This is an older assignment from a class on cleaning data. The data set used is the UCI HAR dataset for activity, available at https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip
The purpose of the assignment was to combine these two machine learning datasets into a single data set, homogenize it, and post it to my github repository.
Upon reflection, I believe I did a good job reading in the data. Using fread from the data.table package, I only read in variables corresponding to a regular expression. This saved time and computing power by not having to read in the full data set then reduce it.
Things that could be improved: - Use more regular expressions to rename the variables into something shorter, more descriptive, and more programming-friendly. - Make use of data.table’s join capabilities instead of using data frame functions to join datasets. - Come up with a way to more efficiently split the variable names up from the variable file; I don’t think using the stringr package was 100% necessary.
## Getting and Cleaning Data
## Peer-reviewed assignment
require(data.table)## Loading required package: data.tablerequire(stringr)## Loading required package: stringr## Get files
download.file("https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip",
destfile="./wearables.zip")
unzip("wearables.zip")
setwd("./UCI HAR Dataset")
## Read in files
varnames<-readLines("features.txt")
testsubj<-as.numeric(readLines("./test/subject_test.txt"))
testact<-as.factor(readLines("./test/y_test.txt"))
trainsubj<-as.numeric(readLines("./train/subject_train.txt"))
trainact<-as.factor(readLines("./train/y_train.txt"))
test<-fread("./test/X_test.txt",
select = which(c(1:length(varnames)*grepl("std\\(|mean\\(",
x=varnames)>0)))
train<-fread("./train/X_train.txt",
select = which(c(1:length(varnames)*grepl("std\\(|mean\\(",
x=varnames)>0)))
# Combine, organize, and label data
test<-cbind(Subject=testsubj,Activity=testact,test)
train<-cbind(Subject=trainsubj,Activity=trainact,train)
full<-rbind(test,train)
varnames<-str_split_fixed(varnames," ",2)[,2][grepl("std\\(|mean\\(",
x=varnames)]
names(full)[3:68]<-varnames
levels(full$Activity)<-c("walking","walkingupstairs",
"walkingdownstairs","sitting","standing","laying")
# Create tidy aggregate dataset
avgdat<-full[ ,lapply(.SD,mean),keyby="Subject,Activity",.SDcols=3:68]
head(avgdat,24)## Subject Activity tBodyAcc-mean()-X tBodyAcc-mean()-Y
## 1: 1 walking 0.2773308 -0.017383819
## 2: 1 walkingupstairs 0.2554617 -0.023953149
## 3: 1 walkingdownstairs 0.2891883 -0.009918505
## 4: 1 sitting 0.2612376 -0.001308288
## 5: 1 standing 0.2789176 -0.016137590
## 6: 1 laying 0.2215982 -0.040513953
## 7: 2 walking 0.2764266 -0.018594920
## 8: 2 walkingupstairs 0.2471648 -0.021412113
## 9: 2 walkingdownstairs 0.2776153 -0.022661416
## 10: 2 sitting 0.2770874 -0.015687994
## 11: 2 standing 0.2779115 -0.018420827
## 12: 2 laying 0.2813734 -0.018158740
## 13: 3 walking 0.2755675 -0.017176784
## 14: 3 walkingupstairs 0.2608199 -0.032410941
## 15: 3 walkingdownstairs 0.2924235 -0.019355408
## 16: 3 sitting 0.2571976 -0.003502998
## 17: 3 standing 0.2800465 -0.014337656
## 18: 3 laying 0.2755169 -0.018955679
## 19: 4 walking 0.2785820 -0.014839948
## 20: 4 walkingupstairs 0.2708767 -0.031980430
## 21: 4 walkingdownstairs 0.2799653 -0.009802009
## 22: 4 sitting 0.2715383 -0.007163065
## 23: 4 standing 0.2804997 -0.009489111
## 24: 4 laying 0.2635592 -0.015003184
## Subject Activity