{
    "data_id": "43361",
    "name": "Condominium-Comparable-Rental-Income-in-NYC",
    "exact_name": "Condominium-Comparable-Rental-Income-in-NYC",
    "version": 1,
    "version_label": "v1.0",
    "description": "If you think the dataset is useful please vote for it, it's an assignment from my data science class, I'll be appreciate! :))\nContext\nThe Department of Finance (DOF) is required by NY State law to value condominiums or cooperatives as if they were residential rental apartment buildings. DOF uses income information from rental properties similar in physical features and location to the condominiums or cooperatives. DOF applies this income data to the condominium or cooperative to determine its value in the same way DOF values rental apartment buildings. This report includes information at a condominium suffix level which represents a subdivision of the condominium since DOF values condominiums at a suffix level. A condominium may have more than one suffix.\nContent\nThis data set contains the reports from 2012-2018.\nBoro-Block-Lot    \nThe Borough-Block-Lot location of the subject condominium. The lot identifies the condominium billing lot generally associated with the condominium management organization.\nAddress\nThe Street Address of the property\nNeighborhood    \nDepartment of Finance determines the neighborhood name in the course of valuing properties. The common name of the neighborhood is generally the same as the name Finance designates. However, there may be slight differences in neighborhood boundary lines.\nBuilding Classification    \nThe Building Class code is used to describe a propertys use. This report includes the two character code as well as the description of the building class.\nTotal Units\nTotal number of units in the building\nYear Built    \nThe year the building was built\nGross SqFt    \nGross square footage of the building\nEstimated Gross Income    \nEstimated Income per SquareFoot * Gross SquareFoot\nEstimated Expense\nEstimated Expense per SquareFoot * Gross SquareFoot\nNet Operating Income\nEstimated Gross Income-Estimated Expense\nFull Market Value\nCurrent years total market value of the land and building\nReport Year\nAcknowledgements\nAgency: Department of Finance (DOF)\nSource: NYC open data",
    "format": "arff",
    "uploader": "Elif Ceren Gok",
    "uploader_id": 30125,
    "visibility": "public",
    "creator": null,
    "contributor": null,
    "date": "2022-03-23 12:39:34",
    "update_comment": null,
    "last_update": "2022-03-23 12:39:34",
    "licence": "CC0: Public Domain",
    "status": "active",
    "error_message": null,
    "url": "https:\/\/www.openml.org\/data\/download\/22102186\/dataset",
    "default_target_attribute": null,
    "row_id_attribute": null,
    "ignore_attribute": null,
    "runs": 0,
    "suggest": {
        "input": [
            "Condominium-Comparable-Rental-Income-in-NYC",
            "If you think the dataset is useful please vote for it, it's an assignment from my data science class, I'll be appreciate! :)) Context The Department of Finance (DOF) is required by NY State law to value condominiums or cooperatives as if they were residential rental apartment buildings. DOF uses income information from rental properties similar in physical features and location to the condominiums or cooperatives. DOF applies this income data to the condominium or cooperative to determine its va "
        ],
        "weight": 5
    },
    "qualities": {
        "NumberOfInstances": 22073,
        "NumberOfFeatures": 12,
        "NumberOfClasses": null,
        "NumberOfMissingValues": 76,
        "NumberOfInstancesWithMissingValues": 76,
        "NumberOfNumericFeatures": 8,
        "NumberOfSymbolicFeatures": 0,
        "Dimensionality": 0.0005436506138721515,
        "PercentageOfNumericFeatures": 66.66666666666666,
        "MajorityClassPercentage": null,
        "PercentageOfSymbolicFeatures": 0,
        "MajorityClassSize": null,
        "MinorityClassPercentage": null,
        "MinorityClassSize": null,
        "NumberOfBinaryFeatures": 0,
        "PercentageOfBinaryFeatures": 0,
        "PercentageOfInstancesWithMissingValues": 0.34431205545236265,
        "AutoCorrelation": null,
        "PercentageOfMissingValues": 0.028692671287696883
    },
    "tags": [
        {
            "uploader": "38960",
            "tag": "Computer Systems"
        },
        {
            "uploader": "38960",
            "tag": "Machine Learning"
        }
    ],
    "features": [
        {
            "name": "Boro-Block-Lot",
            "index": "0",
            "type": "string",
            "distinct": "3748",
            "missing": "0"
        },
        {
            "name": "Address",
            "index": "1",
            "type": "string",
            "distinct": "4289",
            "missing": "0"
        },
        {
            "name": "Neighborhood",
            "index": "2",
            "type": "string",
            "distinct": "180",
            "missing": "0"
        },
        {
            "name": "Building_Classification",
            "index": "3",
            "type": "string",
            "distinct": "13",
            "missing": "0"
        },
        {
            "name": "Total_Units",
            "index": "4",
            "type": "numeric",
            "distinct": "426",
            "missing": "0",
            "min": "1",
            "max": "20363",
            "mean": "69",
            "stdev": "239"
        },
        {
            "name": "Year_Built",
            "index": "5",
            "type": "numeric",
            "distinct": "140",
            "missing": "73",
            "min": "0",
            "max": "2019",
            "mean": "1969",
            "stdev": "88"
        },
        {
            "name": "Gross_SqFt",
            "index": "6",
            "type": "numeric",
            "distinct": "4252",
            "missing": "0",
            "min": "1",
            "max": "3801490",
            "mean": "78418",
            "stdev": "147571"
        },
        {
            "name": "Estimated_Gross_Income",
            "index": "7",
            "type": "numeric",
            "distinct": "21793",
            "missing": "0",
            "min": "34",
            "max": "64093121",
            "mean": "2680227",
            "stdev": "4770694"
        },
        {
            "name": "Estimated_Expense",
            "index": "8",
            "type": "numeric",
            "distinct": "21589",
            "missing": "1",
            "min": "12",
            "max": "35125768",
            "mean": "882237",
            "stdev": "1595207"
        },
        {
            "name": "Net_Operating_Income",
            "index": "9",
            "type": "numeric",
            "distinct": "21735",
            "missing": "0",
            "min": "22",
            "max": "43003610",
            "mean": "1798030",
            "stdev": "3283737"
        },
        {
            "name": "Full_Market_Value",
            "index": "10",
            "type": "numeric",
            "distinct": "20032",
            "missing": "2",
            "min": "31",
            "max": "346132985",
            "mean": "13963090",
            "stdev": "25620785"
        },
        {
            "name": "Report_Year",
            "index": "11",
            "type": "numeric",
            "distinct": "8",
            "missing": "0",
            "min": "2012",
            "max": "2019",
            "mean": "2016",
            "stdev": "2"
        }
    ],
    "nr_of_issues": 0,
    "nr_of_downvotes": 0,
    "nr_of_likes": 0,
    "nr_of_downloads": 0,
    "total_downloads": 0,
    "reach": 0,
    "reuse": 0,
    "impact_of_reuse": 0,
    "reach_of_reuse": 0,
    "impact": 0
}