I have the following data.table read from an excel sheet.
structure(list(AC = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 280.905387337496, NA, 278.107886102079, NA, 273.477288966662,
NA, 271.411774831244, NA, 273.638082495827, NA, 272.50162891041,
NA, 280.674549724992, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA), AD = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, 275.737756776872,
NA, 269.727645491455, NA, 266.930144256038, NA, 263.89490362062,
NA, 263.621819435203, NA, 261.212208799786, NA, 261.633573914368,
NA, 265.549082578951, NA, 261.625447343534, NA, 268.803616458116,
NA, NA, NA, NA, NA, NA, NA, NA, NA), AE = c(NA, NA, NA, NA, NA,
NA, 277.733589716248, NA, 270.562934780831, NA, 264.953226695414,
NA, 258.852399059996, NA, 255.063274274579, NA, 250.388883039162,
NA, NA, NA, 248.428790868327, NA, 251.88758963291, NA, 255.240031297492,
NA, 258.895903512075, NA, 259.733312576658, NA, 264.890696791241,
NA, NA, NA, NA, NA, NA), AF = c(NA, NA, NA, NA, NA, 280.641907320207,
NA, 267.471460684789, NA, 269.244186599372, NA, 250.102101613955,
NA, 245.493401528538, NA, 242.83666704312, NA, 240.439569007703,
NA, 238.261441472286, NA, 239.827709486868, NA, 241.347055251451,
NA, 248.193640466034, NA, 252.819239180617, NA, 257.366634145199,
NA, 262.117358859782, NA, NA, NA, NA, NA), AG = c(NA, NA, NA,
NA, 275.779900324165, NA, 265.215202638748, NA, 251.181386603331,
NA, 243.322538667914, NA, 236.940177532496, NA, 232.863262947079,
NA, 231.417122511662, NA, 229.620629276244, NA, 231.333920340827,
NA, 233.78232665541, NA, 236.352730819992, NA, 242.010619034575,
NA, 247.896862199158, NA, 254.787241513741, NA, 260.814251428323,
NA, NA, NA, NA), AH = c(NA, NA, NA, 275.525658278124, NA, 262.261367142707,
NA, 252.735215257289, NA, NA, NA, 230.470301436455, NA, 223.928404651038,
NA, 220.39266001562, NA, 220.607567230203, NA, 222.001786994786,
NA, 223.987227109368, NA, 228.712926623951, NA, 233.128939288534,
NA, NA, NA, 244.669942517699, NA, 253.171319082282, NA, 260.011647996865,
NA, NA, NA), AI = c(NA, NA, 282.635081332083, NA, 260.852837746665,
NA, 250.416394211248, NA, 238.343928225831, NA, 228.376707190414,
NA, 220.780623854996, NA, 216.303306069579, NA, 211.960498734162,
NA, 212.769754448744, NA, 217.648733313327, NA, 223.14708587791,
NA, 224.854120642492, NA, 231.669424357075, NA, 239.157280321658,
NA, 245.750485386241, NA, 254.311296800823, NA, 260.441535665406,
NA, NA), AJ = c(NA, 275.902440636041, NA, 263.470237400624, NA,
250.209074415207, NA, 236.422382229789, NA, 226.336291494372,
NA, 232.454017758955, NA, 211.735345173538, NA, 207.87740108812,
NA, 205.076771702703, NA, 209.677345217286, NA, 213.211219581868,
NA, 220.924302346451, NA, 226.000354661034, NA, 233.162883025617,
NA, 240.888478390199, NA, 248.160492004782, NA, 255.157228419365,
NA, 262.885951933947, NA), AK = c(275.94224469, NA, 263.456862904583,
NA, 251.916182419165, NA, 239.543414033748, NA, 227.402128748331,
NA, 220.710080762913, NA, NA, NA, 205.361506592079, NA, 201.609919606662,
NA, 202.234614471244, NA, 206.181404635827, NA, 212.52122955041,
NA, NA, NA, 224.972524429575, NA, 235.879448344158, NA, 245.969925108741,
NA, 251.865552723323, NA, 259.625557737906, NA, 270.551250552489
), AL = c(NA, 266.993938658541, NA, 254.377174573124, NA, 242.248401887707,
