How to load combined data in R - r
I get 60 Excel files that look like this (the original file has 135 rows):
structure(list(Ce = c(NA, NA, NA, "AC12-PRD-C1", "Camarda", "45431",
"171,0 cm", "754 mmHg", "20W-25W", "RÈsumÈ", NA, "Moyennag",
"Time", "Load", "V'O2", "VO2/kg", "dO2/dW", "V'CO2", "MET", "RER",
"V'E", "BF", "VTex", "PETO2", "PETCO2", "EqCO2", "EqO2", "HR",
"HRR %", "SpO2", "O2/HR", "Ce", NA, NA, NA, "AC12-PRD", NA, "t-ph",
"min", NA, "9.7222222222222224E-3", "1.9444444444444445E-2",
"2.9166666666666664E-2", "3.888888888888889E-2", "4.9999999999999996E-2",
"6.1111111111111116E-2", "7.2222222222222229E-2", "8.2638888888888887E-2",
"9.1666666666666674E-2", "0.10208333333333335", "0.1111111111111111",
"0.12430555555555556", "9.7222222222222224E-3", "2.013888888888889E-2",
"3.0555555555555555E-2", "4.0972222222222222E-2", "5.0694444444444452E-2",
"6.1805555555555558E-2", "7.1527777777777787E-2", "8.3333333333333329E-2",
"9.2361111111111116E-2", "0.10347222222222223", "0.11319444444444444",
"0.12361111111111112", NA, "t-ph", "min", NA, "9.7222222222222224E-3",
"2.013888888888889E-2", "3.0555555555555555E-2", "4.0972222222222222E-2",
"5.0694444444444452E-2", "6.1805555555555558E-2", "7.1527777777777787E-2",
"8.3333333333333329E-2", "9.2361111111111116E-2", "0.10347222222222223",
"0.11319444444444444", "0.12361111111111112", NA, "t-ph", "min",
NA, "1.0416666666666666E-2"), `ntre …` = c("5055", NA, NA, "linear",
NA, "54", NA, NA, "+ 15W", NA, NA, "e temp", NA, NA, NA, "ml",
"ml/m", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
"ntre …", "5055", NA, NA, "-C", NA, "Load", "W", NA, "0", "0",
"0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "20", "20",
"20", "20", "20", "20", "20", "20", "20", "20", "20", "20", NA,
"Load", "W", NA, "20", "20", "20", "20", "20", "20", "20", "20",
"20", "20", "20", "20", NA, "Load", "W", NA, "25"), `PIC, Insti` = c("rue St Zot",
"tÈl.", "fax.", NA, NA, "masc", "84", "01/0", NA, NA, NA, "orel 15 Se",
"min", "W", "ml/min", "/min/kg", "in/Watt", "ml/min", NA, NA,
"L/min", "1/min", "L", "mmHg", "mmHg", NA, NA, "1/min", "%",
"%", "ml", "PIC, Insti", "rue St Zot", "tÈl.", "fax.", NA, NA,
"HR", "1/min", NA, "73", "71", "74", "72", "81", "77", "78",
"77", "78", "76", "76", "80", "86", "82", "85", "84", "85", "86",
"86", "86", "90", "89", "90", "91", NA, "HR", "1/min", NA, "86",
"82", "85", "84", "85", "86", "86", "86", "90", "89", "90", "91",
NA, "HR", "1/min", NA, "92"), `tut de` = c("ique E", "-514",
"-514", NA, "Ant", "ulin", "kg", "9/2016", NA, "ThÈo", NA, "con",
NA, "163", "2041", NA, NA, NA, NA, NA, "71", "29", NA, NA, NA,
NA, NA, "170", NA, NA, "12.1", "tut de", "ique E", "-514", "-514",
NA, "Rep", "BF", "1/min", NA, "24", "22", "22", "22", "22", "19",
"19", "19", "19", "20", "19", "18", "25", "24", "24", "24", "22",
"23", "21", "21", "22", "19", "23", "24", "RÈfÈr", "BF", "1/min",
NA, "25", "24", "24", "24", "22", "23", "21", "21", "22", "19",
"23", "24", "Exer", "BF", "1/min", NA, "23"), Cardiolo = c("st, Montr",
"3741480", "3742416", NA, "oine", NA, NA, NA, NA, "Repos", NA,
NA, "0.12430555555555556", "0", "380", "4.5", "0.00", "347",
"1.3", "0.91", "14", "18", "0.777", "111.75", "34.10", "37.4",
"34.1", "80", "53", "-4", "4.8", "Cardiolo", "st, Montr", "3741480",
"3742416", NA, "os", "V'E", "L/min", NA, "12", "13", "14", "12",
"9", "12", "12", "12", "13", "14", "13", "14", "15", "17", "18",
"18", "18", "18", "20", "19", "22", "22", "21", "22", "ence",
"V'E", "L/min", NA, "15", "17", "18", "18", "18", "18", "20",
"19", "22", "22", "21", "22", "cice", "V'E", "L/min", NA, "23"
), `gie de M` = c("Èal, HT1", NA, NA, NA, NA, "62 AnnÈ", "Dr Math",
"0.62850694444444444", NA, "AT", "Manuel", NA, "0.33333333333333331",
"40", "823", "9.8", "11.08", "704", "2.8", "0.86", "23", "23",
"0.996", "101.82", "40.90", "30.1", "25.7", "94", "45", "-4",
"8.8", "gie de M", "Èal, HT1", NA, NA, NA, NA, "V'O2", "ml/min",
NA, "365", "389", "417", "310", "281", "364", "354", "382", "401",
"405", "349", "380", "461", "516", "566", "594", "626", "641",
"720", "664", "789", "724", "746", "762", NA, "V'O2", "ml/min",
NA, "461", "516", "566", "594", "626", "641", "720", "664", "789",
"724", "746", "762", NA, "V'O2", "ml/min", NA, "777"), ontrÈal = c("1N6",
NA, NA, NA, NA, "es", "ieu Gayda", "8", NA, "MaxVO2", NA, NA,
"0.54166666666666663", "115", "1703", "20.3", "11.50", "2034",
"5.8", "1.19", "62", "27", "2.316", "112.88", "40.62", "29.5",
"35.2", "139", "18", "-4", "12.2", "ontrÈal", "1N6", NA, NA,
NA, NA, "V'CO2 d", "ml/min", "m", "283", "309", "344", "264",
"210", "296", "283", "304", "325", "339", "299", "347", "370",
"427", "464", "491", "506", "512", "591", "559", "655", "658",
"640", "657", NA, "V'CO2 d", "ml/min", "m", "370", "427", "464",
"491", "506", "512", "591", "559", "655", "658", "640", "657",
NA, "V'CO2 d", "ml/min", "m", "677"), ...8 = c(NA, NA, NA, NA,
NA, NA, NA, "VÈlo", NA, "MaxVO2", "%thÈo.", NA, NA, "71", "83",
NA, NA, NA, NA, NA, "87", "93", NA, NA, NA, NA, NA, "82", NA,
NA, "101", NA, NA, NA, NA, NA, NA, "O2/dW", "ml/", "in/Watt",
"0.00", "0.00", "0.00", "0.00", "0.00", "0.00", "0.00", "0.00",
"0.00", "0.00", "0.00", "0.00", "4.03", "6.76", "9.30", "10.70",
"12.27", "13.04", "16.97", "14.20", "20.42", "17.16", "18.29",
"19.06", NA, "O2/dW", "ml/", "in/Watt", "4.03", "6.76", "9.30",
"10.70", "12.27", "13.04", "16.97", "14.20", "20.42", "17.16",
"18.29", "19.06", NA, "O2/dW", "ml/", "in/Watt", "19.81"), ...9 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "1", NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, "RER", NA, NA, "0.78", "0.80", "0.83", "0.85",
"0.75", "0.82", "0.80", "0.79", "0.81", "0.84", "0.86", "0.91",
"0.80", "0.83", "0.82", "0.83", "0.81", "0.80", "0.82", "0.84",
"0.83", "0.91", "0.86", "0.86", NA, "RER", NA, NA, "0.80", "0.83",
