在 R 中，对于每个重复的 ID-时间组合，如何保留特定列中的最高值？

Question

在 R 中，对于每个重复的 ID-时间组合，如何保留特定列中的最高值？

Ann*_*nna 2 r economics dplyr data-cleaning

我有一个包含工资记录的 df 。对于每个重复的 PersonID-CalendarYear 组合，我想保留 WagesQ1:WagesQ4 列中的最高值。我还希望这些值都位于同一行。

例如，PersonID #49 有 3 行代表 2017 年。我想保留每个工资列中的最高值，这样我最终会得到 1 行代表 PersonID #49 和 2017 年。

我拥有的：

我想要的是：

到目前为止，我尝试了以下操作，但这会将每个 PersonID-CalendarYear 组合重复 4 次，这根本不是我想要的。

    test <- Emp %>% 
              group_by(PersonID, CalendarYear) %>%
              slice(which.max(WagesQ1), 
              which.max(WagesQ2), 
              which.max(WagesQ3), 
              which.max(WagesQ4))

Run Code Online (Sandbox Code Playgroud)

我在这里分享 df 的前 50 行：

structure(list(PersonID = c("30", "30", "30", "30", "30", "30", 
"30", "30", "30", "30", "30", "30", "30", "30", "30", "30", "30", 
"30", "30", "30", "30", "30", "36", "49", "49", "49", "49", "49", 
"49", "49", "49", "49", "49", "49", "49", "49", "49", "49", "49", 
"49", "49", "49", "49", "49", "49", "49", "49", "49", "49", "49"
), CalendarYear = c(2003L, 2004L, 2005L, 2006L, 2006L, 2007L, 
2008L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L, 2014L, 2015L, 
2016L, 2017L, 2017L, 2018L, 2019L, 2020L, 2021L, 2018L, 2003L, 
2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 
2012L, 2013L, 2014L, 2014L, 2015L, 2015L, 2015L, 2016L, 2016L, 
2016L, 2017L, 2017L, 2017L, 2018L, 2018L, 2019L, 2020L), County = c("181", 
"181", "181", "53", "175", "175", "53", "175", "53", "53", "53", 
"53", "53", "53", "53", "53", "53", "53", "53", "53", "53", "53", 
"9", "169", "169", "169", "169", "169", "169", "169", "169", 
"169", "169", "169", "169", "169", "169", "157", "169", "169", 
"157", "169", "169", "157", "169", "169", "169", "169", "169", 
"169"), industryID = c(844L, 844L, 844L, 418L, 829L, 829L, 418L, 
829L, 418L, 418L, 418L, 418L, 418L, 418L, 418L, 418L, 411L, 418L, 
411L, 411L, 411L, 411L, 10L, 410L, 1037L, 1037L, 1037L, 1037L, 
1037L, 1037L, 1037L, 1037L, 1037L, 1037L, 1037L, 892L, 1037L, 
892L, 892L, 1037L, 892L, 892L, 1037L, 892L, 892L, 1037L, 892L, 
1037L, 1037L, 1037L), OwnershipCode_Qtr1 = c("50", "50", "50", 
"50", NA, "50", NA, "50", "50", "50", "50", "50", "50", "50", 
"50", "50", NA, "50", "50", "50", "50", "50", NA, "50", NA, "30", 
"30", "30", "30", "30", "30", "30", "30", "30", "30", "50", "30", 
NA, "50", "30", NA, "50", "30", NA, "50", "30", "50", "30", "30", 
"30"), EmployeeQuarterlyHoursWorked_Qtr1 = c("560", "480", "520", 
"520", NA, "520", NA, "520", "480", "432", "480", "480", "417", 
"371", "404", "384", NA, "488", "479", "454", "476", "428", NA, 
"520", NA, "369", "386", "449", "457", "416", "448", "384", "389", 
"384", "388", "23", "386", NA, "1", "384", NA, "6", "384", NA, 
"6", "560", "60", "560", "560", "560"), EmployeeQuarterlyWages_Qtr1 = c("25974.00", 
"21961.00", "40279.00", "28924.00", "0", "47695.00", "0", "51586.00", 
"53059.00", "34615.00", "51267.00", "65367.00", "65935.00", "66764.00", 
"68044.00", "67817.00", "0", "68835.00", "70923.00", "67671.00", 
"80230.00", "54924.00", "0", "6977.00", "0", "6106.00", "7207.00", 
"8640.00", "8976.00", "8576.00", "9801.00", "8275.00", "8275.00", 
"8275.00", "8474.00", "376.00", "8677.00", "0", "750.00", "8883.00", 
"0", "500.00", "9356.00", "0", "441.00", "16433.00", "490.00", 
"17652.00", "18791.00", "20521.00"), EmployeeTenure_Qtr1 = c("3", 
"7", "11", "1", NA, "3", NA, "7", "4", "8", "12", "16", "20", 
"24", "28", "32", NA, "36", "2", "6", "10", "14", NA, "16", NA, 
"2", "6", "10", "14", "18", "22", "26", "30", "34", "38", "1", 
"42", NA, "1", "46", NA, "2", "50", NA, "2", "54", "2", "58", 
"62", "66"), EmployerLocationTotalWagesPaid_Qtr1 = c("2705239.00", 
