Subset xts object using vector of unique index days - r

I'm trying to subset an xts object using a vector of xts timestamps that have been processed into a vector of unique timestamps. This follows on from this previous question that was only partially answered.
Some sample data:
dput(sample.data.merge, control="all")
structure(c(11.65, 11.13, 11.13, 11.5, 11.8, 11.45, 11.45, 11.08,
11.08, 11.25, 9.8, 10.45, 10.9, 10.9, 10.9, 10.9, 10.9, 10.9,
10.45, 10.5, 10.5, 10.08, 10.08, 10.65, 10.08, 10.65, 10.6, 10.65,
10.65, 10.085, 10.145, 11.9, 11.085, 9.35, 9.15, 9.15, 9.9, 9.0875,
9.3, 9.3, 9.3, 9.35, 9.35, 9.35, 9.25, 9.5, 9.45, 9.3, 11.15,
11.15, 11.15, 11.15, 11.8, 8, 10.05, 10.05, 10.25, 10.4, 10.15,
10.15, 10.3, 10.15, 10.1, 11.08, 11.08, 11.08, 11.65, 11.85,
11.9, 11.9, 11.9, 12.65, 13.35, 13.35, 15.95, 15.9, 15.4, 15.4,
15.4, 15.4, 15.13, 12.13, 12.35, 11.082, 11.082, 11.08, 12.1,
12.3, 12.3, 12.4, 12.6, 12.6, 12.13, 12.45, 12.9, 12.9, 12.9,
14, 12.6, 12.6, 12.45, 15.25, 12.085, 12.95, 12.95, 12.35, 12.13,
12.8, 14, 14, 12.45, 12.45, 12.45, 12.45, 12.25, 12.6, 12.085,
15.1, 15.15, 15.35, 15.3, 12.5, 12.5, 12.15, 12.2, 11.085, 11.35,
11.45, 11.13, 11.13, 11.35, 11.2, 12.5, 12.6, 12.95, 12.95, 12.5,
12.45, 12.3, 12.3, 12.3, 12.45, 12.45, 12.45, 12.5, 12.45, 12.45,
12.13, 12.13, 12.65, 190, 190, 190, 190, 130, 190, 190, 190,
190, 190, 130, 190, 130, 130, 445, 445, 445, 445, 130, 445, 190,
445, 445, 190, 190, 190, 190, 130, 190, 190, 190, 190, 190, 190,
190, 190, 190, 190, 190, 190, 190, 190, 190, 190, 190, 190, 190,
190, 275, 190, 190, 190, 190, 190, 190, 190, 190, 190, 130, 130,
190, 190, 190, 130, 130, 130, 190, 130, 190, 190, 190, 130, 190,
190, 190, 190, 190, 190, 190, 190, 190, 190, 190, 190, 190, 190,
1190, 190, 190, 130, 130, 130, 190, 1130, 190, 190, 130, 190,
190, 190, 190, 190, 190, 130, 130, 190, 190, 375, 190, 190, 190,
130, 190, 130, 190, 190, 190, 190, 130, 190, 190, 190, 190, 190,
190, 190, 190, 190, 190, 190, 190, 190, 190, 190, 190, 190, 190,
130, 130, 130, 190, 130, 190, 190, 190, 130, 130, 445, 445, 130,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, 0, 0, NA, NA, NA, NA, NA, 0.21, 0.21, 0.26, 0.0250000000000004,
0, 0.0250000000000004, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, 0.0249999999999995, 0.0250000000000004, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.0250000000000004,
0.100000000000001, 0.39, NA, NA, NA, NA, NA, 0.0250000000000004,
NA, NA, NA, NA, NA, 0.524999999999999, 0.25, 0, 0, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, 0.149999999999999, 0.135000000000001,
0.149999999999999, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, 0.409999999999999, 0.375, 0.3, 0.635, 0.385, 0.335, 0.175000000000001,
0, NA, NA, NA, NA, NA, 1.4, 0.2, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, 0.109999999999999, NA, NA, NA, NA, NA, NA, NA, NA,
NA, 0.0749999999999993, 0.0749999999999993, 0.0749999999999993,
0.0250000000000004, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 0, NA, NA, NA,
NA, NA, 127.5, 0, 0, 0, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, 30, 30, 30, NA, NA, NA, NA,
NA, 0, NA, NA, NA, NA, NA, 0, 0, 0, 0, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 30, 30, 30, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, 0, 30, 30, 0, 0, 0, 0, 0, NA, NA, NA, NA, NA, 0,
0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA,