"0.82", "0.83", "0.81", "0.80", "0.82", "0.84", "0.83", "0.91",
"0.86", "0.86", NA, "RER", NA, NA, "0.87"), ...10 = c(NA, NA,
NA, NA, NA, NA, NA, NA, NA, "Max", "Watts", NA, "0.55208333333333337",
"130", "1583", "18.9", "9.25", "1952", "5.4", "1.23", "64", "30",
"2.114", "14.84", "39.35", "31.5", "38.8", "142", "16", "-4",
"11.2", NA, NA, NA, NA, NA, NA, "EqO2", NA, NA, "27.6", "29.3",
"30.8", "33.9", "25.3", "30.3", "28.9", "29.1", "29.2", "30.5",
"32.9", "34.1", "29.4", "28.8", "28.0", "27.0", "26.3", "25.9",
"25.7", "26.3", "25.3", "28.6", "26.4", "27.3", NA, "EqO2", NA,
NA, "29.4", "28.8", "28.0", "27.0", "26.3", "25.9", "25.7", "26.3",
"25.3", "28.6", "26.4", "27.3", NA, "EqO2", NA, NA, "27.4"),
...11 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "EqCO2", NA, NA,
"35.7", "36.8", "37.3", "39.9", "33.8", "37.2", "36.2", "36.6",
"36.0", "36.5", "38.4", "37.4", "36.6", "34.9", "34.2", "32.7",
"32.5", "32.5", "31.4", "31.2", "30.5", "31.4", "30.8", "31.7",
NA, "EqCO2", NA, NA, "36.6", "34.9", "34.2", "32.7", "32.5",
"32.5", "31.4", "31.2", "30.5", "31.4", "30.8", "31.7", NA,
"EqCO2", NA, NA, "31.5"), ...12 = c(NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "PETCO2", "mmHg", NA, "35.68", "32.78", "35.26", "33.61",
"36.27", "35.53", "35.87", "36.38", "36.51", "36.36", "35.92",
"34.10", "36.80", "36.34", "37.09", "32.65", "38.35", "38.99",
"39.26", "39.91", "39.95", "39.22", "40.18", "39.63", NA,
"PETCO2", "mmHg", NA, "36.80", "36.34", "37.09", "32.65",
"38.35", "38.99", "39.26", "39.91", "39.95", "39.22", "40.18",
"39.63", NA, "PETCO2", "mmHg", NA, "39.66"), ...13 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "VES (ml)", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "86"), ...14 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "VESi (ml/m²)", NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "42.6"), ...15 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "FC (bpm)", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "90"), ...16 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "QC (l/min)", NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "7.8"), ...17 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "IC (l/min/m²)", NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "3.9"), ...18 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "PAS (mmHg)", NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "120"), ...19 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "PAD (mmHg)", NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "74"), ...20 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "PAM (mmHg)", NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "94"), ...21 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "ICT", NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, "153"), ...22 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "TEV (ms)", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "415.6"), ...23 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "RPD (%)", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "49.3"), ...24 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "WCI (kg.m/m²)", NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "4.7"), ...25 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "RVSi (dyn.s/cm5.m²)", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "1819"
), ...26 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "RVS (dyn.s/cm5)",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "901"), ...27 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "VTD est (ml)",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "137.5"), ...28 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "FE est (%)",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "62.7"), ...29 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "O2Hb",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "3.8E-3"), ...30 = c(NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "HHb",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "-0.29199999999999998"), ...31 = c(NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "tHb", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, "-0.28820000000000001"), ...32 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "HbDiff", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "0.29580000000000001"
)), row.names = c(NA, -85L), class = c("tbl_df", "tbl", "data.frame"
))
I want to get rid of rows and columns to make my files all looking like this:
structure(list(time = c("00:15", "00:30", "00:46", "01:00", "01:15",
"01:31", "01:46", "01:59", "02:14", "02:30", "02:44", "02:59",
"03:16", "03:29", "03:46", "03:57", "04:14", "04:31", "04:44",
"05:00", "05:16", "05:30", "05:46", "06:01", "06:15", "06:31",
"06:44", "07:00", "07:16", "00:01"), power = c(25, 25, 25, 25,
40, 40, 40, 40, 55, 55, 55, 55, 70, 70, 70, 70, 85, 85, 85, 85,
100, 100, 100, 100, 115, 115, 115, 115, 130, 130), hr = c(92,
90, 86, 87, 93, 91, 95, 94, 98, 100, 101, 100, 108, 108, 110,
113, 115, 118, 120, 122, 122, 126, 130, 130, 131, 136, 137, 139,
142, 144), fr = c(23, 22, 21, 25, 25, 22, 22, 23, 24, 23, 23,
21, 22, 24, 24, 22, 23, 23, 22, 23, 25, 26, 27, 26, 30, 27, 27,
28, 30, 31), VE = c(23, 23, 25, 20, 23, 25, 24, 23, 25, 26, 28,
28, 32, 33, 32, 33, 37, 42, 38, 41, 47, 48, 48, 50, 52, 56, 55,
60, 65, 64), absVO2 = c(0.777, 0.744, 0.761, 0.674, 0.808, 0.868,
0.787, 0.816, 0.921, 0.935, 0.989, 0.96, 1.05, 0.994, 1.121,
1.136, 1.227, 1.193, 1.164, 1.212, 1.333, 1.289, 1.358, 1.403,
1.463, 1.494, 1.441, 1.593, 1.585, 1.515), VCO2 = c(0.677, 0.68,
0.728, 0.583, 0.689, 0.766, 0.714, 0.691, 0.784, 0.825, 0.9,
0.907, 1.008, 0.982, 1.066, 1.132, 1.204, 1.269, 1.241, 1.291,
1.463, 1.488, 1.527, 1.596, 1.633, 1.756, 1.74, 1.912, 1.972,