"2655546.00", "3060808.00", "56494722.00", NA, "11577972.00", 
NA, "7905850.00", "67523518.00", "43414753.00", "59875257.00", 
"70830126.00", "77209774.00", "57210242.00", "72471506.00", "78008581.00", 
NA, "69864117.00", "12839820.00", "14455450.00", "16005038.00", 
"11267450.00", NA, "7107073.00", NA, "1900914.00", "2031601.00", 
"2495287.00", "2637867.00", "2678876.00", "2780822.00", "2219695.00", 
"2268540.00", "2120709.00", "2231025.00", "672803.00", "2234705.00", 
NA, "734496.00", "2228583.00", NA, "611993.00", "2408250.00", 
NA, "646954.00", "2993537.00", "622919.00", "3193565.00", "3395497.00", 
"3553823.00"), QuarterlyAverageEmployment_Qtr1 = c("97", "98", 
"105", "2385", NA, "362", NA, "240", "1952", "1760", "1715", 
"1710", "1617", "1640", "1606", "1595", NA, "1470", "389", "443", 
"461", "402", NA, "762", NA, "260", "251", "254", "265", "269", 
"259", "235", "241", "235", "233", "106", "227", NA, "97", "224", 
NA, "97", "221", NA, "94", "238", "92", "236", "239", "241"), 
    OwnershipCode_Qtr2 = c("50", "50", "50", "50", NA, "50", 
    "50", NA, "50", "50", "50", "50", "50", "50", "50", "50", 
    NA, "50", "50", "50", "50", NA, NA, "50", NA, "30", "30", 
    "30", "30", "30", "30", "30", "30", "30", "30", NA, "30", 
    "30", NA, "30", "30", "50", "30", "30", "50", "30", "50", 
    "30", "30", "30"), EmployeeQuarterlyHoursWorked_Qtr2 = c("480", 
    "520", "520", "520", NA, "520", "520", NA, "448", "464", 
    "464", "508", "536", "489", "495", "492", NA, "422", "423", 
    "424", "384", NA, NA, "520", NA, "448", "450", "386", "386", 
    "255", "387", "387", "385", "449", "451", NA, "456", "1", 
    NA, "455", "3", "2", "457", "6", "5", "480", "20", "480", 
    "480", "480"), EmployeeQuarterlyWages_Qtr2 = c("21911.00", 
    "22970.00", "29353.00", "28490.00", "0", "29964.00", "34491.00", 
    "0", "32600.00", "32250.00", "37819.00", "41553.00", "42701.00", 
    "44442.00", "49143.00", "46457.00", "0", "41058.00", "42066.00", 
    "41826.00", "34726.00", "0", "0", "7182.00", "0", "7934.00", 
    "8408.00", "7426.00", "7726.00", "5293.00", "8275.00", "8275.00", 
    "8275.00", "9830.00", "9896.00", "0", "10147.00", "80.00", 
    "0", "10423.00", "80.00", "166.00", "11007.00", "50.00", 
    "367.00", "14214.00", "163.00", "15188.00", "16168.00", "18067.00"
    ), EmployeeTenure_Qtr2 = c("4", "8", "12", "2", NA, "4", 
    "1", NA, "5", "9", "13", "17", "21", "25", "29", "33", NA, 
    "37", "3", "7", "11", NA, NA, "17", NA, "3", "7", "11", "15", 
    "19", "23", "27", "31", "35", "39", NA, "43", "1", NA, "47", 
    "1", "3", "51", "1", "3", "55", "3", "59", "63", "67"), EmployerLocationTotalWagesPaid_Qtr2 = c("2273677.00", 
    "2360550.00", "2501736.00", "46874830.00", NA, "8604560.00", 
    "42606565.00", NA, "36796585.00", "36680417.00", "44117859.00", 
    "46342635.00", "49910970.00", "59437204.00", "53698147.00", 
    "54838150.00", NA, "39797895.00", "10375288.00", "11095997.00", 
    "10321467.00", NA, NA, "6344850.00", NA, "2282968.00", "2439921.00", 
    "2159125.00", "2375421.00", "2373332.00", "2368912.00", "2203507.00", 
    "2184714.00", "2570868.00", "2605639.00", NA, "2692559.00", 
    "968147.00", NA, "2782204.00", "966568.00", "638154.00", 
    "2802058.00", "1024873.00", "683685.00", "2645041.00", "660148.00", 
    "2811118.00", "2986976.00", "3153488.00"), QuarterlyAverageEmployment_Qtr2 = c("98", 
    "100", "103", "2379", NA, "358", "1935", NA, "1776", "1682", 
    "1739", "1703", "1660", "1658", "1586", "1606", NA, "1459", 
    "414", "438", "450", NA, NA, "715", NA, "276", "258", "283", 
    "300", "305", "285", "264", "261", "273", "275", NA, "273", 
