Reading the activitie file activities <- read.table(" UCI HAR Dataset/activity_labels.txt" activities [,2 ] <- as.character(activities [,2 ])
head(activities )## V1 V2
## 1 1 WALKING
## 2 2 WALKING_UPSTAIRS
## 3 3 WALKING_DOWNSTAIRS
## 4 4 SITTING
## 5 5 STANDING
## 6 6 LAYING
Reading the features file and extracting mean and std variables features <- read.table(" UCI HAR Dataset/features.txt" features [,2 ] <- as.character(features [,2 ])
extractredFeatures <- grep(" .*mean.*|.*std.*" features [,2 ])
extractredFeatures.names <- features [extractredFeatures ,2 ]
extractredFeatures.names <- gsub(' -mean' ' Mean' extractredFeatures.names )
extractredFeatures.names <- gsub(' -std' ' Std' extractredFeatures.names )
extractredFeatures.names <- gsub(' [-()]' ' ' extractredFeatures.names )
extractredFeatures.names ## [1] "tBodyAccMeanX" "tBodyAccMeanY"
## [3] "tBodyAccMeanZ" "tBodyAccStdX"
## [5] "tBodyAccStdY" "tBodyAccStdZ"
## [7] "tGravityAccMeanX" "tGravityAccMeanY"
## [9] "tGravityAccMeanZ" "tGravityAccStdX"
## [11] "tGravityAccStdY" "tGravityAccStdZ"
## [13] "tBodyAccJerkMeanX" "tBodyAccJerkMeanY"
## [15] "tBodyAccJerkMeanZ" "tBodyAccJerkStdX"
## [17] "tBodyAccJerkStdY" "tBodyAccJerkStdZ"
## [19] "tBodyGyroMeanX" "tBodyGyroMeanY"
## [21] "tBodyGyroMeanZ" "tBodyGyroStdX"
## [23] "tBodyGyroStdY" "tBodyGyroStdZ"
## [25] "tBodyGyroJerkMeanX" "tBodyGyroJerkMeanY"
## [27] "tBodyGyroJerkMeanZ" "tBodyGyroJerkStdX"
## [29] "tBodyGyroJerkStdY" "tBodyGyroJerkStdZ"
## [31] "tBodyAccMagMean" "tBodyAccMagStd"
## [33] "tGravityAccMagMean" "tGravityAccMagStd"
## [35] "tBodyAccJerkMagMean" "tBodyAccJerkMagStd"
## [37] "tBodyGyroMagMean" "tBodyGyroMagStd"
## [39] "tBodyGyroJerkMagMean" "tBodyGyroJerkMagStd"
## [41] "fBodyAccMeanX" "fBodyAccMeanY"
## [43] "fBodyAccMeanZ" "fBodyAccStdX"
## [45] "fBodyAccStdY" "fBodyAccStdZ"
## [47] "fBodyAccMeanFreqX" "fBodyAccMeanFreqY"
## [49] "fBodyAccMeanFreqZ" "fBodyAccJerkMeanX"
## [51] "fBodyAccJerkMeanY" "fBodyAccJerkMeanZ"
## [53] "fBodyAccJerkStdX" "fBodyAccJerkStdY"
## [55] "fBodyAccJerkStdZ" "fBodyAccJerkMeanFreqX"
## [57] "fBodyAccJerkMeanFreqY" "fBodyAccJerkMeanFreqZ"
## [59] "fBodyGyroMeanX" "fBodyGyroMeanY"
## [61] "fBodyGyroMeanZ" "fBodyGyroStdX"
## [63] "fBodyGyroStdY" "fBodyGyroStdZ"
## [65] "fBodyGyroMeanFreqX" "fBodyGyroMeanFreqY"
## [67] "fBodyGyroMeanFreqZ" "fBodyAccMagMean"
## [69] "fBodyAccMagStd" "fBodyAccMagMeanFreq"
## [71] "fBodyBodyAccJerkMagMean" "fBodyBodyAccJerkMagStd"
## [73] "fBodyBodyAccJerkMagMeanFreq" "fBodyBodyGyroMagMean"
## [75] "fBodyBodyGyroMagStd" "fBodyBodyGyroMagMeanFreq"
## [77] "fBodyBodyGyroJerkMagMean" "fBodyBodyGyroJerkMagStd"
## [79] "fBodyBodyGyroJerkMagMeanFreq"
Loading, Merging data sets and labeling the variables. Using descriptive activity names in resulting data set library(plyr )
traindata <- read.table(" UCI HAR Dataset/train/X_train.txt" extractredFeatures ]
trainActivities <- read.table(" UCI HAR Dataset/train/Y_train.txt" trainSubjects <- read.table(" UCI HAR Dataset/train/subject_train.txt" traindataset <- cbind(trainSubjects , trainActivities , traindata )
testdata <- read.table(" UCI HAR Dataset/test/X_test.txt" extractredFeatures ]