NA, NA, NA, NA, NA, 0, 0, 30, 0, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 10.9,
10.9, NA, NA, NA, NA, NA, 10.29, 10.29, 10.34, 10.625, 10.65,
10.625, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 9.325,
9.325, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 10.15, 10.225, 10.69, NA, NA, NA, NA, NA, 11.9,
NA, NA, NA, NA, NA, 15.4, 15.4, 15.4, 15.4, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, 12.35, 12.35, 12.425, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, 12.65, 12.575, 12.875, 12.875, 12.625,
12.625, 12.625, 12.45, NA, NA, NA, NA, NA, 13.85, 15.125, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, 11.275, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 12.375, 12.375, 12.375, 12.45, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 445, 445, NA, NA, NA, NA, NA, 317.5, 190, 190, 190, 190,
190, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 190,
190, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 160, 160, 160, NA, NA, NA, NA, NA, 190, NA, NA,
NA, NA, NA, 190, 190, 190, 190, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 160, 160, 160, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 190, 190, 190, 190, 190, 190, 190, 190, NA, NA, NA, NA,
NA, 190, 190, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 190, NA,
NA, NA, NA, NA, NA, NA, NA, NA, 130, 130, 160, 190, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NaN, Inf, NA, NA, NA, NA, NA, 0.999999999999996,
1.71428571428572, 1, 1, NaN, 21.5999999999997, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, 1.00000000000004, 2.99999999999993,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 37.1999999999995, 8.54999999999987, 0.999999999999998,
NA, NA, NA, NA, NA, 29.9999999999996, NA, NA, NA, NA, NA, 0,
0, NaN, Inf, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1.66666666666666,
1.62962962962963, 0.166666666666658, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, 1.26829268292683, 0.600000000000004,
3.75, 1.77165354330709, 0.454545454545457, 0.522388059701495,
1, NaN, NA, NA, NA, NA, NA, 1.07142857142857, 0.875000000000003,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.681818181818179, NA,
NA, NA, NA, NA, NA, NA, NA, NA, 1, 1, 1, 2, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NaN, Inf, NA, NA, NA, NA, NA, 1, NaN, NaN, Inf, NaN, NaN,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NaN, NaN,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 1, 1, 1, NA, NA, NA, NA, NA, Inf, NA, NA, NA, NA, NA,
NaN, NaN, NaN, NaN, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1,
1, 32.3333333333333, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NaN, 6.16666666666667, 0, NaN, NaN, Inf, NaN, Inf, NA,
NA, NA, NA, NA, NaN, NaN, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NaN, NA, NA, NA, NA, NA, NA, NA, NA, NA, NaN, Inf, 1, NaN,
NA, NA, NA, NA, NA), .Dim = c(150L, 8L), .Dimnames = list(NULL,
c("price", "volume", "madprice", "madvolume", "medianprice",
"medianvolume", "absdevmadprice", "absdevmadvolume")), index = structure(c(1325584080,
1325594940, 1325594940, 1325604600, 1325759100, 1325762520, 1325762520,
1325769300, 1325769300, 1325848080, 1325864880, 1326128220, 1326196500,
1326196500, 1326196500, 1326196500, 1326196500, 1326196500, 1326209700,
1326279480, 1326283620, 1326288300, 1326288300, 1326289680, 1326289680,
1326289680, 1326292320, 1326294060, 1326294600, 1326297600, 1326387000,