tBodyAcc-mean()-X tBodyAcc-mean()-Y
## tBodyAcc-mean()-Z tBodyAcc-std()-X tBodyAcc-std()-Y tBodyAcc-std()-Z
## 1: -0.11114810 -0.28374026 0.114461337 -0.26002790
## 2: -0.09730200 -0.35470803 -0.002320265 -0.01947924
## 3: -0.10756619 0.03003534 -0.031935943 -0.23043421
## 4: -0.10454418 -0.97722901 -0.922618642 -0.93958629
## 5: -0.11060182 -0.99575990 -0.973190056 -0.97977588
## 6: -0.11320355 -0.92805647 -0.836827406 -0.82606140
## 7: -0.10550036 -0.42364284 -0.078091253 -0.42525752
## 8: -0.15251390 -0.30437641 0.108027280 -0.11212102
## 9: -0.11681294 0.04636668 0.262881789 -0.10283791
## 10: -0.10921827 -0.98682228 -0.950704499 -0.95982817
## 11: -0.10590854 -0.98727189 -0.957304989 -0.94974185
## 12: -0.10724561 -0.97405946 -0.980277399 -0.98423330
## 13: -0.11267486 -0.36035673 -0.069914065 -0.38741199
## 14: -0.11006486 -0.31312344 0.011628081 -0.36975460
## 15: -0.11613984 -0.05741005 -0.033150372 -0.36224025
## 16: -0.09835792 -0.97101012 -0.856617812 -0.87511018
## 17: -0.10162172 -0.96674254 -0.893449307 -0.91141902
## 18: -0.10130048 -0.98277664 -0.962057545 -0.96369103
## 19: -0.11140306 -0.44082997 -0.078826737 -0.58625281
## 20: -0.11421946 -0.20493304 -0.066689911 -0.37213778
## 21: -0.10677752 0.01119355 -0.218598325 -0.47918598
## 22: -0.10587460 -0.98030993 -0.890223981 -0.93220301
## 23: -0.09615749 -0.97692058 -0.861597379 -0.89688054
## 24: -0.11068815 -0.95419374 -0.941714042 -0.96266731
## tBodyAcc-mean()-Z tBodyAcc-std()-X tBodyAcc-std()-Y tBodyAcc-std()-Z
## tGravityAcc-mean()-X tGravityAcc-mean()-Y tGravityAcc-mean()-Z
## 1: 0.9352232 -0.28216502 -0.06810286
## 2: 0.8933511 -0.36215336 -0.07540294
## 3: 0.9318744 -0.26661034 -0.06211996
## 4: 0.8315099 0.20441159 0.33204370
## 5: 0.9429520 -0.27298383 0.01349058
## 6: -0.2488818 0.70554977 0.44581772
## 7: 0.9130173 -0.34660709 0.08472709
## 8: 0.7907174 -0.41621489 -0.19588824
## 9: 0.8618313 -0.32578010 -0.04388902
## 10: 0.9404773 -0.10563002 0.19872677
## 11: 0.8969286 -0.37006270 0.12974716
## 12: -0.5097542 0.75253664 0.64683488
## 13: 0.9365067 -0.26198636 -0.13810787
## 14: 0.8835334 -0.38285115 -0.16294396
## 15: 0.9390578 -0.22882921 -0.10235276
## 16: 0.9010990 0.12730338 0.13902058
## 17: 0.9350308 -0.30173513 0.02476311
## 18: -0.2417585 0.83703210 0.48870319
## 19: 0.9639997 -0.08585403 0.12776411
## 20: 0.9462643 -0.23294430 0.08416754
## 21: 0.9477319 -0.06208528 0.14871481
## 22: 0.8693030 0.21162254 0.11012048
## 23: 0.9561978 -0.07590091 0.16689383
## 24: -0.4206647 0.91516510 0.34153131
## tGravityAcc-mean()-X tGravityAcc-mean()-Y tGravityAcc-mean()-Z
## tGravityAcc-std()-X tGravityAcc-std()-Y tGravityAcc-std()-Z
## 1: -0.9766096 -0.9713060 -0.9477172
## 2: -0.9563670 -0.9528492 -0.9123794
## 3: -0.9505598 -0.9370187 -0.8959397
## 4: -0.9684571 -0.9355171 -0.9490409
## 5: -0.9937630 -0.9812260 -0.9763241
## 6: -0.8968300 -0.9077200 -0.8523663
## 7: -0.9726932 -0.9721169 -0.9720728
## 8: -0.9344077 -0.9237675 -0.8780041
## 9: -0.9403618 -0.9400685 -0.9314383
## 10: -0.9799888 -0.9567503 -0.9544159
## 11: -0.9866858 -0.9741944 -0.9459271
## 12: -0.9590144 -0.9882119 -0.9842304
## 13: -0.9777716 -0.9623556 -0.9520918
## 14: -0.9440408 -0.9098260 -0.9094697
## 15: -0.9500611 -0.9460946 -0.8999439
## 16: -0.9573245 -0.9039230 -0.8977363
## 17: -0.9820204 -0.9574253 -0.9281616
## 18: -0.9825122 -0.9812027 -0.9648075
## 19: -0.9838265 -0.9679632 -0.9629681
## 20: -0.9584952 -0.9233760 -0.9196195
## 21: -0.9552589 -0.9320660 -0.9377538
## 22: -0.9814053 -0.9327271 -0.9509493
## 23: -0.9729084 -0.9176135 -0.8994048
## 24: -0.9212000 -0.9698166 -0.9761766
## tGravityAcc-std()-X tGravityAcc-std()-Y tGravityAcc-std()-Z
## tBodyAccJerk-mean()-X tBodyAccJerk-mean()-Y tBodyAccJerk-mean()-Z
## 1: 0.07404163 0.0282721096 -0.0041684062
## 2: 0.10137273 0.0194863076 -0.0455625449
## 3: 0.05415532 0.0296504490 -0.0109719730
## 4: 0.07748252 -0.0006191028 -0.0033677924
## 5: 0.07537665 0.0079757309 -0.0036852495
## 6: 0.08108653 0.0038382040 0.0108342364
## 7: 0.06180807 0.0182492679 0.0078953371
## 8: 0.07445078 -0.0097098551 0.0194814392
## 9: 0.11004062 -0.0032795908 -0.0209351678
## 10: 0.07225644 0.0116954511 0.0076054693
## 11: 0.07475886 0.0103291775 -0.0083715885
## 12: 0.08259725 0.0122547885 -0.0018026490
## 13: 0.08147459 0.0100591485 -0.0056226459
## 14: 0.04268810 0.0397249270 0.0208205538
## 15: 0.07256893 0.0109707769 -0.0020272798
## 16: 0.07260984 0.0027252913 -0.0042334837
## 17: 0.07509006 0.0077166364 -0.0080717793
## 18: 0.07698111 0.0138041011 -0.0043562587
## 19: 0.07835291 0.0029560243 -0.0007676793
## 20: 0.05609719 0.0234018993 0.0034028084
## 21: 0.09718627 0.0056378022 -0.0072913777
## 22: 0.07845002 -0.0108582171 -0.0121499952
## 23: 0.07213284 -0.0065301569 -0.0211889891
## 24: 0.09344942 0.0069331321 -0.0064105433
## tBodyAccJerk-mean()-X tBodyAccJerk-mean()-Y tBodyAccJerk-mean()-Z
## tBodyAccJerk-std()-X tBodyAccJerk-std()-Y tBodyAccJerk-std()-Z
## 1: -0.11361560 0.06700250 -0.5026998
## 2: -0.44684389 -0.37827443 -0.7065935
## 3: -0.01228386 -0.10160139 -0.3457350
## 4: -0.98643071 -0.98137197 -0.9879108
## 5: -0.99460454 -0.98564873 -0.9922512
## 6: -0.95848211 -0.92414927 -0.9548551
## 7: -0.27753046 -0.01660224 -0.5860904
## 8: -0.27612189 -0.18564895 -0.5737464
## 9: 0.14724914 0.12682801 -0.3401220
## 10: -0.98805585 -0.97798396 -0.9875182
## 11: -0.98108572 -0.97105944 -0.9828414
## 12: -0.98587217 -0.98317254 -0.9884420
## 13: -0.26867964 -0.04496196 -0.5294861
## 14: -0.45836462 -0.25168036 -0.7085517
## 15: -0.08580100 -0.11143919 -0.5717352
## 16: -0.97446739 -0.95363139 -0.9746616
## 17: -0.95708649 -0.94168679 -0.9730596
## 18: -0.98087931 -0.96871072 -0.9820932
## 19: -0.29704261 -0.22116513 -0.7513914
## 20: -0.38048803 -0.28154318 -0.7264953
## 21: -0.14575971 -0.14624229 -0.6266470
## 22: -0.97674220 -0.94459611 -0.9790388
## 23: -0.97258654 -0.93835468 -0.9730542
## 24: -0.97830278 -0.94220949 -0.9785120
## tBodyAccJerk-std()-X tBodyAccJerk-std()-Y tBodyAccJerk-std()-Z
## tBodyGyro-mean()-X tBodyGyro-mean()-Y tBodyGyro-mean()-Z
## 1: -0.041830964 -0.069530046 0.08494482
## 2: 0.050549380 -0.166170015 0.05835955
## 3: -0.035078190 -0.090937129 0.09008501
## 4: -0.045350057 -0.091924155 0.06293138
## 5: -0.023987735 -0.059397221 0.07480075
## 6: -0.016553094 -0.064486124 0.14868944
## 7: -0.053025816 -0.048238232 0.08283366
## 8: -0.057691263 -0.032088310 0.06883740
## 9: -0.115947353 -0.004823292 0.09717381
## 10: -0.045470662 -0.059928680 0.04122775
## 11: -0.023862388 -0.082039658 0.08783517
## 12: -0.018476607 -0.111800825 0.14488285
## 13: -0.025640519 -0.077915094 0.08134859
## 14: 0.072198031 -0.139275406 0.02156037
## 15: -0.131573276 -0.013935804 0.12382674
## 16: -0.038536520 -0.075241003 0.09401140
## 17: -0.024662607 -0.058510192 0.06652621
## 18: -0.020817054 -0.071850716 0.13799956
## 19: -0.031798256 -0.072690528 0.08056772
## 20: 0.039382520 -0.085947168 0.08437538
## 21: -0.102838823 -0.070402595 0.05926395
## 22: -0.049443512 -0.089430061 0.10115033
## 23: -0.030644934 -0.061824851 0.07556364
## 24: -0.009231563 -0.093012818 0.16972040
## tBodyGyro-mean()-X tBodyGyro-mean()-Y tBodyGyro-mean()-Z
## tBodyGyro-std()-X tBodyGyro-std()-Y tBodyGyro-std()-Z
## 1: -0.4735355 -0.054607769 -0.3442666
## 2: -0.5448711 0.004105184 -0.5071687
## 3: -0.4580305 -0.126349195 -0.1247025
## 4: -0.9772113 -0.966473895 -0.9414259
## 5: -0.9871919 -0.987734440 -0.9806456
## 6: -0.8735439 -0.951090440 -0.9082847
## 7: -0.5615503 -0.538453668 -0.4810855
## 8: -0.4392531 -0.466298337 -0.1639958
## 9: -0.3207892 -0.415739145 -0.2794184
## 10: -0.9857420 -0.978919527 -0.9598037
## 11: -0.9729986 -0.971441996 -0.9648567
## 12: -0.9882752 -0.982291609 -0.9603066
## 13: -0.5718696 -0.563793260 -0.4766964
## 14: -0.4560393 -0.582742846 -0.4923273
## 15: -0.2616534 -0.546740388 -0.4423078
## 16: -0.9654348 -0.944854571 -0.9264137
## 17: -0.9004622 -0.927788618 -0.9123641
## 18: -0.9745458 -0.977272654 -0.9635056
## 19: -0.5009167 -0.665394093 -0.6626082
## 20: -0.4544310 -0.551185569 -0.3608110
## 21: -0.3702447 -0.699453537 -0.4984808
## 22: -0.9701318 -0.958468120 -0.9279722
## 23: -0.9096880 -0.949227147 -0.9099950
## 24: -0.9731024 -0.961109292 -0.9620738
## tBodyGyro-std()-X tBodyGyro-std()-Y tBodyGyro-std()-Z
## tBodyGyroJerk-mean()-X tBodyGyroJerk-mean()-Y tBodyGyroJerk-mean()-Z
## 1: -0.08999754 -0.03984287 -0.04613093
## 2: -0.12223277 -0.04214859 -0.04071255
## 3: -0.07395920 -0.04399028 -0.02704611
## 4: -0.09367938 -0.04021181 -0.04670263
## 5: -0.09960921 -0.04406279 -0.04895055
## 6: -0.10727095 -0.04151729 -0.07405012
## 7: -0.08188334 -0.05382994 -0.05149392
## 8: -0.08288580 -0.04240537 -0.04451575
## 9: -0.05810385 -0.04214703 -0.07102298
## 10: -0.09363284 -0.04156020 -0.04358510
## 11: -0.10556216 -0.04224195 -0.05465395
## 12: -0.10197413 -0.03585902 -0.07017830
## 13: -0.09523982 -0.03878747 -0.05036161
## 14: -0.11551057 -0.04003725 -0.04981809
## 15: -0.07787017 -0.03915679 -0.04161931
## 16: -0.10360589 -0.03609099 -0.05900800
## 17: -0.09946026 -0.04724158 -0.04168322
## 18: -0.10004450 -0.03897718 -0.06873387
## 19: -0.11532156 -0.03934745 -0.05511669
## 20: -0.13147207 -0.03905088 -0.07224963
## 21: -0.09212827 -0.03484349 -0.04928364
## 22: -0.09694948 -0.04184839 -0.04899644
## 23: -0.10305789 -0.04612572 -0.04907535
## 24: -0.10501988 -0.03812304 -0.07121563
## tBodyGyroJerk-mean()-X tBodyGyroJerk-mean()-Y tBodyGyroJerk-mean()-Z
## tBodyGyroJerk-std()-X tBodyGyroJerk-std()-Y tBodyGyroJerk-std()-Z
## 1: -0.2074219 -0.3044685 -0.4042555
## 2: -0.6147865 -0.6016967 -0.6063320
## 3: -0.4870273 -0.2388248 -0.2687615
## 4: -0.9917316 -0.9895181 -0.9879358
## 5: -0.9929451 -0.9951379 -0.9921085
## 6: -0.9186085 -0.9679072 -0.9577902
## 7: -0.3895498 -0.6341404 -0.4354927
## 8: -0.4648544 -0.6454913 -0.4675960
## 9: -0.2439406 -0.4693967 -0.2182663
## 10: -0.9897090 -0.9908896 -0.9855423
## 11: -0.9793240 -0.9834473 -0.9736101
## 12: -0.9932358 -0.9895675 -0.9880358
## 13: -0.3859230 -0.6390880 -0.5366641
## 14: -0.5072708 -0.7757741 -0.5734339
## 15: -0.2856832 -0.6809473 -0.3746054
## 16: -0.9725469 -0.9786359 -0.9737517
## 17: -0.9409376 -0.9684337 -0.9582930
## 18: -0.9803286 -0.9867627 -0.9833383
## 19: -0.4923411 -0.8074199 -0.6404541
## 20: -0.5336668 -0.8407228 -0.5562366
## 21: -0.3959955 -0.8168582 -0.3257801
## 22: -0.9698997 -0.9844414 -0.9688048
## 23: -0.9496339 -0.9760652 -0.9579820
## 24: -0.9751032 -0.9868556 -0.9839654
## tBodyGyroJerk-std()-X tBodyGyroJerk-std()-Y tBodyGyroJerk-std()-Z
## tBodyAccMag-mean() tBodyAccMag-std() tGravityAccMag-mean()
## 1: -0.13697118 -0.21968865 -0.13697118
## 2: -0.12992763 -0.32497093 -0.12992763
## 3: 0.02718829 0.01988435 0.02718829
## 4: -0.94853679 -0.92707842 -0.94853679
## 5: -0.98427821 -0.98194293 -0.98427821
## 6: -0.84192915 -0.79514486 -0.84192915
## 7: -0.29040759 -0.42254417 -0.29040759
## 8: -0.10732268 -0.20597705 -0.10732268
## 9: 0.08995112 0.21558633 0.08995112
## 10: -0.96789362 -0.95308144 -0.96789362
## 11: -0.96587518 -0.95787497 -0.96587518
## 12: -0.97743549 -0.97287391 -0.97743549
## 13: -0.25469033 -0.32842894 -0.25469033
## 14: -0.18401489 -0.33359743 -0.18401489
## 15: -0.06281261 -0.04113401 -0.06281261
## 16: -0.89538335 -0.87030170 -0.89538335
## 17: -0.92543082 -0.91514330 -0.92543082
## 18: -0.97279135 -0.96421818 -0.97279135
## 19: -0.31205057 -0.52767910 -0.31205057
## 20: -0.15370394 -0.21201230 -0.15370394
## 21: -0.04916167 -0.08195590 -0.04916167
## 22: -0.93569482 -0.91440784 -0.93569482
## 23: -0.90647805 -0.89097668 -0.90647805
## 24: -0.95455760 -0.93129222 -0.95455760
## tBodyAccMag-mean() tBodyAccMag-std() tGravityAccMag-mean()
## tGravityAccMag-std() tBodyAccJerkMag-mean() tBodyAccJerkMag-std()
## 1: -0.21968865 -0.141428809 -0.07447175
## 2: -0.32497093 -0.466503446 -0.47899162
## 3: 0.01988435 -0.089447481 -0.02578772
## 4: -0.92707842 -0.987364196 -0.98412002
## 5: -0.98194293 -0.992367791 -0.99309621
## 6: -0.79514486 -0.954396265 -0.92824563
## 7: -0.42254417 -0.281424154 -0.16415099
## 8: -0.20597705 -0.321268911 -0.21738939
## 9: 0.21558633 0.005655163 0.22961719
## 10: -0.95308144 -0.986774713 -0.98447587
## 11: -0.95787497 -0.980489077 -0.97667528
## 12: -0.97287391 -0.987741696 -0.98551808
## 13: -0.32842894 -0.280009317 -0.13991636
## 14: -0.33359743 -0.436901159 -0.43902059
## 15: -0.04113401 -0.205239247 -0.09263245
## 16: -0.87030170 -0.969080753 -0.96655008
## 17: -0.91514330 -0.959303840 -0.94877004
## 18: -0.96421818 -0.979484593 -0.97612130
## 19: -0.52767910 -0.366700880 -0.31691896
## 20: -0.21201230 -0.400922255 -0.43726148
## 21: -0.08195590 -0.228851414 -0.21685892
## 22: -0.91440784 -0.970132284 -0.96254911
## 23: -0.89097668 -0.963370738 -0.95815948
## 24: -0.93129222 -0.970095772 -0.96078643
## tGravityAccMag-std() tBodyAccJerkMag-mean() tBodyAccJerkMag-std()
## tBodyGyroMag-mean() tBodyGyroMag-std() tBodyGyroJerkMag-mean()
## 1: -0.16097955 -0.1869784 -0.2987037
## 2: -0.12673559 -0.1486193 -0.5948829
## 3: -0.07574125 -0.2257244 -0.2954638
## 4: -0.93089249 -0.9345318 -0.9919763
## 5: -0.97649379 -0.9786900 -0.9949668
## 6: -0.87475955 -0.8190102 -0.9634610
## 7: -0.44654909 -0.5530199 -0.5479120
## 8: -0.21971347 -0.3775322 -0.5728164
## 9: -0.16218859 -0.2748441 -0.4108727
## 10: -0.94603509 -0.9613136 -0.9910815
## 11: -0.96346634 -0.9539434 -0.9839519
## 12: -0.95001157 -0.9611641 -0.9917671
## 13: -0.46641175 -0.5615107 -0.5661352
## 14: -0.34732181 -0.4088867 -0.6588614
## 15: -0.21529450 -0.2457947 -0.5085676
## 16: -0.91935437 -0.9255181 -0.9779981
## 17: -0.89208935 -0.8821252 -0.9623393
## 18: -0.95156475 -0.9542751 -0.9867136
## 19: -0.49779220 -0.5531161 -0.6813040
## 20: -0.29977941 -0.5109741 -0.6869784
## 21: -0.34660629 -0.3805726 -0.5928430
## 22: -0.92606331 -0.9288983 -0.9804905
## 23: -0.90098210 -0.8851443 -0.9676141
## 24: -0.93023646 -0.9470318 -0.9850685
## tBodyGyroMag-mean() tBodyGyroMag-std() tBodyGyroJerkMag-mean()
## tBodyGyroJerkMag-std() fBodyAcc-mean()-X fBodyAcc-mean()-Y
## 1: -0.3253249 -0.20279431 0.089712726
## 2: -0.6485530 -0.40432178 -0.190976721
## 3: -0.3065106 0.03822918 0.001549908
## 4: -0.9883087 -0.97964124 -0.944084550
## 5: -0.9947332 -0.99524993 -0.977070848
## 6: -0.9358410 -0.93909905 -0.867065205
## 7: -0.5577982 -0.34604816 -0.021904810
## 8: -0.5972917 -0.26672093 0.009924459
## 9: -0.3431879 0.11284116 0.278345042
## 10: -0.9895949 -0.98580384 -0.957343498
## 11: -0.9772044 -0.98394674 -0.959871697
## 12: -0.9897181 -0.97672506 -0.979800878
## 13: -0.5673716 -0.31661401 -0.081302435
## 14: -0.7180280 -0.39200421 -0.078809416
## 15: -0.5839192 -0.04217069 -0.007700483
## 16: -0.9767727 -0.97015444 -0.891907751
## 17: -0.9576798 -0.96012341 -0.908075354
## 18: -0.9831393 -0.98066561 -0.961169983
## 19: -0.7301464 -0.42671945 -0.149399633
## 20: -0.7552705 -0.29448827 -0.117109161
## 21: -0.6370795 -0.07223923 -0.129606639
## 22: -0.9758067 -0.97746250 -0.905782932
## 23: -0.9642828 -0.97349755 -0.889549205
## 24: -0.9826982 -0.95880208 -0.938883374
## tBodyGyroJerkMag-std() fBodyAcc-mean()-X fBodyAcc-mean()-Y
## fBodyAcc-mean()-Z fBodyAcc-std()-X fBodyAcc-std()-Y fBodyAcc-std()-Z
## 1: -0.3315601 -0.31913472 0.056040007 -0.27968675
## 2: -0.4333497 -0.33742819 0.021769511 0.08595655
## 3: -0.2255745 0.02433084 -0.112963740 -0.29792789
## 4: -0.9591849 -0.97641231 -0.917275006 -0.93446956
## 5: -0.9852971 -0.99602835 -0.972293102 -0.97793726
## 6: -0.8826669 -0.92443743 -0.833625556 -0.81289156
## 7: -0.4538064 -0.45765138 -0.169219686 -0.45522215
## 8: -0.2810020 -0.32058241 0.084880279 -0.09454498
## 9: -0.1312908 0.01610462 0.171973973 -0.16203289
## 10: -0.9701622 -0.98736209 -0.950073754 -0.95686286
## 11: -0.9624712 -0.98905647 -0.957908842 -0.94643358
## 12: -0.9843810 -0.97324648 -0.981025106 -0.98479218
## 13: -0.4123741 -0.37927678 -0.124030832 -0.42299847
## 14: -0.5044945 -0.28533302 -0.008039875 -0.35079723
## 15: -0.4044524 -0.06544172 -0.109722354 -0.38972303
## 16: -0.9179879 -0.97160588 -0.849655658 -0.86432246
## 17: -0.9395077 -0.96993129 -0.892434349 -0.90480125
## 18: -0.9683321 -0.98369113 -0.964094604 -0.96327908
## 19: -0.6310055 -0.44723493 -0.101799451 -0.59419833
## 20: -0.5246557 -0.17321722 -0.101434446 -0.34510982
## 21: -0.4946835 0.03900983 -0.322531318 -0.51269430
## 22: -0.9517837 -0.98190819 -0.889467349 -0.92699932
## 23: -0.9316434 -0.97873764 -0.857380282 -0.88755432
## 24: -0.9675043 -0.95246488 -0.946380971 -0.96215445
## fBodyAcc-mean()-Z fBodyAcc-std()-X fBodyAcc-std()-Y fBodyAcc-std()-Z
## fBodyAccJerk-mean()-X fBodyAccJerk-mean()-Y fBodyAccJerk-mean()-Z
## 1: -0.17054696 -0.03522552 -0.4689992
## 2: -0.47987525 -0.41344459 -0.6854744
## 3: -0.02766387 -0.12866716 -0.2883347
## 4: -0.98659702 -0.98157947 -0.9860531
## 5: -0.99463080 -0.98541870 -0.9907522
## 6: -0.95707388 -0.92246261 -0.9480609
## 7: -0.30461532 -0.07876408 -0.5549567
## 8: -0.25863944 -0.18784213 -0.5227281
## 9: 0.13812068 0.09620916 -0.2714987
## 10: -0.98784879 -0.97713970 -0.9851291
## 11: -0.98097324 -0.97085134 -0.9797752
## 12: -0.98581363 -0.98276825 -0.9861971
## 13: -0.30469444 -0.14050859 -0.5141373
## 14: -0.47843431 -0.28377255 -0.6773145
## 15: -0.09067071 -0.13593854 -0.5290595
## 16: -0.97495036 -0.95417015 -0.9708457
## 17: -0.95766686 -0.94349797 -0.9691749
## 18: -0.98051320 -0.96875211 -0.9791223
## 19: -0.35888341 -0.27955339 -0.7289916
## 20: -0.41830465 -0.29780519 -0.6901069
## 21: -0.16163291 -0.17294163 -0.5839174
## 22: -0.97684571 -0.94429839 -0.9751549
## 23: -0.97231089 -0.93762424 -0.9686484
## 24: -0.97854246 -0.94396999 -0.9753833
## fBodyAccJerk-mean()-X fBodyAccJerk-mean()-Y fBodyAccJerk-mean()-Z
## fBodyAccJerk-std()-X fBodyAccJerk-std()-Y fBodyAccJerk-std()-Z
## 1: -0.13358661 0.106739857 -0.5347134
## 2: -0.46190703 -0.381777065 -0.7260402
## 3: -0.08632790 -0.134580009 -0.4017215
## 4: -0.98749299 -0.982513910 -0.9883392
## 5: -0.99507376 -0.987018227 -0.9923498
## 6: -0.96416071 -0.932217870 -0.9605870
## 7: -0.31431306 -0.015332952 -0.6158982
## 8: -0.36541544 -0.243554147 -0.6250910
## 9: 0.04995906 0.080833349 -0.4082274
## 10: -0.98945911 -0.980804228 -0.9885708
## 11: -0.98300792 -0.973520241 -0.9845999
## 12: -0.98725026 -0.984987393 -0.9893454
## 13: -0.29659663 -0.005614988 -0.5435291
## 14: -0.48644651 -0.268191524 -0.7387059
## 15: -0.16544290 -0.147728240 -0.6135251
## 16: -0.97628353 -0.956461757 -0.9771596
## 17: -0.96057092 -0.943948547 -0.9755959
## 18: -0.98312262 -0.971044013 -0.9837119
## 19: -0.29732607 -0.209900006 -0.7723591
## 20: -0.39676258 -0.314525031 -0.7627722
## 21: -0.20825006 -0.177202094 -0.6688673
## 22: -0.97877691 -0.949293158 -0.9816994
## 23: -0.97570672 -0.944075309 -0.9762295
## 24: -0.98007929 -0.944366882 -0.9802612
## fBodyAccJerk-std()-X fBodyAccJerk-std()-Y fBodyAccJerk-std()-Z
## fBodyGyro-mean()-X fBodyGyro-mean()-Y fBodyGyro-mean()-Z
## 1: -0.3390322 -0.10305942 -0.25594094
## 2: -0.4926117 -0.31947461 -0.45359721
## 3: -0.3524496 -0.05570225 -0.03186943
## 4: -0.9761615 -0.97583859 -0.95131554
## 5: -0.9863868 -0.98898446 -0.98077312
## 6: -0.8502492 -0.95219149 -0.90930272
## 7: -0.4297135 -0.55477211 -0.39665991
## 8: -0.3316436 -0.48808612 -0.24860112
## 9: -0.1457760 -0.36191382 -0.08749447
## 10: -0.9826214 -0.98210092 -0.95981482
## 11: -0.9670371 -0.97257615 -0.96062770
## 12: -0.9864311 -0.98332164 -0.96267189
## 13: -0.4378458 -0.56152627 -0.41812622
## 14: -0.3782167 -0.63729351 -0.43150336
## 15: -0.1290666 -0.54269416 -0.30286646
## 16: -0.9575506 -0.95617355 -0.93496796
## 17: -0.9012823 -0.93771116 -0.91617254
## 18: -0.9701673 -0.97809968 -0.96234196
## 19: -0.3733845 -0.68846006 -0.60138113
## 20: -0.3710690 -0.68431020 -0.35076574
## 21: -0.2402989 -0.71754584 -0.31830648
## 22: -0.9605896 -0.96758365 -0.93377689
## 23: -0.9054642 -0.95599295 -0.91528096
## 24: -0.9672037 -0.97218784 -0.96147926
## fBodyGyro-mean()-X fBodyGyro-mean()-Y fBodyGyro-mean()-Z
## fBodyGyro-std()-X fBodyGyro-std()-Y fBodyGyro-std()-Z
## 1: -0.5166919 -0.03350816 -0.4365622
## 2: -0.5658925 0.15153891 -0.5717078
## 3: -0.4954225 -0.18141473 -0.2384436
## 4: -0.9779042 -0.96234504 -0.9439178
## 5: -0.9874971 -0.98710773 -0.9823453
## 6: -0.8822965 -0.95123205 -0.9165825
## 7: -0.6040530 -0.53304695 -0.5598566
## 8: -0.4763588 -0.45975849 -0.2180725
## 9: -0.3794367 -0.45873275 -0.4229877
## 10: -0.9868085 -0.97735619 -0.9635227
## 11: -0.9749881 -0.97103605 -0.9697543
## 12: -0.9888607 -0.98191062 -0.9631742
## 13: -0.6151214 -0.56888867 -0.5458964
## 14: -0.4848210 -0.55604595 -0.5610976
## 15: -0.3086303 -0.55309454 -0.5481643
## 16: -0.9680131 -0.93960999 -0.9306332
## 17: -0.9019857 -0.92312594 -0.9197438
## 18: -0.9759864 -0.97703250 -0.9672569
## 19: -0.5426468 -0.65465777 -0.7164585
## 20: -0.4835487 -0.48982428 -0.4245335