1.93), PETCO2 = c(39.66, 39.08, 38.76, 39.67, 39, 39.4, 38.71,
41.37, 41.02, 41.19, 41.54, 41.89, 41.12, 41.16, 42.98, 42.8,
42.53, 40.75, 42.64, 41.45, 40.82, 40.23, 41.46, 41.87, 41.37,
40.54, 40.36, 40.64, 39.3, 38.91), VES = c(86, 92.4, 91.4, 84.8,
86, 88.1, 88.9, 86.5, 90.8, 93.2, 94.7, 94.8, 92.6, 93.7, 95.9,
93.1, 101.4, 101.1, 89.4, 97.6, 105.1, 100.3, 97.5, 100.7, 99.8,
108, 105.6, 104.5, 108.3, 106.5), QC = c(7.8, 8.5, 8.3, 7.5,
7.7, 8.1, 8.2, 8.2, 8.6, 9.1, 9.5, 9.5, 9.4, 10, 10.4, 10.3,
11.3, 11.5, 10.5, 11.6, 12.7, 12.3, 12.3, 12.9, 13, 14.2, 14.2,
14.4, 15.1, 15.2), IC = c(3.9, 4.2, 4.1, 3.7, 3.8, 4, 4.1, 4,
4.3, 4.5, 4.7, 4.7, 4.6, 4.9, 5.1, 5.1, 5.6, 5.7, 5.2, 5.8, 6.3,
6.1, 6.1, 6.4, 6.4, 7, 7, 7.1, 7.5, 7.5), WCI = c(4.7, 5.1, 5,
4.5, 4.6, 4.9, 4.9, 4.9, 5.2, 5.5, 5.7, 5.7, 5.6, 6, 6.2, 6.2,
6.8, 6.9, 6.3, 7, 7.6, 7.4, 7.4, 7.7, 7.8, 8.5, 8.5, 8.7, 9.1,
9.1), RVSi = c(1819, 1657, 1709, 1890, 1832, 1745, 1729, 1732,
1641, 1555, 1486, 1480, 1505, 1423, 1358, 1371, 1256, 1224, 1347,
1216, 1112, 1151, 1152, 1096, 1092, 993, 993, 978, 930, 928),
RVS = c(901, 821, 846, 936, 907, 865, 857, 858, 813, 770,
736, 733, 745, 705, 673, 679, 622, 606, 667, 603, 551, 570,
571, 543, 541, 492, 492, 484, 461, 460), VTD = c(137.5, 146.4,
149.6, 138.6, 146.4, 137.2, 142.2, 140.7, 148.5, 146.9, 153.6,
152.3, 144.2, 144, 147.5, 147.3, 146.3, 155.9, 142.4, 151.3,
152.8, 151.4, 154.3, 158.4, 159.5, 157.2, 159.8, 155.4, 150.9,
152.8), FE = c(62.7, 63.1, 61.1, 61.3, 58.8, 64.2, 62.4,
61.5, 61.1, 63.4, 61.6, 62.3, 64.2, 65.1, 65, 63.2, 69.3,
64.8, 62.7, 64.5, 68.8, 66.3, 63.2, 63.6, 62.8, 68.7, 66.2,
67.3, 71.8, 69.7), O2Hb = c("3.8E-3", "0.37130000000000002",
"0.10929999999999999", "0.1457", "0.24440000000000001", "0.39960000000000001",
"0.51039999999999996", "0.28970000000000001", "0.1762", "0.78080000000000005",
"1.0116000000000001", "1.2717000000000001", "1.4643999999999999",
"2.5387", "2.3233000000000001", "2.5627", "2.5230000000000001",
"2.7890000000000001", "2.8567", "3.5232999999999999", "3.7351999999999999",
"4.2393000000000001", "4.3661000000000003", "4.3578000000000001",
"4.2431000000000001", "4.6954000000000002", "4.5110000000000001",
"5.1020000000000003", "4.9044999999999996", "4.8182999999999998"
), HHb = c(-0.292, -0.3309, -0.2811, -0.1445, -0.1007, -0.2498,
-0.4758, -0.2753, -0.0079, -0.2002, -0.4731, -0.3644, -0.5278,
-0.7466, -0.8117, -0.8199, -1.0041, -1.1128, -0.9041, -0.9066,
-1.0106, -0.9902, -0.9717, -0.9746, -1.0317, -1.0096, -0.9691,
-1.0462, -0.8992, -0.8552), tHb = c("-0.28820000000000001",
"4.0399999999999998E-2", "-0.17180000000000001", "1.1999999999999999E-3",
"0.14369999999999999", "0.14979999999999999", "3.4599999999999999E-2",
"1.44E-2", "0.16830000000000001", "0.58050000000000002",
"0.53849999999999998", "0.9073", "0.93659999999999999", "1.7921",
"1.5116000000000001", "1.7427999999999999", "1.5188999999999999",
"1.6761999999999999", "1.9525999999999999", "2.6166999999999998",
"2.7246000000000001", "3.2490000000000001", "3.3944000000000001",
"3.3832", "3.2113999999999998", "3.6859000000000002", "3.5419",
"4.0556999999999999", "4.0053000000000001", "3.9630999999999998"
), HbDiff = c("0.29580000000000001", "0.70209999999999995",
"0.39050000000000001", "0.29020000000000001", "0.34510000000000002",
"0.64939999999999998", "0.98619999999999997", "0.56499999999999995",
"0.18410000000000001", "0.98099999999999998", "1.4846999999999999",
"1.6361000000000001", "1.9922", "3.2852999999999999", "3.1349999999999998",
"3.3826000000000001", "3.5270999999999999", "3.9018000000000002",
"3.7608000000000001", "4.4298999999999999", "4.7458", "5.2294999999999998",
"5.3377999999999997", "5.3323999999999998", "5.2747999999999999",
"5.7050000000000001", "5.4802", "6.1482000000000001", "5.8037000000000001",
"5.6734999999999998"), id = c("AC12-PRD-C1", "AC12-PRD-C1",
"AC12-PRD-C1", "AC12-PRD-C1", "AC12-PRD-C1", "AC12-PRD-C1",
"AC12-PRD-C1", "AC12-PRD-C1", "AC12-PRD-C1", "AC12-PRD-C1",
"AC12-PRD-C1", "AC12-PRD-C1", "AC12-PRD-C1", "AC12-PRD-C1",
"AC12-PRD-C1", "AC12-PRD-C1", "AC12-PRD-C1", "AC12-PRD-C1",
"AC12-PRD-C1", "AC12-PRD-C1", "AC12-PRD-C1", "AC12-PRD-C1",
"AC12-PRD-C1", "AC12-PRD-C1", "AC12-PRD-C1", "AC12-PRD-C1",
"AC12-PRD-C1", "AC12-PRD-C1", "AC12-PRD-C1", "AC12-PRD-C1"
), body_mass = c("84", "84", "84", "84", "84", "84", "84",
"84", "84", "84", "84", "84", "84", "84", "84", "84", "84",
"84", "84", "84", "84", "84", "84", "84", "84", "84", "84",
"84", "84", "84"), training = c("linear", "linear", "linear",
"linear", "linear", "linear", "linear", "linear", "linear",
"linear", "linear", "linear", "linear", "linear", "linear",
"linear", "linear", "linear", "linear", "linear", "linear",
"linear", "linear", "linear", "linear", "linear", "linear",
"linear", "linear", "linear")), row.names = c(NA, -30L), class = c("tbl_df",
"tbl", "data.frame"))
To do so, I used this code to combine my data and select the rows and columns I want:
load_files <- function(files){
temp <- read_excel(files) %>%
select(-(c(8:11, 14:15, 18:23))) %>%
mutate(id = pull(.[4,1])) %>% ##ID
mutate(body_mass = pull(.[7,3])) %>% ##body mass
mutate(training = pull(.[4,2])) %>% ##training group
set_names(c("time", "power", "hr", "fr", "VE", "absVO2", "VCO2", "PETCO2", "VES", "QC", "IC", "WCI", "RVSi", "RVS", "VTD", "FE", "O2Hb", "HHb", "tHb", "HbDiff", "id", "body_mass", "training")) %>%
slice(86:which(grepl("ration", VE))-1) %>% ##until recovery period
mutate_at(vars(1:16), as.numeric) %>%
mutate_at(vars(18), as.numeric) %>%
mutate(time = format(as.POSIXct(Sys.Date() + time), "%H:%M", tz="UTC"),
absVO2 = absVO2/1000,
VCO2 = VCO2/1000)
}
df <- map_df(file_list, load_files)
But I get this output:
Error in `set_names()`:
! The size of `nm` (23) must be compatible with the size of `x` (25).