NA, 230.210345552289, NA, 220.593477316872, NA, 211.549060531455,
NA, 208.279208646038, NA, 199.70714251062, NA, 197.219328125203,
NA, 199.608299589786, NA, 206.755187204368, NA, 214.727906418951,
NA, 221.439981183534, NA, 230.498168448116, NA, 239.859786262699,
NA, 250.044107527282, NA, 256.896949041865, NA, 266.433743256447,
NA), AM = c(267.9847003125, NA, 257.617076077083, NA, NA, NA,
234.773454506248, NA, 224.221269420831, NA, 215.236287485413,
NA, 216.001749099996, NA, 240.078184514579, NA, 195.038145679162,
NA, NA, NA, 199.822344908327, NA, 209.29031982291, NA, 217.478881387492,
NA, 225.761287452075, NA, 235.013420016658, NA, 240.539925931241,
NA, NA, NA, 261.143179710406, NA, 271.408832874989), AN = c(NA,
263.963230531041, NA, 251.818817095624, NA, 240.403262610207,
NA, 228.756225024789, NA, 219.802524589372, NA, 220.561729903955,
NA, 230.492671018538, NA, 196.73274108312, NA, 194.845531497703,
NA, 195.767400612286, NA, 201.544158526868, NA, 230.178308491451,
NA, 220.827333006034, NA, 231.299444070617, NA, 239.419186335199,
NA, 250.066473799782, NA, 259.515679814365, NA, 270.191120628947,
NA), AO = c(272.452167735, NA, 260.576775199583, NA, 245.435594064165,
NA, 235.121148378748, NA, 225.438588993331, NA, 217.986400557913,
NA, 218.379612322496, NA, 212.388269937079, NA, 214.577039801662,
NA, 198.553720366244, NA, 204.327350130827, NA, 209.12186894541,
NA, 222.431212059992, NA, 228.070331374575, NA, 240.991783889158,
NA, 247.528682253741, NA, 258.373043168323, NA, 268.366547282906,
NA, 277.843906647489), AP = c(NA, 271.180341803541, NA, 259.239258118124,
NA, 244.310791182707, NA, 235.945182947289, NA, 224.714189311872,
NA, 217.327692026455, NA, 210.863998991038, NA, 206.54308870562,
NA, 206.661023270203, NA, 207.998936334786, NA, 211.429581749368,
NA, 217.963351963951, NA, 226.036171978534, NA, 235.022411793116,
NA, 247.168083107699, NA, 258.262696022282, NA, 269.213414036865,
NA, 278.556262951447, NA), AQ = c(NA, NA, 265.332032422083, NA,
254.889332586665, NA, 245.353796251248, NA, 236.181125315831,
NA, 246.862822430414, NA, 220.754347394996, NA, 215.923548659579,
NA, 215.375187274162, NA, NA, NA, 218.104191953327, NA, 221.05935856791,
NA, 226.570223732492, NA, 237.214383047075, NA, 248.631195411658,
NA, 262.907136876241, NA, 274.280155140823, NA, 280.288396155406,
NA, NA), AR = c(NA, NA, NA, 263.925696040624, NA, 252.303683655207,
NA, 243.440699569789, NA, NA, NA, 230.009681348955, NA, 225.379084213538,
NA, 221.49298677812, NA, 222.258448392703, NA, 223.881023107286,
NA, 227.865351071868, NA, 233.567033386451, NA, 240.823406251034,
NA, NA, NA, 262.968837980199, NA, 274.582723794782, NA, 287.400947359365,
NA, NA, NA), AS = c(NA, NA, NA, NA, 262.678895309165, NA, 254.335184123748,
NA, 245.910141038331, NA, 239.365116102914, NA, 235.247535567496,
NA, 231.226927682079, NA, 229.921553996662, NA, 230.167742711244,
NA, 232.816350625827, NA, 239.98200714041, NA, 247.019409504992,
NA, 255.849241819575, NA, 265.332857484158, NA, 275.798712248741,
NA, 285.457504313323, NA, NA, NA, NA), AT = c(NA, NA, NA, NA,
NA, 264.316248877707, NA, 257.226925842289, NA, 251.720446706872,
NA, 244.484100621455, NA, 241.489525936038, NA, 236.97154220062,
NA, 237.802694965203, NA, 242.043531229786, NA, 247.401117044368,
