I have the following reproducible data:
MyScaledData contains scaled values between 0 and 1 for 6 variables. minvec and maxvec are named vectors and contain the maximum and minimum values from the original data set that was used to create the scaled data frame MyScaledData. minvec and maxvec contain values for all 22 variables of the original data set, including the 6 variables I have now in MyScaledData.
X14863 X15066 X15067 X15068 X15069 X15070
0.6014784 0.6975109 0.5043208 0.15284648 0.9416364 0.7860731
0.2495215 0.7801444 0.6683925 0.13768245 0.4277954 0.2058412
0.6167705 0.3344044 0.9254125 0.12777565 0.3826231 0.2590457
0.1227380 0.4448501 0.3961802 0.19117246 0.7789835 0.7587897
0.7299760 0.6375931 0.5760061 0.44746838 0.3634903 0.1079679
0.1988647 0.7814712 0.6572054 0.71409305 0.6715690 0.4029459
0.5041371 0.6374958 0.9333635 0.89057831 0.5716711 0.7219823
0.5774327 0.7677038 0.7622717 0.45288270 0.2817869 0.2572325
0.6809509 0.6089656 0.8191862 0.01151454 0.2780449 0.4655353
0.5754383 0.5662045 0.7003630 0.62559642 0.2865510 0.1847980
MyScaledData<-structure(list(X14863=c(0.601478444979532,0.249521497274968,0.616770466379489,0.122737966507165,0.729975993009922,0.198864661389536,0.504137054265617,0.577432671357089,0.680950947164095,0.575438259547452),X15066=c(0.697510926657699,0.780144354632397,0.334404422875259,0.444850091405716,0.637593061483412,0.781471212351781,0.637495834667556,0.7677038048039,0.608965550162107,0.566204459603197),X15067=c(0.50432083998529,0.668392530333367,0.925412484830622,0.396180214305286,0.576006062451239,0.657205387087382,0.933363470346907,0.762271729415789,0.819186151914183,0.700362991098644),X15068=c(0.152846483002917,0.137682446305942,0.127775652495726,0.191172455317975,0.447468375530484,0.714093046059637,0.890578310935752,0.452882699805154,0.011514536383708,0.625596417031532),X15069=c(0.94163636689763,0.427795395079331,0.38262308941233,0.77898345642139,0.363490265569212,0.671568951210917,0.571671115989958,0.281786881885636,0.278044876559552,0.286551022600823),X15070=c(0.786073059382553,0.205841229942702,0.259045736299276,
0.758789694211416,0.107967864736275,0.402945912782515,0.721982268066207,0.257232456508833,0.46553533255268,0.184798001614338)),row.names=c(NA,10L),class="data.frame"); minvec<-c(X14861=22.95,X14862=29.95,X14863= 39.95,X15066=59.95,X15067=79.95,X15068=14.99,X15069=24.99,X15070=33.45,X15071=36.95,X15072=44.95,X15073=54.95,X15074=74.95,X15132=12.95,X15548=12.95,X15549=22.95,X15550=29.95,X15551=39.95,X15552=59.95,X15553=79.95,X15956=49.95,X15957=49.95,X16364=3.5);maxvec<-c(X14861=29.99,X14862=39.99,X14863=49.99,X15066=79.99,X15067=99.99,X15068=19.99,X15069=29.99,X15070=39.99,X15071=49.99,X15072=59.99,X15073=79.99,X15074=99.99,X15132=19.99,X15548=19.99,X15549=29.99,X15550=39.99,X15551=49.99,X15552=79.99,X15553=99.99,X15956=59.99,X15957=59.99,X16364=9.99)
I want to rescale back MyScaledData to their original scale by matching the min/max values to each corresponding column based on name. I've tried the following:
descale <- function(x,minval,maxval) {x*(maxval-minval) + minval}
as.data.frame(Map(descale,MyScaledData,minvec,maxvec))
The output I get has more than 6 columns than MyScaledData has. I sense that the function is not even matching columns by names and therefore the output is not calculated correctly. How can I match the function by column name so it takes the corresponding minvec and maxvec element for each column and return only the 6 columns I have?
Desired output shall be:
MyDeScaledData <- structure(list(X14863 = c(45.9888435875945, 42.4551958326407,46.1423754824501, 41.1822891837319, 47.2789589698196, 41.9466012003509,45.0115360248268, 45.7474240204252, 46.7867475095275, 45.7274001258564), X15066 = c(73.9281189702203, 75.5840928668332, 66.6514646344202,68.8647958317706, 72.7273649521276, 75.6106830955297, 72.7254165267378,75.3347842482702, 72.1536696252486, 71.2967373704481), X15067 = c(90.0565896333052,93.3445863078807, 98.4952661960057, 87.8894514946779, 91.4931614915228,93.1203959572311, 98.654603945752, 95.2259254574924, 96.3664904843602,93.9852743416168), X15068 = c(15.7542324150146, 15.6784122315297,15.6288782624786, 15.9458622765899, 17.2273418776524, 18.5604652302982,19.4428915546788, 17.2544134990258, 15.0475726819185, 18.1179820851577), X15069 = c(29.6981818344881, 27.1289769753967, 26.9031154470616,28.8849172821069, 26.8074513278461, 28.3478447560546, 27.8483555799498,26.3989344094282, 26.3802243827978, 26.4227551130041), X15070 = c(38.5909178083619,34.7962016438253, 35.1441591153973, 38.4124846001427, 34.1561098353752,36.0852662695976, 38.171764033153, 35.1323002655678, 36.4946010748945,34.6585789305578)), row.names = c(NA, 10L), class = "data.frame")
Thanks to @Shirin Yavari for providing the solution:
MyDeScaledData<-as.data.frame(Map(descale,MyScaledData,minvec[names(MyScaledData)],maxvec[names(MyScaledData)]))