Run `rlang::last_error()` to see where the error occurred.
It was working before, but this I have added column in the Excel files, it does work anymore.
Thank you for your support!
Related
Remove all rows before row meeting condition in R
I am importing multiple excel files. The files have a non-standard structure, but all have the required data after a row of headers, midway down the rows of the data frame.
Here is a MWE:
df= structure(list(...1 = c("CPET Results", NA, "Operator", NA, NA,
"Patient data", NA, "Administrative Data", "ID", "Title", "Last Name",
"First Name", "Name Addition", "Sex", "Date of Birth", NA, NA,
"Biological and Medical Baseline Data", "Height", "Weight", "Mask",
"Race", "Body Fat", "Hip/Waist Ratio", "BMI", "Estimated Fitness Level",
"BSA", "Hct", "Hb", "Medication that changes the Heart Rate",
"Medication", "Existing Medical Conditions", NA, NA, NA, "Test data",
"Start Time", "Duration", "CPET device", "Serial number", "Firmware version",
"Flow Sensor", "Temperature", "Barometric Pressure", "Humidity",
NA, NA, NA, "Variable", "V'O2", "V'CO2", "V'O2/kg", "V'O2/HR",
"HR", "V'E/V'O2", "V'E/V'CO2", "V'E", "BF", "RER", "WR", NA,
NA, "t", "h:mm:ss.ms", "0:00:25.000", "0:00:26.000", "0:00:27.000",
"0:00:28.000", "0:00:29.000", "0:00:30.000"), ...2 = c(NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Unit",
"L/min", "L/min", "ml/min/kg", "ml", "/min", NA, NA, "L/min",
"/min", NA, "W", NA, NA, "Phase", NA, "Rest", "Rest", "Rest",
"Rest", "Rest", "Rest"), ...3 = c(NA, NA, NA, NA, NA, NA, NA,
NA, "343", NA, "GFRex", "343", NA, "female", "21/05/1924", NA,
NA, NA, "178 cm", "88.2 kg", "Blue, medium", NA, NA, "0.96",
"28", NA, "2.06 m2", NA, NA, NA, NA, NA, NA, NA, NA, NA, "12/04/2021 11:27 AM",
"0:15:12", "MetaLyzer 3B-R3", "231821624", "1.3.10", NA, "21.5°C",
"1030mBar", "36%", NA, NA, NA, "Rest", "0.36", "0.31", "4", "0",
"-", "35.7", "40.0", "14.9", "14", "0.88", "0", NA, NA, "Marker",
NA, NA, NA, NA, NA, NA, NA), ...4 = c(NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "Unloaded Pedalling",
"-", "-", "-", "-", "-", "-", "-", "-", "-", "-", "-", NA, NA,
"V'O2", "L/min", "0.61123179277253403", "0.61123179277253403",
"0.61123179277253403", "0.61123179277253403", "0.51731964113453299",
"0.51731964113453299"), ...5 = c(NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, "Warm Up", "0.61", "0.47",
"7", "0", "-", "26.2", "33.9", "18.5", "16", "0.77", "0", NA,
NA, "V'O2/kg", "ml/min/kg", "6.9339965147196203", "6.9339965147196203",
"6.9339965147196203", "6.9339965147196203", "5.8686289408341796",
"5.8686289408341796"), ...6 = c(NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, "VT1", "1.22", "0.98", "14",
"-", "-", "28.6", "32.3", "35.4", "22", "0.88", "71", NA, NA,
"V'O2/HR", "ml", "0", "0", "0", "0", "0", "0"), ...7 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "VT1 % Norm",
"145", "-", "145", "-", "-", "-", "-", "-", "102", "-", "131",
NA, NA, "HR", "/min", NA, NA, NA, NA, NA, NA), ...8 = c(NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "VT1 % Max",
"69", "55", "69", "-", "-", "83", "96", "54", "76", "87", "55",
NA, NA, "WR", "W", "0", "0", "0", "0", "0", "0"), ...9 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "VT2",
"1.71", "1.66", "19", "-", "-", "31.9", "32.7", "60.0", "32",
"0.97", "122", NA, NA, "V'E/V'O2", NA, "30.6521809263484", "30.6521809263484",
"30.6521809263484", "30.6521809263484", "34.760039405568897",
"34.760039405568897"), ...10 = c(NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, "VT2 % Norm", "203", "-",
"203", "-", "-", "-", "-", "-", "147", "-", "226", NA, NA, "V'E/V'CO2",
NA, "35.697970640705897", "35.697970640705897", "35.697970640705897",
"35.697970640705897", "39.618822090063901", "39.618822090063901"
), ...11 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, "VT2 % Max", "97", "93", "97", "-", "-", "93",
"97", "92", "110", "96", "96", NA, NA, "RER", NA, "0.858653317715381",
"0.858653317715381", "0.858653317715381", "0.858653317715381",
"0.87736175817015105", "0.87736175817015105"), ...12 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "V'O2peak",
"1.77", "1.79", "20", "0", "-", "34.3", "33.8", "65.4", "29",
"1.01", "128", NA, NA, "V'E", "L/min", "23.334937499999999",
"23.334937499999999", "23.334937499999999", "23.334937499999999",
"21.762284444444401", "21.762284444444401"), ...13 = c(NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "V'O2peak % Norm",
"210", "-", "210", "0", "-", "-", "-", "-", "135", "-", "237",
NA, NA, "VT", "L", "0.86250000000000004", "0.86250000000000004",
"0.86250000000000004", "0.86250000000000004", "0.97866666666666702",
"0.97866666666666702"), ...14 = c(NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, "Normal", "0.84", "-", "10",
"8", "104", "-", "-", "-", "22", "-", "54", NA, NA, "BF", "/min",
"27.055", "27.055", "27.055", "27.055", "22.2366666666667", "22.2366666666667"
), ...15 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, "Absolute Maximum Values", "2.06", "1.96", "23",
"0", "-", "44.5", "37.2", "73.5", "34", "1.19", "128", NA, NA,
"V'CO2", "L/min", "0.52483620675725695", "0.52483620675725695",
"0.52483620675725695", "0.52483620675725695", "0.45387646988174501",
"0.45387646988174501"), ...16 = c(NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, "WR", "W", "0", "0", "0", "0", "0",
"0")), row.names = c(NA, -70L), class = c("tbl_df", "tbl", "data.frame"
))
I want to remove all rows before ...1 == "t". I'm importing multiple files and want to do this to all of them at the sametime, and the header "t" appears at a different row number in each file.
I have tried
df1 = df[-c(1:row_number(df$...1 =="t")),]
df1 = df[-c(rownames(df[df$...1 =="t",])),]
I'd like a base R or dplyr solution. Thanks
In dplyr, the slice function can be used to select rows by index, and the base-R which() can tell you which row index to start at. df %>% slice(min(which(...1 == 't')):n()) This code will check for any rows on which ...1 == 't', then which() tells you the row index. min() is in case you get a file with two rows of 't'. Then, the slice picks all rows from that row you just found to the end (n()).
in base R you could do: df[-seq(which(df[, '...1'] == 't') - 1),]
How to plot an igraph object on a vector map in R
I use the igraph and sf packages.