NA, 252.452144158951, NA, 261.447768423534, NA, 269.483050638116,
NA, 282.454553552699, NA, 292.948561667282, NA, NA, NA, NA, NA
), AU = c(NA, NA, NA, NA, NA, NA, 267.320603996248, NA, 261.507566160831,
NA, 255.888473625413, NA, 252.030529539996, NA, 251.472783704579,
NA, 250.708579969162, NA, NA, NA, 255.129913798327, NA, 261.06307921291,
NA, 268.313195777492, NA, 276.135763792075, NA, 288.994653306658,
NA, 297.358391271241, NA, NA, NA, NA, NA, NA), AV = c(NA, NA,
NA, NA, NA, NA, NA, NA, NA, 266.701626279372, NA, 262.824913293955,
NA, 262.920950808538, NA, 260.03898952312, NA, 261.182957287703,
NA, 265.007749602286, NA, 269.689655016868, NA, 275.579026331451,
NA, 283.470413646034, NA, 292.428500110616, NA, NA, NA, NA, NA,
NA, NA, NA, NA), AW = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 270.731079462496, NA, 272.475652027079, NA, 271.630116391662,
NA, 273.868936656244, NA, 277.452861420827, NA, 283.75827668541,
NA, 290.848857599992, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA)), row.names = c(NA, -37L), class = c("tbl_df", "tbl",
"data.frame"))
Is there a vectorized way to transform this table into the following format? The result should be a new data.frame/data.table with two columns ('cell' and 'value'). Each cell, which is not NA in original table, will be a row in the transformed table. Content of column 'value' is the value, content of column 'cell' should include the concatenated column and row information from original cell (e.g. AC9)
structure(list(cell = c("AC13", "AC15", "AC17", "AC19", "AC21",
"AC23", "AC25", "AD10", "AD12", "AD14", "AD16", "AD18", "AD20",
"AD22", "AD24", "AD26", "AD28", "AE7", "AE9", "AE11", "AE13",
"AE15", "AE17", "AE21", "AE23", "AE25", "AE27", "AE29", "AE31",
"AF6", "AF8", "AF10", "AF12", "AF14", "AF16", "AF18", "AF20",
"AF22", "AF24", "AF26", "AF28", "AF30", "AF32", "AG5", "AG7",
"AG9", "AG11", "AG13", "AG15", "AG17", "AG19", "AG21", "AG23",
"AG25", "AG27", "AG29", "AG31", "AG33", "AH4", "AH6", "AH8",
"AH12", "AH14", "AH16", "AH18", "AH20", "AH22", "AH24", "AH26",
"AH30", "AH32", "AH34", "AI3", "AI5", "AI7", "AI9", "AI11", "AI13",
"AI15", "AI17", "AI19", "AI21", "AI23", "AI25", "AI27", "AI29",
"AI31", "AI33", "AI35", "AJ2", "AJ4", "AJ6", "AJ8", "AJ10", "AJ12",
"AJ14", "AJ16", "AJ18", "AJ20", "AJ22", "AJ24", "AJ26", "AJ28",
"AJ30", "AJ32", "AJ34", "AJ36", "AK1", "AK3", "AK5", "AK7", "AK9",
"AK11", "AK15", "AK17", "AK19", "AK21", "AK23", "AK27", "AK29",
"AK31", "AK33", "AK35", "AK37", "AL2", "AL4", "AL6", "AL8", "AL10",
"AL12", "AL14", "AL16", "AL18", "AL20", "AL22", "AL24", "AL26",
"AL28", "AL30", "AL32", "AL34", "AL36", "AM1", "AM3", "AM7",
"AM9", "AM11", "AM13", "AM15", "AM17", "AM21", "AM23", "AM25",
"AM27", "AM29", "AM31", "AM35", "AM37", "AN2", "AN4", "AN6",
"AN8", "AN10", "AN12", "AN14", "AN16", "AN18", "AN20", "AN22",
"AN24", "AN26", "AN28", "AN30", "AN32", "AN34", "AN36", "AO1",
"AO3", "AO5", "AO7", "AO9", "AO11", "AO13", "AO15", "AO17", "AO19",
"AO21", "AO23", "AO25", "AO27", "AO29", "AO31", "AO33", "AO35",
"AO37", "AP2", "AP4", "AP6", "AP8", "AP10", "AP12", "AP14", "AP16",
"AP18", "AP20", "AP22", "AP24", "AP26", "AP28", "AP30", "AP32",
"AP34", "AP36", "AQ3", "AQ5", "AQ7", "AQ9", "AQ11", "AQ13", "AQ15",
"AQ17", "AQ21", "AQ23", "AQ25", "AQ27", "AQ29", "AQ31", "AQ33",