1326456720, 1326467160, 1326711600, 1326723000, 1326724260, 1326809940,
1326814860, 1326885960, 1326885960, 1326889980, 1326894000, 1326895200,
1326895200, 1326898080, 1326986700, 1326987240, 1326992100, 1327072140,
1327328040, 1327328040, 1327328040, 1327417920, 1327423140, 1327424820,
1327425240, 1327483200, 1327496520, 1327570320, 1327570320, 1327575420,
1327588680, 1327588980, 1327595880, 1327595880, 1327595880, 1327664820,
1327674720, 1327680660, 1327680780, 1327680780, 1327683960, 1327914300,
1327914300, 1327915260, 1327918140, 1327924860, 1327924920, 1327924980,
1327924980, 1327927680, 1328013360, 1328014200, 1328025000, 1328025000,
1328026740, 1328089440, 1328091360, 1328091360, 1328110620, 1328111340,
1328111340, 1328112420, 1328113800, 1328193540, 1328194080, 1328194140,
1328196720, 1328274360, 1328274420, 1328278320, 1328519280, 1328520120,
1328520600, 1328520600, 1328524140, 1328527980, 1328531580, 1328540880,
1328540880, 1328547600, 1328547660, 1328547720, 1328547780, 1328607060,
1328608080, 1328618760, 1328623380, 1328623380, 1328625720, 1328631480,
1328717760, 1328717880, 1328793000, 1328797980, 1329132840, 1329210480,
1329215400, 1329215820, 1329215820, 1329219480, 1329223140, 1329300900,
1329301620, 1329315240, 1329315240, 1329388740, 1329389700, 1329390000,
1329390000, 1329390180, 1329391860, 1329391860, 1329391860, 1329402120,
1329467700, 1329467700, 1329469080, 1329469080, 1329471300), tzone = "", tclass = c("POSIXlt",
"POSIXt")), .indexCLASS = c("POSIXlt", "POSIXt"), .indexTZ = "", tclass = c("POSIXlt",
"POSIXt"), tzone = "", class = c("xts", "zoo"))
The code:
sample.data.mergesub <- sample.data.merge['T10:30/T17:30']
sample.data.mergeout <- sample.data.mergesub[ which((sample.data.mergesub$absdevmadprice >=5 & sample.data.mergesub$absdevmadprice < Inf) | (sample.data.mergesub$absdevmadvol>=10 & sample.data.mergesub$absdevmadvol<Inf)),]
sample.data.unique <- unique(.indexday(sample.data.mergeout))
This sample.data.unique is therefore a vector of index days. Question: I'd like to use this to extract the full day of data from the original dataset sample.data in order to later graph the full day of trades, rather than the subset of data. For instance, if Jan 03 2012 10:53:00 meets the conditions of having absdevmadprice >= 5, and less than infinite, then I'd like to return the day (Jan 03 2012) into a vector and use this to subset the original dataset. This would select all observations in that day (so over the whole trading period) and I could then graph this day.
I've tried this code (based on Joshua's answer here) but it doesn't work:
> sample.data.uniquePOS<-sample.data.merge[paste(as.Date(as.POSIXct(sample.data.unique, origin = "1970-01-01 00:00.00 UTC", tz="GMT")))]
It returns simply the column names:
> sample.data.uniquePOS
price volume madprice madvolume medianprice medianvolume absdevmadprice
absdevmadvolume
For info, the structure of the variables:
> str(sample.data.merge)
An ‘xts’ object on 2012-01-03 09:48:00/2012-02-17 09:35:00 containing:
Data: num [1:150, 1:8] 11.6 11.1 11.1 11.5 11.8 ...
- attr(*, "dimnames")=List of 2
..$ : NULL
..$ : chr [1:8] "price" "volume" "madprice" "madvolume" ...
Indexed by objects of class: [POSIXlt,POSIXt] TZ:
xts Attributes:
NULL
> str(sample.data.uniquePOS)
An 'xts' object of zero-width
> str(sample.data.unique)
num 15371
Thanks for the help (and if anyone can explain why the code doesn't work!).