I have an igraph object whose vertices have spatial coordinates geo_dist_graph.
The vertices names and coordinates look like this:
grid_grid <-
structure(list(coords.x1 = c(15.504078, 15.704078, 15.904078,
15.104078, 15.304078, 15.504078, 15.704078, 15.104078, 15.304078,
15.704078, 14.904078, 14.304078, 13.904078, 14.704078, 13.704078,
14.104078, 14.704078, 14.904078, 13.704078, 13.904078, 14.704078,
13.704078, 13.904078, 14.304078),
coords.x2 = c(43.835623, 43.835623,
43.835623, 44.035623, 44.035623, 44.035623, 44.035623, 44.235623,
44.235623, 44.235623, 44.435623, 44.635623, 44.835623, 44.835623,
45.035623, 45.035623, 45.035623, 45.035623, 45.235623, 45.235623,
45.235623, 45.435623, 45.435623, 45.435623),
g9.nodes = c(27,
28, 29, 40, 41, 42, 43, 55, 56, 58, 69, 81, 94, 98, 108, 110,
113, 114, 123, 124, 128, 138, 139, 141)),
class = "data.frame", row.names = c("1",
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13",
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24"
))
The graph is from a simple squared adjacency matrix:
geo_dist_graph <-
structure(c(NA, 1, 1, NA, NA, 1, 1, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, 1, NA, NA, NA,
1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 1, 1, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA,
NA, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, 1, NA, 1, NA, NA, 1, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, 1, NA,
1, NA, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 1, 1, 1, NA, NA, 1, NA, NA, NA, 1, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA,
NA, 1, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 1, 1, 1, NA, 1, NA, 1, 1, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, 1, NA,
1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, 1, 1, NA, NA, NA, NA, 1, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 1, 1, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, 1, 1,
NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 1, 1, NA, NA, NA, NA, 1, 1, NA, NA, 1, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, 1, NA,
NA, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 1, 1, NA, 1, NA, NA, NA, NA, 1, NA, NA, NA, 1, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, 1,
NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, 1, NA, NA, 1, NA, NA, NA, 1, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA,
NA, 1, NA, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 1, NA, 1, 1, NA, NA, 1, NA, NA, 1, 1, 1, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, 1, 1, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, 1, 1, NA, NA, 1, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1,
1, NA, 1, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 1, NA, NA, NA, 1, NA, NA, 1, NA),
.Dim = c(24L,
24L))
colnames(geo_dist_graph) <- grid_grid$g9.nodes
row.names(geo_dist_graph) <- grid_grid$g9.nodes
geo_dist_graph <- graph_from_adjacency_matrix(geo_dist_graph, mode = "upper", diag = F)
The spatial coordinates where attched this way:
V(geo_dist_graph)$x <-
grid_grid$coords.x1[match(V(geo_dist_graph)$name, grid_grid$g9.nodes)]
V(geo_dist_graph)$y <-
grid_grid$coords.x2[match(V(geo_dist_graph)$name, grid_grid$g9.nodes)]
The graph is correclty plotted in space when using the plot function. But when I try to add a basemap like this plot(map_crop_sp, add = T), the map doesn't show behind the graph, but there is no error message.
The map is vector map, don't know if it's important. Here is the code used to create it.
map <- st_read("ne_10m_coastline/ne_10m_coastline.shp")
map_crop <- st_crop(map, xmin = 13.304078, ymin = 43.635623, xmax = 16.503846, ymax = 45.60185)
map_crop_sp <- as(map_crop, Class = "Spatial")
Answer Since the igraph should be on top of the map, I plot it second. I also added rescale = F: plot(map_crop_sp) plot(geo_dist_graph, add = T, rescale = F) Rationale I typed ?plot.igraph. From there, I found ?igraph.plotting. It seems that plotting an igraph object rescales it (plot(..., rescale = TRUE): Logical constant, whether to rescale the coordinates to the [-1,1]x-1,1 interval. This parameter is not implemented for tkplot. Defaults to TRUE, the layout will be rescaled.
Row and columns-wise calculation in long format in R
I am struggling with cellwise-calculations in a complex data-set (see below for dput() example).
I need to apply the formula for standardized mean difference (M1-M2/sqrt(s1^2+s2^2) to multiple rows and columns (studies and tests). The M1 & M2 (means) values are in the pr_cognm_ columns and s1 and s2 (standard deviations) in the pr_cognsd_ columns, and they should be calculated dependent on the factors id & tx...3 (treatments).
So e.g. for the pr_cognm_VV2_CRT_error column the id 336 has two rows and, in this case!, the values in the treat1 row need to be subtracted from VGT. But sometimes it is the other way around, e.g. within id 162 dGT needs to be subtracted from treat1 (luckily, this logic will be the same for each specific comparison though). Then, the same thing needs to happen with the standard deviations (i.e. potentiate and addition). Lastly, M and S need to be divided. There are many tests (columns) to run the formula on (e.g.pr_cognm_BVMT_perc_retention, pr_cognm_VV2_CRT_error, etc.) and often NA, since the specific id did not have this test. The data is in the long format and, to make it more complicated, some id have three instead of two rows (where two rows need to be subtracted from one other in a specific direction e.g. task1).
My best idea was to
#make a dataset
a <- readxl::read_excel("C:/.../reprod.xlsx")
b<- a[!grepl("com", a$id),] #already omitted in example dataset
pr_cognm <- dplyr::select(b,contains("pr_cognm"))
pr_cognsd <- dplyr::select(b,contains("pr_cognsd"))
c <- cbind(b$tx...3, b$id ,pr_cognm, pr_cognsd)
c$`b$id` <- as.factor(c$`b$id`)
#turn var's into numerics and factors
#potentiate all standard deviations (s1^2 and s2^2)
c[,3:ncol(c)] <- sapply(c[,3:ncol(c)], as.numeric)
c[,grepl("pr_cognsd", colnames(c))] <- c[,grepl("pr_cognsd", colnames(c))]^2
#then reshape
require(reshape2)
c %>%
dcast(b$id ~ b$tx...3, value.var = c("pr_cognm_VV2_CRT_error"), fill = 0)
b$id BF BL BT dGT H-TT HFL LM-TT treat1 VGT
1 55 0 0 0 0 0 0.00 0.00 0.00 0.00
2 162 0 0 0 0 0 0.00 0.00 0.00 0.00
3 236 0 0 0 0 0 0.00 0.00 0.00 0.00
4 336 0 0 0 0 0 0.00 0.00 8.75 7.58
5 377 0 0 0 0 0 0.00 0.00 0.00 0.00
6 521 0 0 0 0 0 0.00 0.00 0.00 0.00
7 525 0 0 0 0 0 0.00 0.00 0.00 0.00
8 527 0 0 0 0 0 0.00 0.00 0.00 0.00
9 528 0 0 0 0 0 0.00 0.00 0.00 0.00
10 535 0 0 0 0 0 5.65 6.54 0.00 0.00
11 548 0 0 0 0 0 0.00 0.00 0.00 0.00
12 553 0 0 0 0 0 0.00 0.00 0.00 0.00
Now I could define the rules which variables should be added like c$sub <- c$treat1-c$VGT and c$sub <- c$HFL-c$LM-TT, do the addition with the SD's in a similar fashion and finally divide the two variables to find the SMD. BUT, this only works for one test. In this case value.var = c("pr_cognm_VV2_CRT_error"). I would like to get this matrix for every test I have in the dataset via e.g. loop since more than one value.var dont work:
require(reshape2)
c %>%
dcast(b$id ~ b$tx...3, value.var = c("pr_cognm_VV2_CRT_error", "pr_cognm_BNT_perc_retention"), fill = 0)
Error in .subset2(x, i, exact = exact) : subscript out of bounds
In addition: Warning message:
In if (!(value.var %in% names(data))) { :
the condition has length > 1 and only the first element will be used
If there were a way to loop via
c %>%
+ dcast(b$id ~ b$tx...3, value.var = c(names(c[,3:ncol(c)]), fill = 0)
then I could maybe rbind them and do the subtractions into a new variable as described above and after doing the same for the SD's I would finally be able to do the division to get the SMD.