## 21: -0.4149190 -0.69151837 -0.6216585
## 22: -0.9733331 -0.95412042 -0.9328684
## 23: -0.9124648 -0.94582584 -0.9166516
## 24: -0.9750947 -0.95618250 -0.9658075
## fBodyGyro-std()-X fBodyGyro-std()-Y fBodyGyro-std()-Z
## fBodyAccMag-mean() fBodyAccMag-std() fBodyBodyAccJerkMag-mean()
## 1: -0.12862345 -0.39803259 -0.05711940
## 2: -0.35239594 -0.41626010 -0.44265216
## 3: 0.09658453 -0.18653030 0.02621849
## 4: -0.94778292 -0.92844480 -0.98526213
## 5: -0.98535636 -0.98231380 -0.99254248
## 6: -0.86176765 -0.79830094 -0.93330036
## 7: -0.32428943 -0.57710521 -0.16906435
## 8: -0.14531854 -0.36672824 -0.18951114
## 9: 0.29342483 -0.02147879 0.22224741
## 10: -0.96127375 -0.95557560 -0.98387470
## 11: -0.96405217 -0.96051938 -0.97706530
## 12: -0.97511020 -0.97512139 -0.98537411
## 13: -0.29003154 -0.45637308 -0.18676452
## 14: -0.31586608 -0.44799437 -0.41292090
## 15: 0.02894132 -0.23384942 -0.04947798
## 16: -0.90418573 -0.87462659 -0.96588889
## 17: -0.92696893 -0.92183608 -0.94862747
## 18: -0.96552428 -0.96835022 -0.97594960
## 19: -0.45080456 -0.65117263 -0.31858781
## 20: -0.27682550 -0.30100590 -0.39740629
## 21: -0.01907434 -0.26364403 -0.17529529
## 22: -0.92900209 -0.91981571 -0.96250073
## 23: -0.91761401 -0.89534004 -0.95613928
## 24: -0.93938970 -0.93718798 -0.96228713
## fBodyAccMag-mean() fBodyAccMag-std() fBodyBodyAccJerkMag-mean()
## fBodyBodyAccJerkMag-std() fBodyBodyGyroMag-mean()
## 1: -0.10349240 -0.1992526
## 2: -0.53305985 -0.3259615
## 3: -0.10405226 -0.1857203
## 4: -0.98160618 -0.9584356
## 5: -0.99253600 -0.9846176
## 6: -0.92180398 -0.8621902
## 7: -0.16409197 -0.5307048
## 8: -0.26042384 -0.4506122
## 9: 0.22748073 -0.3208385
## 10: -0.98412419 -0.9718406
## 11: -0.97516046 -0.9617759
## 12: -0.98456849 -0.9721130
## 13: -0.08985199 -0.5697558
## 14: -0.48060920 -0.5142116
## 15: -0.15910229 -0.3323766
## 16: -0.96656885 -0.9466649
## 17: -0.94820681 -0.9136824
## 18: -0.97530538 -0.9645867
## 19: -0.32045870 -0.6092856
## 20: -0.49732409 -0.5757941
## 21: -0.28042678 -0.4292134
## 22: -0.96158452 -0.9487698
## 23: -0.96003250 -0.9142092
## 24: -0.95803712 -0.9615567
## fBodyBodyAccJerkMag-std() fBodyBodyGyroMag-mean()
## fBodyBodyGyroMag-std() fBodyBodyGyroJerkMag-mean()
## 1: -0.3210180 -0.3193086
## 2: -0.1829855 -0.6346651
## 3: -0.3983504 -0.2819634
## 4: -0.9321984 -0.9897975
## 5: -0.9784661 -0.9948154
## 6: -0.8243194 -0.9423669
## 7: -0.6517928 -0.5832493
## 8: -0.4386204 -0.6007985
## 9: -0.3725768 -0.3801753
## 10: -0.9613857 -0.9898620
## 11: -0.9567887 -0.9778498
## 12: -0.9610984 -0.9902487
## 13: -0.6326433 -0.6077516
## 14: -0.4451818 -0.7168778
## 15: -0.3224408 -0.5762772
## 16: -0.9254496 -0.9778981
## 17: -0.8834397 -0.9603317
## 18: -0.9554419 -0.9842783
## 19: -0.5939372 -0.7243274
## 20: -0.5524896 -0.7407492
## 21: -0.4576741 -0.6217525
## 22: -0.9288506 -0.9765478
## 23: -0.8871944 -0.9644711
## 24: -0.9471003 -0.9836091
## fBodyBodyGyroMag-std() fBodyBodyGyroJerkMag-mean()
## fBodyBodyGyroJerkMag-std()
## 1: -0.3816019
## 2: -0.6939305
## 3: -0.3919199
## 4: -0.9870496
## 5: -0.9946711
## 6: -0.9326607
## 7: -0.5581046
## 8: -0.6218202
## 9: -0.3436990
## 10: -0.9896329
## 11: -0.9777543
## 12: -0.9894927
## 13: -0.5490870
## 14: -0.7400334
## 15: -0.6249108
## 16: -0.9766898
## 17: -0.9571215
## 18: -0.9825682
## 19: -0.7577681
## 20: -0.7942095
## 21: -0.6854709
## 22: -0.9762618
## 23: -0.9664302
## 24: -0.9825436
## fBodyBodyGyroJerkMag-std()