answer to own question:
Using these posts (Ananda's answer to this, Joshua's answer to this, and the as.Date.numeric function I found out about here) I was able to solve my own problem. This line of code seems to do it:
sample.data.uniquePOS <- sample.data.merge[paste(as.Date.numeric(sample.data.unique, origin= "1970-01-01 00:00.00 UTC", tz="GMT")),]
Can't give a great explanation as to why it works compared to the below, but perhaps as.POSIXct can't take the same format that as.Date.numeric can?
sample.data.uniquePOS <- sample.data.merge[paste(as.Date(as.POSIXct(sample.data.unique, origin = "1970-01-01 00:00.00 UTC", tz="GMT")))]

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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!

R, Pivot longer, multiple observations per row

I think I have a question that is nearly identical to this one: R Pivot multiple columns from wide to long but I am hopelessly lost on the regex when trying to follow along.
I am also trying to pivot data to be longer, and I also have multiple columns I'd like to save. My data currently:
FollowUpScans<-structure(list(study_id = c(40, 44, 49, 61, 66, 67, 68, 84, 86,
94, 95, 101, 123, 126, 131, 153, 154, 155, 156, 161, 166, 169,
175, 185, 199, 203, 207, 211, 217, 221, 227, 256, 257, 259, 266,
275, 284, 301, 306, 307, 309, 313, 320, 353, 382, 392, 398, 401,
402, 412, 415, 428, 431, 433, 434, 436), Score1 = c(3, 0, 4,
4, NA, 0, 0, 5, 0, 0, 7, 0, 4, 0, 4, 2, 3, 1, 0, 2, 2, 0, 3,
0, 0, 0, 9, 0, 0, 0, 6, 0, 0, 7, 5, 7, 0, 0, 8, 0, 0, 0, 5, 0,
3, 0, 5, 0, 2, 0, 0, 0, 0, 7, 0, 2), TimeBetweenScans = structure(c(316,
113, 335, 104, 7, 42, 30, 643, 404, 40, 171, 51, 449, 56, 104,
79, 116, 65, 39, 1193, 142, 106, 221, 36, 125, 137, 927, 63,
156, 32, 411, 201, 160, 166, 459, 212, 50, 312, 1627, 354, 33,
62, 842, 174, 216, 17, 214, 24, 149, 72, 9, 13, 42, 771, 113,
122), class = "difftime", units = "days"), Score2 = c(NA, 0,
7, NA, NA, NA, 0, 7, NA, 5, 8, 0, NA, NA, NA, 8, NA, NA, 9, NA,
NA, 0, 4, NA, NA, 0, 9, 2, 0, NA, NA, NA, NA, NA, NA, NA, 4,
1, 8, NA, NA, 3, NA, 0, 8, NA, 5, NA, 7, NA, 0, 3, NA, 7, NA,
4), TimeBetweenScans2 = structure(c(NA, 139, 660, NA, NA, NA,
84, 1794, NA, 221, 320, 227, NA, NA, NA, 989, NA, NA, 411, NA,
NA, 216, 474, NA, NA, 372, 1006, 429, 447, NA, NA, NA, NA, NA,
NA, NA, 313, 530, 1706, NA, NA, 130, NA, 300, 264, NA, 268, NA,
382, NA, 38, 138, NA, 1200, 166, 475), class = "difftime", units = "days"),
Score3 = c(NA, NA, NA, NA, NA, NA, 7, NA, NA, 8, NA, NA,
NA, NA, NA, 8, NA, NA, NA, NA, NA, 1, 4, NA, NA, 0, NA, 5,
0, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA,
NA, NA, NA, 5, NA, NA, NA, NA, NA, NA, 8, 0, 4), TimeBetweenScans3 = structure(c(NA,
NA, NA, NA, NA, NA, 467, NA, NA, 394, NA, NA, NA, NA, NA,
1097, NA, NA, NA, NA, NA, 266, 796, NA, NA, 941, NA, 533,
470, NA, NA, NA, NA, NA, NA, NA, NA, 783, NA, NA, NA, NA,
NA, NA, NA, NA, 388, NA, NA, NA, NA, NA, NA, 1512, 180, 640
), class = "difftime", units = "days"), Score4 = c(NA, NA,
NA, NA, NA, NA, 8, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 5, NA, NA, NA, 1, NA, 5, 0, NA, NA, NA, NA,
NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA), TimeBetweenScans4 = structure(c(NA,
NA, NA, NA, NA, NA, 826, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, 497, NA, NA, NA, 1102, NA, 567, 1204,
NA, NA, NA, NA, NA, NA, NA, NA, 1574, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), class = "difftime", units = "days"),
Score5 = c(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, 1, NA,
NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA),
TimeBetweenScans5 = structure(c(NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 575,
NA, NA, NA, 1225, NA, NA, 1266, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA), class = "difftime", units = "days")), row.names = c(NA,
-56L), class = c("tbl_df", "tbl", "data.frame"))
And instead of columns that looks like: study_id, Score1, TimeBetweenScans,Score2,TimeBetweenScans2, Score3, TimeBetweenScans3,etc.etc..