I could not get any solutions to work.
Reprod example (truncated):
a <- structure(list(checked = c("Y", "Y", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA), id = c("55", "55", "162", "162", "236", "236", "336", "336",
"377", "377", "521", "521", "525", "525", "527", "527", "528",
"528", "535", "535", "548", "548", "548", "553", "553"), tx...3 = c("task1",
"VGT", "dGT", "task1", "BT", "H-TT", "task1", "VGT", "BT", "H-TT",
"task1", "VGT", "HFL", "H-TT", "BF", "BT", "HFL", "task1", "HFL",
"LM-TT", "HFL", "BL", "task1", "HFL", "task1"), nta = c(2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3,
2, 2), id2 = c(1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2,
1, 2, 1, 2, 1, 2, 3, 1, 2), cross = c("N", "N", "N", "N", "N",
"N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N",
"N", "N", "N", "N", "N", "N", "N"), pre_post = c("N", "N", "N",
"N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N",
"N", "N", "N", "N", "N", "N", "N", "N", "N"), case_control = c("N",
"N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N",
"N", "N", "N", "N", "N", "N", "N", "N", "N", "N", "N"), expsy = c("Y",
"Y", "Y", "Y", "Y", "Y", "Y", "Y", "Y", "Y", "Y", "Y", "Y", "Y",
"Y", "Y", "Y", "Y", "Y", "Y", "Y", "Y", "Y", "Y", "Y"), hosp = c("Out",
"Out", "Out", "Out", "In", "In", "NA", "NA", "In", "In", "NR",
"NR", "NR", "NR", "Mx", "Mx", "NR", "NR", "Mx", "Mx", "Out",
"Out", "Out", "Out", "Out"), tx...11 = c("task1", "VGT", "dGT",
"task1", "BT", "H-TT", "task1", "VGT", "BT", "H-TT", "task1",
"VGT", "HFL", "H-TT", "BF", "BT", "HFL", "task1", "HFL", "LM-TT",
"HFL", "BL", "task1", "HFL", "task1"), vt_p = c("17", "17", "24",
"24", "21", "21", "NR", "NR", "NR", "NR", "NA", "NA", "17", "17",
"24", "24", "17", "17", "17", "17", "17", "17", "17", "17", "17"
), n_se = c("12", "12", "20", "20", "6", "6", "10", "10", "NR",
"NR", "20", "20", "10", "6", "8", "8", "15", "15", "10", "6",
"15", "15", "15", "10", "10"), cogn_name_AMI_K = c(NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA), cogn_cite_AMI_K = c(NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA), cogn_last_stim_AMI_K = c(NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA), n_bcogn_AMI_K = c(NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA), n_pcogn_AMI_K = c(NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA), pr_cognm_AMI_K = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA),
pr_cognsd_AMI_K = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
), po_cognm_n_AMI_K = c(NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA), po_cognsd_n_AMI_K = c(NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA), cogn_name_BVMT_perc_retention = c(NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "brief_visual_memory_test", "brief_visual_memory_test",
"brief_visual_memory_test", NA, NA), cogn_cite_BVMT_perc_retention = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, "benedict_1997", "benedict_1997", "benedict_1997",
NA, NA), cogn_last_stim_BVMT_perc_retention = c(NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "NR", "NR", "NR", NA, NA), n_bcogn_BVMT_perc_retention = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 19, 24, 18, NA, NA), n_pcogn_BVMT_perc_retention = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 19, 24, 18, NA, NA), pr_cognm_BVMT_perc_retention = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, "91.6", "86.6", "90", NA, NA), pr_cognsd_BVMT_perc_retention = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, "17", "36", "13.3", NA, NA), po_cognm_n_BVMT_perc_retention = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, "86.7", "82.1", "71.7", NA, NA), po_cognsd_n_BVMT_perc_retention = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, "20", "39.3", "24.2", NA, NA), cogn_name_BNT_naming = c(NA,
NA, NA, NA, NA, NA, NA, NA, "boston_naming_task_naming",
"boston_naming_task_naming", NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA), cogn_cite_BNT_naming = c(NA,
NA, NA, NA, NA, NA, NA, NA, "kaplan_1983", "kaplan_1983",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
), cogn_last_stim_BNT_naming = c(NA, NA, NA, NA, NA, NA,
NA, NA, 30, 30, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA), n_bcogn_BNT_naming = c(NA, NA, NA, NA, NA,
NA, NA, NA, 14, 14, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA), n_pcogn_BNT_naming = c(NA, NA, NA, NA,
NA, NA, NA, NA, 14, 14, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA), pr_cognm_BNT_naming = c(NA, NA,
NA, NA, NA, NA, NA, NA, "19.64", "18.14", NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), pr_cognsd_BNT_naming = c(NA,
NA, NA, NA, NA, NA, NA, NA, "9.15", "5.3", NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), po_cognm_n_BNT_naming = c(NA,
NA, NA, NA, NA, NA, NA, NA, "20.21", "20.71", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), po_cognsd_n_BNT_naming = c(NA,
NA, NA, NA, NA, NA, NA, NA, "9.38", "6.34", NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), cogn_name_VV2_CRT_error = c(NA,
NA, NA, NA, NA, NA, "VV2_crt_error", "VV2_crt_error", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, "VV2_crt_error", "VV2_crt_error",
NA, NA, NA, NA, NA), cogn_cite_VV2_CRT_error = c(NA, NA,
NA, NA, NA, NA, "robbins_1994", "robbins_1994", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, "robbins_1994", "robbins_1994",
NA, NA, NA, NA, NA), cogn_last_stim_VV2_CRT_error = c(NA,
NA, NA, NA, NA, NA, "NR", "NR", NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, "NR", "NR", NA, NA, NA, NA, NA), n_bcogn_VV2_CRT_error = c(NA,
NA, NA, NA, NA, NA, 12, 12, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 12, 12, NA, NA, NA, NA, NA), n_pcogn_VV2_CRT_error = c(NA,
NA, NA, NA, NA, NA, 12, 12, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 12, 12, NA, NA, NA, NA, NA), pr_cognm_VV2_CRT_error = c(NA,
NA, NA, NA, NA, NA, "8.75", "7.58", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, "5.65", "6.54", NA, NA, NA, NA, NA), pr_cognsd_VV2_CRT_error = c(NA,
NA, NA, NA, NA, NA, "1.13", "2.84", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, "1.10", "1.89", NA, NA, NA, NA, NA), po_cognm_n_VV2_CRT_error = c(NA,
NA, NA, NA, NA, NA, "7.50", "5.33", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, "7.50", "2.34", NA, NA, NA, NA, NA), po_cognsd_n_VV2_CRT_error = c(NA,
NA, NA, NA, NA, NA, "2.06", "2.42", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, "2.06", "2", NA, NA, NA, NA, NA), cogn_name_VV2_CRT_latency = c(NA,
NA, NA, NA, NA, NA, "VV2_crt_latency", "VV2_crt_latency",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA), cogn_cite_VV2_CRT_latency = c(NA, NA, NA, NA, NA,
NA, "robbins_1994", "robbins_1994", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), cogn_last_stim_VV2_CRT_latency = c(NA,
NA, NA, NA, NA, NA, "NR", "NR", NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), n_bcogn_VV2_CRT_latency = c(NA,
NA, NA, NA, NA, NA, 12, 12, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA), n_pcogn_VV2_CRT_latency = c(NA,
NA, NA, NA, NA, NA, 12, 12, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA), pr_cognm_VV2_CRT_latency = c(NA,
NA, NA, NA, NA, NA, "476.05", "465.65", NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), pr_cognsd_VV2_CRT_latency = c(NA,
NA, NA, NA, NA, NA, "35.86", "37.54", NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), po_cognm_n_VV2_CRT_latency = c(NA,
NA, NA, NA, NA, NA, "460.66", "433.13", NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), po_cognsd_n_VV2_CRT_latency = c(NA,
NA, NA, NA, NA, NA, "34.75", "46.70", NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA)), row.names = c(NA,
-25L), class = c("tbl_df", "tbl", "data.frame"))
How to further format forest Plots in R, from the metafor package?