"AQ35", "AR4", "AR6", "AR8", "AR12", "AR14", "AR16", "AR18",
"AR20", "AR22", "AR24", "AR26", "AR30", "AR32", "AR34", "AS5",
"AS7", "AS9", "AS11", "AS13", "AS15", "AS17", "AS19", "AS21",
"AS23", "AS25", "AS27", "AS29", "AS31", "AS33", "AT6", "AT8",
"AT10", "AT12", "AT14", "AT16", "AT18", "AT20", "AT22", "AT24",
"AT26", "AT28", "AT30", "AT32", "AU7", "AU9", "AU11", "AU13",
"AU15", "AU17", "AU21", "AU23", "AU25", "AU27", "AU29", "AU31",
"AV10", "AV12", "AV14", "AV16", "AV18", "AV20", "AV22", "AV24",
"AV26", "AV28", "AW13", "AW15", "AW17", "AW19", "AW21", "AW23",
"AW25"), value = c(280.905387337496, 278.107886102079, 273.477288966662,
271.411774831244, 273.638082495827, 272.50162891041, 280.674549724992,
275.737756776872, 269.727645491455, 266.930144256038, 263.89490362062,
263.621819435203, 261.212208799786, 261.633573914368, 265.549082578951,
261.625447343534, 268.803616458116, 277.733589716248, 270.562934780831,
264.953226695414, 258.852399059996, 255.063274274579, 250.388883039162,
248.428790868327, 251.88758963291, 255.240031297492, 258.895903512075,
259.733312576658, 264.890696791241, 280.641907320207, 267.471460684789,
269.244186599372, 250.102101613955, 245.493401528538, 242.83666704312,
240.439569007703, 238.261441472286, 239.827709486868, 241.347055251451,
248.193640466034, 252.819239180617, 257.366634145199, 262.117358859782,
275.779900324165, 265.215202638748, 251.181386603331, 243.322538667914,
236.940177532496, 232.863262947079, 231.417122511662, 229.620629276244,
231.333920340827, 233.78232665541, 236.352730819992, 242.010619034575,
247.896862199158, 254.787241513741, 260.814251428323, 275.525658278124,
262.261367142707, 252.735215257289, 230.470301436455, 223.928404651038,
220.39266001562, 220.607567230203, 222.001786994786, 223.987227109368,
228.712926623951, 233.128939288534, 244.669942517699, 253.171319082282,
260.011647996865, 282.635081332083, 260.852837746665, 250.416394211248,
238.343928225831, 228.376707190414, 220.780623854996, 216.303306069579,
211.960498734162, 212.769754448744, 217.648733313327, 223.14708587791,
224.854120642492, 231.669424357075, 239.157280321658, 245.750485386241,
254.311296800823, 260.441535665406, 275.902440636041, 263.470237400624,
250.209074415207, 236.422382229789, 226.336291494372, 232.454017758955,
211.735345173538, 207.87740108812, 205.076771702703, 209.677345217286,
213.211219581868, 220.924302346451, 226.000354661034, 233.162883025617,
240.888478390199, 248.160492004782, 255.157228419365, 262.885951933947,
275.94224469, 263.456862904583, 251.916182419165, 239.543414033748,
227.402128748331, 220.710080762913, 205.361506592079, 201.609919606662,
202.234614471244, 206.181404635827, 212.52122955041, 224.972524429575,
235.879448344158, 245.969925108741, 251.865552723323, 259.625557737906,
270.551250552489, 266.993938658541, 254.377174573124, 242.248401887707,
230.210345552289, 220.593477316872, 211.549060531455, 208.279208646038,
199.70714251062, 197.219328125203, 199.608299589786, 206.755187204368,
214.727906418951, 221.439981183534, 230.498168448116, 239.859786262699,
250.044107527282, 256.896949041865, 266.433743256447, 267.9847003125,
257.617076077083, 234.773454506248, 224.221269420831, 215.236287485413,
216.001749099996, 240.078184514579, 195.038145679162, 199.822344908327,