    "103", NA, "268", "104", "88", "269", "115", "85", "274", 
    "80", "278", "268", "208"), OwnershipCode_Qtr3 = c("50", 
    "50", "50", NA, "50", "50", "50", NA, "50", "50", "50", "50", 
    "50", "50", "50", "50", NA, "50", "50", "50", "50", NA, "50", 
    "50", NA, "30", "30", "30", "30", "30", "30", "30", "30", 
    "30", "30", NA, "30", NA, NA, "30", NA, NA, "30", NA, NA, 
    "30", NA, "30", "30", "30"), EmployeeQuarterlyHoursWorked_Qtr3 = c("520", 
    "520", "520", NA, "520", "520", "520", NA, "488", "544", 
    "560", "399", "426", "396", "443", "415", NA, "489", "489", 
    "524", "488", NA, "839", "520", NA, "384", "449", "446", 
    "451", "418", "452", "450", "449", "390", "389", NA, "384", 
    NA, NA, "384", NA, NA, "545", NA, NA, "560", NA, "560", "560", 
    "560"), EmployeeQuarterlyWages_Qtr3 = c("25563.00", "26941.00", 
    "29161.00", "0", "33522.00", "37714.00", "37519.00", "0", 
    "33862.00", "37625.00", "42420.00", "37400.00", "36718.00", 
    "38339.00", "39777.00", "43092.00", "0", "48008.00", "49174.00", 
    "48985.00", "45297.00", "0", "12678.00", "3644.00", "0", 
    "7065.00", "8494.00", "8737.00", "9013.00", "8619.00", "9654.00", 
    "9654.00", "9654.00", "8394.00", "8521.00", "0", "8697.00", 
    "0", "0", "8912.00", "0", "0", "14892.00", "0", "0", "17151.00", 
    "0", "18305.00", "19518.00", "21078.00"), EmployeeTenure_Qtr3 = c("5", 
    "9", "13", NA, "1", "5", "2", NA, "6", "10", "14", "18", 
    "22", "26", "30", "34", NA, "38", "4", "8", "12", NA, "1", 
    "18", NA, "4", "8", "12", "16", "20", "24", "28", "32", "36", 
    "40", NA, "44", NA, NA, "48", NA, NA, "52", NA, NA, "56", 
    NA, "60", "64", "68"), EmployerLocationTotalWagesPaid_Qtr3 = c("2561942.00", 
    "2836345.00", "2901631.00", NA, "6006025.00", "9244633.00", 
    "45594699.00", NA, "40660417.00", "42996310.00", "46205456.00", 
    "41682396.00", "41350115.00", "43793052.00", "42007503.00", 
    "54221071.00", NA, "44139475.00", "12277604.00", "12920820.00", 
    "12261562.00", NA, "841949.00", "5433154.00", NA, "2077482.00", 
    "2588350.00", "2625862.00", "2810502.00", "2888481.00", "2855988.00", 
    "2737480.00", "2717807.00", "2322919.00", "2346778.00", NA, 
    "2349394.00", NA, NA, "2424185.00", NA, NA, "3049769.00", 
    NA, NA, "3227870.00", NA, "3388103.00", "3536607.00", "3555916.00"
    ), QuarterlyAverageEmployment_Qtr3 = c("102", "110", "104", 
    NA, "292", "355", "1962", NA, "1814", "1730", "1742", "1703", 
    "1645", "1663", "1624", "1622", NA, "1461", "419", "443", 
    "433", NA, "96", "665", NA, "330", "335", "339", "354", "358", 
    "339", "356", "321", "334", "334", NA, "326", NA, NA, "322", 
    NA, NA, "336", NA, NA, "332", NA, "342", "340", "231"), OwnershipCode_Qtr4 = c("50", 
    "50", "50", NA, "50", "50", "50", NA, "50", "50", "50", "50", 
    "50", "50", "50", "50", "50", NA, "50", "50", "50", NA, "50", 
    "50", "30", "30", "30", "30", "30", "30", "30", "30", "30", 
    "30", "30", NA, "30", NA, "50", "30", NA, "50", "30", NA, 
    "50", "30", "50", "30", "30", "30"), EmployeeQuarterlyHoursWorked_Qtr4 = c("520", 
    "520", "520", NA, "520", "520", "520", NA, "520", "536", 
    "480", "499", "429", "490", "506", "426", "430", NA, "375", 
    "416", "500", NA, "772", "520", "293", "458", "395", "400", 
    "394", "387", "457", "450", "449", "460", "458", NA, "451", 
    NA, "4", "454", NA, "6", "480", NA, "30", "480", "0", "480", 
    "480", "560"), EmployeeQuarterlyWages_Qtr4 = c("25588.00", 
    "28944.00", "31548.00", "0", "35997.00", "35253.00", "37625.00", 
    "0", "43087.00", "38574.00", "34017.00", "61003.00", "43721.00", 
    "44729.00", "46407.00", "39777.00", "41149.00", "0", "42559.00", 