I'm quite new to R and have been struggling with properly formatting a forest plot I've created.
When I click the "zoom" option in R to open the graph in a new window, it looks as such:
Forest Plot Currently
My main goal is to get the forest plot as compact as possible, i.e. publication quality/style. I currently have wayyyy too much white space in my plot. I think it has something to do with me messing around with the par() function, and now have no clue how to revert to defaults.
#Metafor library
library(metafor)
#ReadXL library to import excel sheet
library(readxl)
#Name the data sheet from the excel file
ACDF<- read_excel("outpatient_ACDF_meta_analysis.xlsx")
#View the data sheet with view(ACDF)
par(mar=c(20,1,1,1))
#This below measures with risk ratios. If you want to measure odds ratios, use argument measure=OR
returnop <- escalc(measure="OR", ai=op_return_OR, bi=op_no_return_OR, ci=ip_return_OR, di=ip_no_return_OR, data=ACDF)
#Generate a Random Effects Model
REmodel<-rma(yi=yi, vi=vi, data=returnop, slab=paste(Author, Year, sep=", "), method="REML")
#Generate a forest plot of the data
forest(REmodel, xlim=c(-17, 6),
ilab=cbind(ACDF$op_return_OR, ACDF$op_no_return_OR, ACDF$ip_return_OR, ACDF$ip_no_return_OR),
ilab.xpos=c(-9.5,-8,-6,-4.5), cex=.75, ylim=c(-1, 27),
psize=1)
### add column headings to the plot
text(c(-9.5,-8,-6,-4.5), 26, c("Return+", "Return-", "Return+", "Return-"))
text(c(-8.75,-5.25), 27, c("Outpatient", "Inpatient"))
text(-16, 26, "Study", pos=4)
text(6, 26, "Log Odds Ratio [95% CI]", pos=2)
I'm not 100% as to how to provide my data otherwise, but I used the dput function to provide as follows. Apologies for the N/As, still fleshing out the data for the future.
structure(list(Study = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA), Author = c("Stieber", "Villavicencio",
"Lied", "Liu", "Garringer", "Joseffer", "Trahan", "Lied", "Sheperd",
"Talley", "Martin", "McGirt", "Adamson", "Fu", "Arshi", "Khanna",
"McClelland", "Purger", "McLellend2", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Year = c(2005, 2007,
2007, 2009, 2010, 2010, 2011, 2012, 2012, 2013, 2015, 2015, 2016,
2017, 2017, 2017, 2017, 2017, 2017, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA), op_return_OR = c(NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, 1, 3, 2, 16, 257, 7, NA, 5, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
), op_no_return_OR = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
596, 769, 992, 4581, 958, 1749, NA, 3120, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), ip_return_OR = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, 8, 9, 2, 257, 2034, 12, NA,
200, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA), ip_no_return_OR = c(NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, 589, 641, 482, 16171, 8930, 1744, NA, 46312, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
), op_death = c(NA, NA, NA, 0, NA, NA, NA, NA, NA, NA, 1, NA,
1, 0, NA, 2, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA), op_no_death = c(NA, NA, NA, 45, NA,
NA, NA, NA, NA, NA, 596, NA, 993, 4597, NA, 1754, NA, 3125, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
), ip_death = c(NA, NA, NA, 0, NA, NA, NA, NA, NA, NA, 0, NA,
0, 42, NA, 2, NA, 20, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA), ip_no_death = c(NA, NA, NA, 64,
NA, NA, NA, NA, NA, NA, 597, NA, 484, 16386, NA, 1754, NA, 46492,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
2979.79797979798), op_thrombo = c(NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, 0, NA, NA, 8, 20, 4, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), op_no_thrombo = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, 597, NA, NA, 4589, 1195,
1752, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA), ip_thrombo = c(NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, 2, NA, NA, 67, 150, 4, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), ip_no_thrombo = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, 595, NA, NA, 16361, 10814,
1752, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA), op_stroke = c(NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, 0, NA, NA, 2, 12, 0, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), op_no_stroke = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, 597, NA, NA, 4595, 1203,
1756, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA), ip_stroke = c(NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, 2, NA, NA, 14, 132, 0, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), ip_no_stroke = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, 595, NA, NA, 16414, 10832,
1756, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA), op_dysphagia = c(NA, NA, NA, 0, NA, NA,
NA, NA, NA, NA, NA, NA, 11, NA, NA, NA, NA, 2, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), op_no_dysphagia = c(NA,
NA, NA, 45, NA, NA, NA, NA, NA, NA, NA, NA, 618, NA, NA, NA,
NA, 49, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA), ip_dysphagia = c(NA, NA, NA, 1, NA, NA, NA, NA,
NA, NA, NA, NA, 1, NA, NA, NA, NA, 59, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), ip_no_dysphagia = c(NA,
NA, NA, 63, NA, NA, NA, NA, NA, NA, NA, NA, 273, NA, NA, NA,
NA, 2917, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA), op_hematoma = c(NA, NA, NA, 0, NA, NA, NA, NA,
NA, NA, NA, NA, 1, NA, NA, NA, 1, 4, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), op_no_hematoma = c(NA,
NA, NA, 45, NA, NA, NA, NA, NA, NA, NA, NA, 629, NA, NA, NA,
2015, 47, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA), ip_hematoma = c(NA, NA, NA, 1, NA, NA, NA, NA,
NA, NA, NA, NA, 1, NA, NA, NA, 273, 65, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), ip_no_hematoma = c(NA,
NA, NA, 63, NA, NA, NA, NA, NA, NA, NA, NA, 273, NA, NA, NA,
7791, 1713, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA)), .Names = c("Study", "Author", "Year", "op_return_OR",
"op_no_return_OR", "ip_return_OR", "ip_no_return_OR", "op_death",
"op_no_death", "ip_death", "ip_no_death", "op_thrombo", "op_no_thrombo",
"ip_thrombo", "ip_no_thrombo", "op_stroke", "op_no_stroke", "ip_stroke",
"ip_no_stroke", "op_dysphagia", "op_no_dysphagia", "ip_dysphagia",
"ip_no_dysphagia", "op_hematoma", "op_no_hematoma", "ip_hematoma",
"ip_no_hematoma"), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA,
-35L))
The par option looks ok to me. I changed the ylim option and modified the y location and size of some of the header text as below:
#Generate a forest plot of the data
forest(REmodel, xlim=c(-17, 6),
ylim=c(-1, 10),
ilab=cbind(ACDF$op_return_OR, ACDF$op_no_return_OR, ACDF$ip_return_OR,
ACDF$ip_no_return_OR),
ilab.xpos=c(-9.5,-8,-6,-4.5), cex=.75,
psize=1)
### add column headings to the plot
text(c(-9.5,-8,-6,-4.5), 8.5, c("Return+", "Return-", "Return+", "Return-"),
cex = 0.65)
text(c(-8.75,-5.25), 9.5, c("Outpatient", "Inpatient"))
text(-17, 8.5, "Study", pos=4)
text(6, 8.5, "Log Odds Ratio [95% CI]", pos=2)
This gives the following plot:
Combine columns that have the same row values but are spread out
I want to combine these columns based on the value in "Date" so that there are only unique values of date with the corresponding age groups conglomerated. This was a result from using spread() in tidyr. If u look the values for Date are repeated
dput(dataframe) reads ....