209.29031982291, 217.478881387492, 225.761287452075, 235.013420016658,
240.539925931241, 261.143179710406, 271.408832874989, 263.963230531041,
251.818817095624, 240.403262610207, 228.756225024789, 219.802524589372,
220.561729903955, 230.492671018538, 196.73274108312, 194.845531497703,
195.767400612286, 201.544158526868, 230.178308491451, 220.827333006034,
231.299444070617, 239.419186335199, 250.066473799782, 259.515679814365,
270.191120628947, 272.452167735, 260.576775199583, 245.435594064165,
235.121148378748, 225.438588993331, 217.986400557913, 218.379612322496,
212.388269937079, 214.577039801662, 198.553720366244, 204.327350130827,
209.12186894541, 222.431212059992, 228.070331374575, 240.991783889158,
247.528682253741, 258.373043168323, 268.366547282906, 277.843906647489,
271.180341803541, 259.239258118124, 244.310791182707, 235.945182947289,
224.714189311872, 217.327692026455, 210.863998991038, 206.54308870562,
206.661023270203, 207.998936334786, 211.429581749368, 217.963351963951,
226.036171978534, 235.022411793116, 247.168083107699, 258.262696022282,
269.213414036865, 278.556262951447, 265.332032422083, 254.889332586665,
245.353796251248, 236.181125315831, 246.862822430414, 220.754347394996,
215.923548659579, 215.375187274162, 218.104191953327, 221.05935856791,
226.570223732492, 237.214383047075, 248.631195411658, 262.907136876241,
274.280155140823, 280.288396155406, 263.925696040624, 252.303683655207,
243.440699569789, 230.009681348955, 225.379084213538, 221.49298677812,
222.258448392703, 223.881023107286, 227.865351071868, 233.567033386451,
240.823406251034, 262.968837980199, 274.582723794782, 287.400947359365,
262.678895309165, 254.335184123748, 245.910141038331, 239.365116102914,
235.247535567496, 231.226927682079, 229.921553996662, 230.167742711244,
232.816350625827, 239.98200714041, 247.019409504992, 255.849241819575,
265.332857484158, 275.798712248741, 285.457504313323, 264.316248877707,
257.226925842289, 251.720446706872, 244.484100621455, 241.489525936038,
236.97154220062, 237.802694965203, 242.043531229786, 247.401117044368,
252.452144158951, 261.447768423534, 269.483050638116, 282.454553552699,
292.948561667282, 267.320603996248, 261.507566160831, 255.888473625413,
252.030529539996, 251.472783704579, 250.708579969162, 255.129913798327,
261.06307921291, 268.313195777492, 276.135763792075, 288.994653306658,
297.358391271241, 266.701626279372, 262.824913293955, 262.920950808538,
260.03898952312, 261.182957287703, 265.007749602286, 269.689655016868,
275.579026331451, 283.470413646034, 292.428500110616, 270.731079462496,
272.475652027079, 271.630116391662, 273.868936656244, 277.452861420827,
283.75827668541, 290.848857599992)), row.names = c(NA, -301L), class = "data.frame")
Currently I use two nested loops to achieve the desired result:
cols <- ncol(dt)
rows <- nrow(dt)
transformedDT <- data.frame(cell=character(), value=numeric())
for (c in 1:cols) {
currentCol <- colnames(dt)[c]
for (r in 1:rows) {
curCell <- dt[[r, c]]
if (!is.na(curCell)){
transformedDT <- rbind(transformedDT, data.frame(cell=paste0(currentCol,r), value=curCell))
}
}
}
Since I have a lot of those files to process, the execution time needs to be improved.
A data.table solution is preferable to a dplyr solution because I concentrate on data.table as my workhorse.
