------------------------\n\n    #The standard output for usaddress has a lot of fields. The granularity parameter\n    #allows you to condense the results you get back for different types of analysis.\n    #see parameter documentation below for all granularity options.\n\n    #Addresses are often unstandardized. The same address can come as 123 1st ST, or\n    #123 First Street, etc. This can cause issues with analysis such as aggregation,\n    #or record matching. The standardize parameter attempts to standardize the address\n    #to US Postal Service (USPS) standards.\n\n### Parsing with Address Standardization\n\n    import pandas as pd\n    import pandas_usaddress\n\n    #load dataframe\n    df = pd.read_csv('test_file.csv')\n\n    #initiate usaddress\n    df = pandas_usaddress.tag(df, ['street1', 'street2', 'city', 'state'], granularity='single', standardize=True)\n\n    #send output to csv\n    df.to_csv('parsed_output.csv')\n\n\n    #------------------------------additional details------------------------------\n\n    #You can also use pandas-usaddress to concatenate and parse multiple address lines. \n    #This can be helpful when you are working with two datasets that have different \n    #field names and you want the field names to be standardized using a specific level of\n    #granularity. It's pretty common for instance that in one dataset will concatenate \n    #address line 1 and 2, and another will not.\n\n    #You will help the parser do it's job if you try to concatenate fields in approximately\n    #same order that you would write them on an envelope.\n\n    #In this instance, we are taking multiple address fields and converting them into a\n    #single address line. That's fine to do!\n\n\n\n\n",
        "description_content_type": "text/markdown",
        "docs_url": null,
        "download_url": "",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "https://github.com/Lyonk71/pandas-usaddress",
        "keywords": "",
        "license": "MIT",
        "maintainer": "",
        "maintainer_email": "",
        "name": "pandas-usaddress",
        "package_url": "https://pypi.org/project/pandas-usaddress/",
        "platform": "",
        "project_url": "https://pypi.org/project/pandas-usaddress/",
        "project_urls": {
            "Homepage": "https://github.com/Lyonk71/pandas-usaddress"
        },
        "release_url": "https://pypi.org/project/pandas-usaddress/0.21/",
        "requires_dist": [
            "pandas",
            "usaddress"
        ],
        "requires_python": "",
        "summary": "The usaddress library made easy with Pandas.",
        "version": "0.21"
    },
    "last_serial": 4843418,
    "releases": {
        "0.11": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "3ef09acd9cd0d31d9ffc684a8158f946",
                    "sha256": "67551237788061e51ab7c2484095eda2f996e30dbf3a72fb78bf9aab589f9002"
                },
                "downloads": -1,
                "filename": "pandas_usaddress-0.11-py3-none-any.whl",
                "has_sig": false,
                "md5_digest": "3ef09acd9cd0d31d9ffc684a8158f946",
                "packagetype": "bdist_wheel",
                "python_version": "py3",
                "requires_python": null,
                "size": 320527,
                "upload_time": "2019-01-30T15:21:34",
                "url": "https://files.pythonhosted.org/packages/3a/1d/7f7ff0dbe571828cf6cf8a5158f0310a22df1a9a8f6e3884598b1d8e41f3/pandas_usaddress-0.11-py3-none-any.whl"
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "a5f7cfc3e6671d608381c15277e92764",
                    "sha256": "fc254acbef85a1b4638c6f7ee29213e654c996e341ee99e03516af776f08c9f4"
                },
                "downloads": -1,
                "filename": "pandas_usaddress-0.11.tar.gz",
                "has_sig": false,
                "md5_digest": "a5f7cfc3e6671d608381c15277e92764",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 298682,
                "upload_time": "2019-01-30T15:21:37",
                "url": "https://files.pythonhosted.org/packages/57/24/4bc5df586da390946d4fca9c9492ee7a95d553a69f9e948c62657a1298f7/pandas_usaddress-0.11.tar.gz"
            }
        ],
        "0.21": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "410a93cc631211aff3b845284a306ed8",
                    "sha256": "b6ca5d94f7b76754ecaa64357d5d30e569a4a6ea08a8638c7a3ddab73ce1390c"
                },
                "downloads": -1,
                "filename": "pandas_usaddress-0.21-py3-none-any.whl",
                "has_sig": false,
                "md5_digest": "410a93cc631211aff3b845284a306ed8",
                "packagetype": "bdist_wheel",
                "python_version": "py3",
                "requires_python": null,
                "size": 320556,
                "upload_time": "2019-02-20T03:00:26",
                "url": "https://files.pythonhosted.org/packages/fe/b7/7734c959d133d63179903d9b06d8fd11aefba1298e511deb0c601cbb93bc/pandas_usaddress-0.21-py3-none-any.whl"
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "f586f768a9ca259d950d752e7525f875",
                    "sha256": "0dbf89d99231becfbf72a88b5fea6defcd45410b643e9f7e7ee7db569fb93f28"
                },
                "downloads": -1,
                "filename": "pandas_usaddress-0.21.tar.gz",
                "has_sig": false,
                "md5_digest": "f586f768a9ca259d950d752e7525f875",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 299329,
                "upload_time": "2019-02-20T03:00:28",
                "url": "https://files.pythonhosted.org/packages/63/16/63e09bc175aee1a03dc6ba455e1f21902b3854d199b530a4cac8cf1ea9f4/pandas_usaddress-0.21.tar.gz"
            }
        ]
    },
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "md5": "410a93cc631211aff3b845284a306ed8",
                "sha256": "b6ca5d94f7b76754ecaa64357d5d30e569a4a6ea08a8638c7a3ddab73ce1390c"
            },
            "downloads": -1,
            "filename": "pandas_usaddress-0.21-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "410a93cc631211aff3b845284a306ed8",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": null,
            "size": 320556,
            "upload_time": "2019-02-20T03:00:26",
            "url": "https://files.pythonhosted.org/packages/fe/b7/7734c959d133d63179903d9b06d8fd11aefba1298e511deb0c601cbb93bc/pandas_usaddress-0.21-py3-none-any.whl"
        },
        {
            "comment_text": "",
            "digests": {
                "md5": "f586f768a9ca259d950d752e7525f875",
                "sha256": "0dbf89d99231becfbf72a88b5fea6defcd45410b643e9f7e7ee7db569fb93f28"
            },
            "downloads": -1,
            "filename": "pandas_usaddress-0.21.tar.gz",
            "has_sig": false,
            "md5_digest": "f586f768a9ca259d950d752e7525f875",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 299329,
            "upload_time": "2019-02-20T03:00:28",
            "url": "https://files.pythonhosted.org/packages/63/16/63e09bc175aee1a03dc6ba455e1f21902b3854d199b530a4cac8cf1ea9f4/pandas_usaddress-0.21.tar.gz"
        }
    ]
}