structure(list(Date = c("201740", "201740", "201740", "201740",
"201741", "201741", "201741", "201741", "201742", "201742", "201742",
"201742", "201743", "201743", "201743", "201743", "201743", "201743",
"201744", "201744", "201744", "201744", "201744", "201744", "201745",
"201745", "201745", "201745", "201745", "201745", "201746", "201746",
"201746", "201746", "201746", "201746", "201747", "201747", "201747",
"201747", "201747", "201747", "201748", "201748", "201748", "201748",
"201748", "201748", "201749", "201749", "201749", "201749", "201749",
"201749", "201750", "201750", "201750", "201750", "201750", "201750",
"201751", "201751", "201751", "201751", "201751", "201751", "201752",
"201752", "201752", "201752", "201752", "201752", "201801", "201801",
"201801", "201801", "201801", "201801", "201802", "201802", "201802",
"201802", "201802", "201802", "201803", "201803", "201803", "201803",
"201803", "201803", "201804", "201804", "201804", "201804", "201804",
"201804", "201805"), `0-4 yr` = c(NA, 0.1, NA, NA, NA, 0.2, NA,
NA, NA, 0.2, NA, NA, NA, NA, 0.3, NA, NA, NA, NA, NA, 0.6, NA,
NA, NA, NA, NA, 0.7, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA,
1.8, NA, NA, NA, NA, NA, 2.7, NA, NA, NA, NA, NA, 3.3, NA, NA,
NA, NA, NA, 5.2, NA, NA, NA, NA, NA, 7.9, NA, NA, NA, NA, NA,
13.7, NA, NA, NA, NA, NA, 18.3, NA, NA, NA, NA, NA, 23.3, NA,
NA, NA, NA, NA, 28.2, NA, NA, NA, NA, NA, 35.6, NA, NA, NA, 41.9
), `18-49 yr` = c(NA, 0.1, NA, NA, 0.1, NA, NA, NA, NA, 0.2,
NA, NA, NA, 0.2, NA, NA, NA, NA, NA, 0.4, NA, NA, NA, NA, NA,
0.5, NA, NA, NA, NA, NA, 0.7, NA, NA, NA, NA, NA, 1, NA, NA,
NA, NA, NA, 1.4, NA, NA, NA, NA, NA, 1.9, NA, NA, NA, NA, NA,
2.7, NA, NA, NA, NA, NA, 4.2, NA, NA, NA, NA, NA, 6.6, NA, NA,
NA, NA, NA, 9.3, NA, NA, NA, NA, NA, 12.5, NA, NA, NA, NA, NA,
15.2, NA, NA, NA, NA, NA, 17.7, NA, NA, NA, NA, NA), `5-17 yr` = c(0,
NA, NA, NA, 0.1, NA, NA, NA, 0.1, NA, NA, NA, 0.1, NA, NA, NA,
NA, NA, 0.2, NA, NA, NA, NA, NA, 0.3, NA, NA, NA, NA, NA, 0.5,
NA, NA, NA, NA, NA, 0.7, NA, NA, NA, NA, NA, 0.9, NA, NA, NA,
NA, NA, 1.2, NA, NA, NA, NA, NA, 1.7, NA, NA, NA, NA, NA, 2.5,
NA, NA, NA, NA, NA, 3.5, NA, NA, NA, NA, NA, 4.3, NA, NA, NA,
NA, NA, 5.9, NA, NA, NA, NA, NA, 7.3, NA, NA, NA, NA, NA, 9,
NA, NA, NA, NA, NA, NA), `50-64 yr` = c(NA, NA, 0.2, NA, NA,
NA, 0.3, NA, NA, NA, 0.5, NA, NA, NA, NA, NA, 0.8, NA, NA, NA,
NA, NA, 1.1, NA, NA, NA, NA, NA, 1.6, NA, NA, NA, NA, NA, 2.2,
NA, NA, NA, NA, NA, 3.1, NA, NA, NA, NA, 4.1, NA, NA, NA, NA,
NA, 5.4, NA, NA, NA, NA, NA, NA, 8.1, NA, NA, NA, NA, NA, 13.7,
NA, NA, NA, NA, 21.7, NA, NA, NA, NA, NA, NA, 32.6, NA, NA, NA,
NA, NA, 42.9, NA, NA, NA, NA, NA, 52, NA, NA, NA, NA, NA, 60.2,
NA, NA), `65+ yr` = c(NA, NA, NA, 0.5, NA, NA, NA, 1, NA, NA,
NA, 2.1, NA, NA, NA, NA, NA, 3, NA, NA, NA, NA, NA, 3.9, NA,
NA, NA, NA, NA, 5.1, NA, NA, NA, NA, NA, 6.5, NA, NA, NA, NA,
NA, 9.2, NA, NA, NA, NA, NA, 14.3, NA, NA, NA, NA, NA, 20.5,
NA, NA, NA, NA, NA, 30.2, NA, NA, NA, NA, NA, 50.2, NA, NA, NA,
NA, NA, 90.1, NA, NA, NA, NA, NA, 137.9, NA, NA, NA, NA, NA,
179.5, NA, NA, NA, NA, NA, 217.4, NA, NA, NA, NA, NA, 251.8,
NA)), .Names = c("Date", "0-4 yr", "18-49 yr", "5-17 yr", "50-64 yr",
"65+ yr"), class = "data.frame", row.names = c(NA, 97L))
Could try aggregation, this could have been done before your spread. But after works as well
library(tidyverse)
dataframe %>%
group_by(Date) %>%
summarise_all(funs(sum(., na.rm = T)))
I've used sum() here because its not clear how you want to summarise.
A more suitable way might be:
dataframe %>%
gather("age_group", "value", -Date) %>%
filter(!is.na(value)) %>%
spread(age_group, value)
Where we gather the data back to may have what been your original input, this needs to be filtered and then just re-spread