    "47402.00", "49078.00", "0", "5737.00", "1634.00", "4758.00", 
    "8287.00", "7280.00", "7499.00", "7726.00", "7956.00", "9654.00", 
    "10013.00", "10013.00", "10160.00", "10314.00", "0", "10524.00", 
    "0", "333.00", "10784.00", "0", "441.00", "13338.00", "0", 
    "245.00", "14782.00", "145.00", "15774.00", "16900.00", "21078.00"
    ), EmployeeTenure_Qtr4 = c("6", "10", "14", NA, "2", "6", 
    "3", NA, "7", "11", "15", "19", "23", "27", "31", "35", "1", 
    NA, "5", "9", "13", NA, "2", "19", "1", "5", "9", "13", "17", 
    "21", "25", "29", "33", "37", "41", NA, "45", NA, "1", "49", 
    NA, "1", "53", NA, "1", "57", "1", "61", "65", "69"), EmployerLocationTotalWagesPaid_Qtr4 = c("2592689.00", 
    "2786088.00", "2805669.00", NA, "5740894.00", "6721161.00", 
    "46794858.00", NA, "42277545.00", "47369971.00", "45689406.00", 
    "52769353.00", "51278020.00", "50198997.00", "53838385.00", 
    "43169822.00", "8467677.00", NA, "10719468.00", "11308861.00", 
    "12149650.00", NA, "316437.00", "6584282.00", "2353924.00", 
    "2497289.00", "2250699.00", "2328109.00", "2456573.00", "2497301.00", 
    "2844437.00", "2796565.00", "2739956.00", "2725955.00", "2746522.00", 
    NA, "2805607.00", NA, "621933.00", "2831090.00", NA, "628393.00", 
    "2498316.00", NA, "647813.00", "2589627.00", "656515.00", 
    "2813896.00", "2945372.00", "2961453.00"), QuarterlyAverageEmployment_Qtr4 = c("100", 
    "106", "100", NA, "279", "300", "1944", NA, "1767", "1738", 
    "1743", "1704", "1646", "1579", "1595", "1538", "354", NA, 
    "423", "446", "418", NA, "25", "659", "247", "255", "263", 
    "259", "276", "277", "254", "291", "257", "244", "250", NA, 
    "233", NA, "97", "238", NA, "92", "243", NA, "91", "239", 
    "91", "237", "245", "220"), CountyName = c("Statewide (i.e. no fixed location)", 
    "Statewide (i.e. no fixed location)", "Statewide (i.e. no fixed location)", 
    "Hennepin County", "City of Minneapolis", "City of Minneapolis", 
    "Hennepin County", "City of Minneapolis", "Hennepin County", 
    "Hennepin County", "Hennepin County", "Hennepin County", 
    "Hennepin County", "Hennepin County", "Hennepin County", 
    "Hennepin County", "Hennepin County", "Hennepin County", 
    "Hennepin County", "Hennepin County", "Hennepin County", 
    "Hennepin County", "Benton County", "Winona County", "Winona County", 
    "Winona County", "Winona County", "Winona County", "Winona County", 
    "Winona County", "Winona County", "Winona County", "Winona County", 
    "Winona County", "Winona County", "Winona County", "Winona County", 
    "Wabasha County", "Winona County", "Winona County", "Wabasha County", 
    "Winona County", "Winona County", "Wabasha County", "Winona County", 
    "Winona County", "Winona County", "Winona County", "Winona County", 
    "Winona County"), mncounty = c(NA, NA, NA, "27", NA, NA, 
    "27", NA, "27", "27", "27", "27", "27", "27", "27", "27", 
    "27", "27", "27", "27", "27", "27", "5", "85", "85", "85", 
    "85", "85", "85", "85", "85", "85", "85", "85", "85", "85", 
    "85", "79", "85", "85", "79", "85", "85", "79", "85", "85", 
    "85", "85", "85", "85"), IndustryGroup = c("Other Professional, Scientific, and Technical Services", 
    "Other Professional, Scientific, and Technical Services", 
    "Other Professional, Scientific, and Technical Services", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Scientific Research and Development Svc", "Scientific Research and Development Svc", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Scientific Research and Development Svc", "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Semiconductor and Other Electronic Component Manufacturing", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Semiconductor and Other Electronic Component Manufacturing", 