I'd love it to ultimately look like: study_id,Score,Time,Occurence
The "Occurence" column would just have a 1,2,3,4 etc.. to demonstrate which column it came from. The study_id column would be nice to keep because it demonstrates which "person" it came from.
Any help would be appreciated! Thank you!

You can try:
FollowUpScans %>%
rename(TimeBetweenScans1 = TimeBetweenScans) %>%
pivot_longer(-study_id,
names_to = c(".value", "Time"),
names_pattern = "([A-Za-z]+)([0-9]+)")
The steps are:
Rename the column that is likely to cause problems
pivot_longer specifying that the columns are named in a any number of characters followed by any number of digits pattern. You can use different regex patterns than the one I've shared here. For example, you could probably use "(.*)(\\d+)" for this particular dataset.
If you don't rename first, I would suspect that you would end up with too many rows. You should end up with nrow(FollowUpScans) * 5 rows.

extracting information from excel into lists in R

hello all i have this datasset :
> dput(test1)
structure(list(startdate = c("2019-11-06", "2019-11-06", "2019-11-06",
"2019-11-06", "2019-11-06", "2019-11-06", "2019-11-06", "2019-11-06",
"2019-11-06", "2019-11-06", "2019-11-06", "2019-11-06", "2019-11-06",
"2019-11-06", "2019-11-06", "2019-11-06", "2019-11-06", "2019-11-06",
"2019-11-06", "2019-11-06", "2019-11-06", "2019-11-27", "2019-11-27",
"2019-11-27", "2019-11-27", "2019-11-27", "2019-11-27", "2019-11-27",
"2019-11-27", "2019-11-27", "2019-11-27", "2019-11-27", "2019-11-27",
"2019-11-27", "2019-11-27", "2019-11-27", "2019-11-27", "2019-11-27",
"2019-11-27", "2019-11-27", "2019-11-01", "2019-11-05", "2019-11-15",
"2019-11-16", "2019-11-17", "2019-11-18", "2019-11-19", "2019-11-20",
"2019-11-21", NA), id = c("POL55", "POL56", "POL57", "POL58",
"POL59", "POL60", "POL61", "POL62", "POL63", "POL64", "POL65",
"POL66", "POL67", "POL68", "POL69", "POL56", "POL57", "POL58",
"POL59", "POL60", "POL61", "POL55", "POL56", "POL57", "POL58",
"POL59", "POL60", "POL61", "POL55", "POL56", "POL57", "POL58",
"POL59", "POL60", "POL61", "POL55", "POL56", "POL57", "POL58",
"POL59", "POL60", "POL61", "POL62", "POL63", "POL64", "POL65",
"POL66", "POL67", "POL68", NA), m0_9 = c(NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
32, 34, NA, NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98,
33, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), m10_19 = c(NA,
NA, NA, 32, 34, NA, NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65,
3, 98, 33, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
), m20_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, 32, 34, NA,
NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33, NA, NA,
NA, NA, NA, NA, NA), m30_39 = c(NA, NA, NA, NA, NA, NA, NA, NA,
NA, 32, 34, NA, NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3,
98, 33, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA), m40_49 = c(32, 34, NA, NA,
NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), m50_59 = c(NA,
NA, NA, NA, NA, NA, 32, 34, NA, NA, NA, NA, 55, 3, NA, NA, NA,
7, 9, 1, 65, 3, 98, 33, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
), m60_69 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, 32, 34, NA, NA, NA, NA, 55, 3, NA, NA, NA, 7, 9,
1, 65, 3, 98, 33, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA), m70 = c(NA, NA, NA, NA, NA, NA, 32,
34, NA, NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), f0_9 = c(32, 34, NA,
NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), f10_19 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, 32, 34, NA, NA, NA, NA, 55,
3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
