{
    "info": {
        "author": "Matt Moody",
        "author_email": "matt@bellwethr.com",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3"
        ],
        "description": "# Grimlock\n\nWe all know that when it comes to machine learning, it takes far more time\nto preprocess your data than it does to actually build a model. Enter, <strong>grimlock</strong>.\n\n<strong>grimlock</strong> will fix your missing values, handle data encoding, and feature scaling.\n\n## Installation\nProvided you already have NumPy, SciPy, Sci-kit Learn and Pandas already installed, the `grimlock` package is `pip`-installable:\n\n<pre>$ pip install grimlock</pre>\n\n\n### Cleaning Missing Data\nMesh of pandas.fillna() and sklearn Imputer\n\n<pre>from grimlock import clean_missing\nclean_missing(dataframe, column, clean_type='zero')</pre>\n\n\n#### Parameters\n- dataframe: dataframe variable\n- column: column name (string)\n- clean_type: 'zero' (default), 'mean', 'mode', 'most_frequent' (string)\n\n\n### Convert Categorical\nQuick conversion for categorical features (non-ordinal) \n\n<pre>from grimlock import convert_categorical\nconvert_categorical(dataframe, column, target_column)</pre>\n\n#### Parameters\n- dataframe: dataframe variable\n- column: column name (string)\n- target_column: target column name (string)\n\n\n\n### Feature Scaling\n<em>coming soon</em>\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/BellwethrInc/grimlock",
        "keywords": "",
        "license": "",
        "maintainer": "",
        "maintainer_email": "",
        "name": "grimlock",
        "package_url": "https://pypi.org/project/grimlock/",
        "platform": "",
        "project_url": "https://pypi.org/project/grimlock/",
        "project_urls": {
            "Homepage": "https://github.com/BellwethrInc/grimlock"
        },
        "release_url": "https://pypi.org/project/grimlock/0.0.1/",
        "requires_dist": [
            "numpy",
            "pandas"
        ],
        "requires_python": "",
        "summary": "Simple tool that assists with preprocessing pandas dataframes for Machine Learning.",
        "version": "0.0.1"
    },
    "last_serial": 3959939,
    "releases": {
        "0.0.1": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "40b4d7e7ec2caa79fa1020380e57db2e",
                    "sha256": "1609e90e8e7cd5f3c34270640d67fcc122addcc4a7d70bb36e4dfa2dd8a1af9c"
                },
                "downloads": -1,
                "filename": "grimlock-0.0.1-py3-none-any.whl",
                "has_sig": false,
                "md5_digest": "40b4d7e7ec2caa79fa1020380e57db2e",
                "packagetype": "bdist_wheel",
                "python_version": "py3",
                "requires_python": null,
                "size": 2760,
                "upload_time": "2018-06-14T04:29:54",
                "url": "https://files.pythonhosted.org/packages/fa/a8/21a621d2403046b78de2a7c44b13add75ebc81a26d5a23493ae638227e83/grimlock-0.0.1-py3-none-any.whl"
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "c2b0a12d94ad95a0c92615875404523b",
                    "sha256": "033b8e23f27e1321d61871bfd029b6136c3b70ba4ce5cb39514b9f6f6cda6e1e"
                },
                "downloads": -1,
                "filename": "grimlock-0.0.1.tar.gz",
                "has_sig": false,
                "md5_digest": "c2b0a12d94ad95a0c92615875404523b",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 2264,
                "upload_time": "2018-06-14T04:29:55",
                "url": "https://files.pythonhosted.org/packages/3f/34/f5272217c1255fa4a1879e390b525c5a8ef32c595b93f2d5148e37e0e49e/grimlock-0.0.1.tar.gz"
            }
        ]
    },
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "md5": "40b4d7e7ec2caa79fa1020380e57db2e",
                "sha256": "1609e90e8e7cd5f3c34270640d67fcc122addcc4a7d70bb36e4dfa2dd8a1af9c"
            },
            "downloads": -1,
            "filename": "grimlock-0.0.1-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "40b4d7e7ec2caa79fa1020380e57db2e",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": null,
            "size": 2760,
            "upload_time": "2018-06-14T04:29:54",
            "url": "https://files.pythonhosted.org/packages/fa/a8/21a621d2403046b78de2a7c44b13add75ebc81a26d5a23493ae638227e83/grimlock-0.0.1-py3-none-any.whl"
        },
        {
            "comment_text": "",
            "digests": {
                "md5": "c2b0a12d94ad95a0c92615875404523b",
                "sha256": "033b8e23f27e1321d61871bfd029b6136c3b70ba4ce5cb39514b9f6f6cda6e1e"
            },
            "downloads": -1,
            "filename": "grimlock-0.0.1.tar.gz",
            "has_sig": false,
            "md5_digest": "c2b0a12d94ad95a0c92615875404523b",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 2264,
            "upload_time": "2018-06-14T04:29:55",
            "url": "https://files.pythonhosted.org/packages/3f/34/f5272217c1255fa4a1879e390b525c5a8ef32c595b93f2d5148e37e0e49e/grimlock-0.0.1.tar.gz"
        }
    ]
}