    "Semiconductor and Other Electronic Component Manufacturing", 
    "Semiconductor and Other Electronic Component Manufacturing", 
    "Semiconductor and Other Electronic Component Manufacturing", 
    "Vegetable and Melon Farming", "Semiconductor and Other Electronic Component Manufacturing", 
    "Executive, Legislative, and Other General Government Support ", 
    "Executive, Legislative, and Other General Government Support ", 
    "Executive, Legislative, and Other General Government Support ", 
    "Executive, Legislative, and Other General Government Support ", 
    "Executive, Legislative, and Other General Government Support ", 
    "Executive, Legislative, and Other General Government Support ", 
    "Executive, Legislative, and Other General Government Support ", 
    "Executive, Legislative, and Other General Government Support ", 
    "Executive, Legislative, and Other General Government Support ", 
    "Executive, Legislative, and Other General Government Support ", 
    "Executive, Legislative, and Other General Government Support ", 
    "Elementary and Secondary Schools", "Executive, Legislative, and Other General Government Support ", 
    "Elementary and Secondary Schools", "Elementary and Secondary Schools", 
    "Executive, Legislative, and Other General Government Support ", 
    "Elementary and Secondary Schools", "Elementary and Secondary Schools", 
    "Executive, Legislative, and Other General Government Support ", 
    "Elementary and Secondary Schools", "Elementary and Secondary Schools", 
    "Executive, Legislative, and Other General Government Support ", 
    "Elementary and Secondary Schools", "Executive, Legislative, and Other General Government Support ", 
    "Executive, Legislative, and Other General Government Support ", 
    "Executive, Legislative, and Other General Government Support "
    ), industry = c("All Other Professional, Scientific, and Technical Services", 
    "All Other Professional, Scientific, and Technical Services", 
    "All Other Professional, Scientific, and Technical Services", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Physical/Engineering/Biological Research", "Physical/Engineering/Biological Research", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Physical/Engineering/Biological Research", "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Semiconductor and Other Electronic Component Manufacturing", 
    "Navigational, Measuring, Electromedical, and Control Instruments Manufacturing", 
    "Semiconductor and Other Electronic Component Manufacturing", 
    "Semiconductor and Other Electronic Component Manufacturing", 
    "Semiconductor and Other Electronic Component Manufacturing", 
    "Semiconductor and Other Electronic Component Manufacturing", 
    "Vegetable and Melon Farming", "Semiconductor and Other Electronic Component Manufacturing", 
    "Executive Offices ", "Executive Offices ", "Executive Offices ", 
    "Executive Offices ", "Executive Offices ", "Executive Offices ", 
    "Executive Offices ", "Executive Offices ", "Executive Offices ", 
    "Executive Offices ", "Executive Offices ", "Elementary and Secondary Schools ", 
    "Executive Offices ", "Elementary and Secondary Schools ", 
    "Elementary and Secondary Schools ", "Executive Offices ", 
    "Elementary and Secondary Schools ", "Elementary and Secondary Schools ", 
    "Executive Offices ", "Elementary and Secondary Schools ", 
    "Elementary and Seco