), f20_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, 32, 34, NA, NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3,
98, 33, NA, NA, NA), f30_39 = c(NA, NA, NA, 32, 34, NA, NA, NA,
NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA), f40_49 = c(NA, NA, NA, NA,
NA, 32, 34, NA, NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3,
98, 33, NA, NA, NA, NA, NA, NA, NA, NA, 32, 34, NA, NA, NA, NA,
55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33, NA), f50_59 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 32, 34, NA, NA, NA, NA,
55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
), f60_69 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 32, 34, NA, NA, NA, NA,
55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA), f70 = c(NA, NA, NA, NA, NA, NA, NA, NA,
NA, 32, 34, NA, NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3,
98, 33, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA)), row.names = c(NA, -50L), class = c("tbl_df",
"tbl", "data.frame"))
I would like to create a list called ageCat. This list should contain a number of lists. The number of lists is the amount of age categories. Then for each age category i would like to extract the following info startAge, endAge, maleCount,femaleCount, totalCount.
Additionaly, i want only to sum up only individuals that have the same id and start date. For now i have written this:
create list of age
createLists <- function(startdate, id){
testFiltered = test1[policyid == id & start == startdate]
ageGroup <- vector("list", length == 8)
names(ageGroup) <- as.character(seq_along(ageGroup))
for(ageCat in seq_along(ageGroup)){
ageGroup[[ageCat]] <- getAgeInfo(testFiltered, ageCat)
}
getAgeInfo <- function(testFiltered, ageCat){
start =
end =
nomales =
nofemales =
}
ageGroup <- list(startAge = start,
endAge = end ,
maleCount = nomales ,
femaleCount = nofemales)
}
I have hard coded the length of the vecor ageGroup. How can i do this without hard coding it, aka. to look up how many columns with age categories I have for each gender?
Secondly, how can i extract the information startAge, endAge, maleCount,femaleCount, totalCount

Instead of working with lists I suggest to convert your data.frame to long format, getting rid of missing values and extracting sex and age. A `tidyverse´ approach might look like this:
library(dplyr)
library(tidyr)
library(tibble)
df <- tibble(
startdate = c(
"2019-11-06", "2019-11-06", "2019-11-06",
"2019-11-06", "2019-11-06", "2019-11-06", "2019-11-06", "2019-11-06",
"2019-11-06", "2019-11-06", "2019-11-06", "2019-11-06", "2019-11-06",
"2019-11-06", "2019-11-06", "2019-11-06", "2019-11-06", "2019-11-06",
"2019-11-06", "2019-11-06", "2019-11-06", "2019-11-27", "2019-11-27",
"2019-11-27", "2019-11-27", "2019-11-27", "2019-11-27", "2019-11-27",
"2019-11-27", "2019-11-27", "2019-11-27", "2019-11-27", "2019-11-27",
"2019-11-27", "2019-11-27", "2019-11-27", "2019-11-27", "2019-11-27",
"2019-11-27", "2019-11-27", "2019-11-01", "2019-11-05", "2019-11-15",
"2019-11-16", "2019-11-17", "2019-11-18", "2019-11-19", "2019-11-20",
"2019-11-21", NA
),
id = c(
"POL55", "POL56", "POL57", "POL58",
"POL59", "POL60", "POL61", "POL62", "POL63", "POL64", "POL65",
"POL66", "POL67", "POL68", "POL69", "POL56", "POL57", "POL58",
"POL59", "POL60", "POL61", "POL55", "POL56", "POL57", "POL58",
"POL59", "POL60", "POL61", "POL55", "POL56", "POL57", "POL58",
"POL59", "POL60", "POL61", "POL55", "POL56", "POL57", "POL58",
"POL59", "POL60", "POL61", "POL62", "POL63", "POL64", "POL65",
"POL66", "POL67", "POL68", NA
),
m0_9 = c(
NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
32, 34, NA, NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98,
33, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
),
m10_19 = c(
NA,
NA, NA, 32, 34, NA, NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65,
3, 98, 33, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
),
m20_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, 32, 34, NA,
NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33, NA, NA,
NA, NA, NA, NA, NA
),
m30_39 = c(
NA, NA, NA, NA, NA, NA, NA, NA,
NA, 32, 34, NA, NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3,
98, 33, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA
),
m40_49 = c(
32, 34, NA, NA,
NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
),
m50_59 = c(
NA,
NA, NA, NA, NA, NA, 32, 34, NA, NA, NA, NA, 55, 3, NA, NA, NA,
7, 9, 1, 65, 3, 98, 33, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
), m60_69 = c(
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, 32, 34, NA, NA, NA, NA, 55, 3, NA, NA, NA, 7, 9,
1, 65, 3, 98, 33, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA
), m70 = c(
NA, NA, NA, NA, NA, NA, 32,
34, NA, NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
), f0_9 = c(
32, 34, NA,
NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
), f10_19 = c(
NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, 32, 34, NA, NA, NA, NA, 55,
3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
), f20_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, 32, 34, NA, NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3,
98, 33, NA, NA, NA
), f30_39 = c(
NA, NA, NA, 32, 34, NA, NA, NA,
NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA
), f40_49 = c(
NA, NA, NA, NA,
NA, 32, 34, NA, NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3,
98, 33, NA, NA, NA, NA, NA, NA, NA, NA, 32, 34, NA, NA, NA, NA,
55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33, NA
), f50_59 = c(
NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 32, 34, NA, NA, NA, NA,
55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
), f60_69 = c(
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 32, 34, NA, NA, NA, NA,
55, 3, NA, NA, NA, 7, 9, 1, 65, 3, 98, 33, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA
), f70 = c(
NA, NA, NA, NA, NA, NA, NA, NA,
NA, 32, 34, NA, NA, NA, NA, 55, 3, NA, NA, NA, 7, 9, 1, 65, 3,
98, 33, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA
)
)
# Convert to tidy data frame
df_age <- df %>%
gather(age_sex, count, -startdate, -id) %>%
filter(!is.na(count)) %>%
extract(age_sex, into = c("sex", "start_age", "end_age"), regex = "(m|f)(\\d+)_?(\\d+)?", remove = FALSE) %>%
mutate(ageg = paste0(start_age, "_", end_age))
df_age
#> # A tibble: 187 x 8
#> startdate id age_sex sex start_age end_age count ageg
#> <chr> <chr> <chr> <chr> <chr> <chr> <dbl> <chr>
#> 1 2019-11-27 POL55 m0_9 m 0 9 32 0_9
#> 2 2019-11-27 POL56 m0_9 m 0 9 34 0_9
#> 3 2019-11-27 POL61 m0_9 m 0 9 55 0_9
#> 4 2019-11-27 POL55 m0_9 m 0 9 3 0_9
#> 5 2019-11-27 POL59 m0_9 m 0 9 7 0_9
#> 6 2019-11-27 POL60 m0_9 m 0 9 9 0_9
#> 7 2019-11-27 POL61 m0_9 m 0 9 1 0_9
#> 8 2019-11-27 POL55 m0_9 m 0 9 65 0_9
#> 9 2019-11-27 POL56 m0_9 m 0 9 3 0_9
#> 10 2019-11-27 POL57 m0_9 m 0 9 98 0_9
#> # ... with 177 more rows
# df back to nested list by startdate and ageg
df_list <- df_age %>%
# Count by startdate, ageg, start_age, end_age, sex
count(startdate, ageg, start_age, end_age, sex, wt = count) %>%
# male and female counts back in columns
spread(sex, n, fill = 0) %>%
# split by startdate
split(.$startdate) %>%
# ... and split each startdate list by ageg
lapply(function(x) split(x, x$ageg))
Created on 2020-03-10 by the reprex package (v0.3.0)

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

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