Answer 1

lan*_*ang 5

您可以reframe()在此处使用across()：

\n

reframe(\n  ungroup(df),\n  across(contains("QuarterlyWages"), ~max(as.numeric(.x))),\n  .by=PersonID:CalendarYear\n)\n

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输出：

\n

# A tibble: 38 \xc3\x97 6\n   PersonID CalendarYear EmployeeQuarterlyWages_Qtr1 EmployeeQuarterlyWages_Qtr2 EmployeeQuarterlyWages_\xe2\x80\xa6\xc2\xb9\n   <chr>           <int>                       <dbl>                       <dbl>                     <dbl>\n 1 30               2003                       25974                       21911                     25563\n 2 30               2004                       21961                       22970                     26941\n 3 30               2005                       40279                       29353                     29161\n 4 30               2006                       28924                       28490                     33522\n 5 30               2007                       47695                       29964                     37714\n 6 30               2008                       51586                       34491                     37519\n 7 30               2009                       53059                       32600                     33862\n 8 30               2010                       34615                       32250                     37625\n 9 30               2011                       51267                       37819                     42420\n10 30               2012                       65367                       41553                     37400\n# \xe2\x84\xb9 28 more rows\n# \xe2\x84\xb9 abbreviated name: \xc2\xb9\xe2\x80\x8bEmployeeQuarterlyWages_Qtr3\n# \xe2\x84\xb9 1 more variable: EmployeeQuarterlyWages_Qtr4 <dbl>\n# \xe2\x84\xb9 Use `print(n = ...)` to see more rows\n

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