testActivities <- read.table(" UCI HAR Dataset/test/Y_test.txt" testSubjects <- read.table(" UCI HAR Dataset/test/subject_test.txt" testdataset <- cbind(testSubjects , testActivities , testdata )
finaldata <- rbind(traindataset , testdataset )
colnames(finaldata ) <- c(" subject" " activity" extractredFeatures.names )
finaldata $ activity <- mapvalues(finaldata $ activity , from = as.character(activities [,1 ]), to = as.character(activities [,2 ]))
finaldata $ activity <- as.factor(finaldata $ activity )
head(finaldata ) ## subject activity tBodyAccMeanX tBodyAccMeanY tBodyAccMeanZ tBodyAccStdX
## 1 1 STANDING 0.2885845 -0.02029417 -0.1329051 -0.9952786
## 2 1 STANDING 0.2784188 -0.01641057 -0.1235202 -0.9982453
## 3 1 STANDING 0.2796531 -0.01946716 -0.1134617 -0.9953796
## 4 1 STANDING 0.2791739 -0.02620065 -0.1232826 -0.9960915
## 5 1 STANDING 0.2766288 -0.01656965 -0.1153619 -0.9981386
## 6 1 STANDING 0.2771988 -0.01009785 -0.1051373 -0.9973350
## tBodyAccStdY tBodyAccStdZ tGravityAccMeanX tGravityAccMeanY
## 1 -0.9831106 -0.9135264 0.9633961 -0.1408397
## 2 -0.9753002 -0.9603220 0.9665611 -0.1415513
## 3 -0.9671870 -0.9789440 0.9668781 -0.1420098
## 4 -0.9834027 -0.9906751 0.9676152 -0.1439765
## 5 -0.9808173 -0.9904816 0.9682244 -0.1487502
## 6 -0.9904868 -0.9954200 0.9679482 -0.1482100
## tGravityAccMeanZ tGravityAccStdX tGravityAccStdY tGravityAccStdZ
## 1 0.11537494 -0.9852497 -0.9817084 -0.8776250
## 2 0.10937881 -0.9974113 -0.9894474 -0.9316387
## 3 0.10188392 -0.9995740 -0.9928658 -0.9929172
## 4 0.09985014 -0.9966456 -0.9813928 -0.9784764
## 5 0.09448590 -0.9984293 -0.9880982 -0.9787449
## 6 0.09190972 -0.9989793 -0.9867539 -0.9973064
## tBodyAccJerkMeanX tBodyAccJerkMeanY tBodyAccJerkMeanZ tBodyAccJerkStdX
## 1 0.07799634 0.005000803 -0.067830808 -0.9935191
## 2 0.07400671 0.005771104 0.029376633 -0.9955481
## 3 0.07363596 0.003104037 -0.009045631 -0.9907428
## 4 0.07732061 0.020057642 -0.009864772 -0.9926974
## 5 0.07344436 0.019121574 0.016779979 -0.9964202
## 6 0.07793244 0.018684046 0.009344434 -0.9948136
## tBodyAccJerkStdY tBodyAccJerkStdZ tBodyGyroMeanX tBodyGyroMeanY
## 1 -0.9883600 -0.9935750 -0.006100849 -0.03136479
## 2 -0.9810636 -0.9918457 -0.016111620 -0.08389378
## 3 -0.9809556 -0.9896866 -0.031698294 -0.10233542
## 4 -0.9875527 -0.9934976 -0.043409983 -0.09138618
## 5 -0.9883587 -0.9924549 -0.033960416 -0.07470803
## 6 -0.9887145 -0.9922663 -0.028775508 -0.07039311
## tBodyGyroMeanZ tBodyGyroStdX tBodyGyroStdY tBodyGyroStdZ
## 1 0.10772540 -0.9853103 -0.9766234 -0.9922053
## 2 0.10058429 -0.9831200 -0.9890458 -0.9891212
## 3 0.09612688 -0.9762921 -0.9935518 -0.9863787
## 4 0.08553770 -0.9913848 -0.9924073 -0.9875542
## 5 0.07739203 -0.9851836 -0.9923781 -0.9874019
## 6 0.07901214 -0.9851808 -0.9921175 -0.9830768
## tBodyGyroJerkMeanX tBodyGyroJerkMeanY tBodyGyroJerkMeanZ
## 1 -0.09916740 -0.05551737 -0.06198580
## 2 -0.11050283 -0.04481873 -0.05924282
## 3 -0.10848567 -0.04241031 -0.05582883
## 4 -0.09116989 -0.03633262 -0.06046466
## 5 -0.09077010 -0.03763253 -0.05828932
## 6 -0.09424758 -0.04335526 -0.04193600
## tBodyGyroJerkStdX tBodyGyroJerkStdY tBodyGyroJerkStdZ tBodyAccMagMean
## 1 -0.9921107 -0.9925193 -0.9920553 -0.9594339
## 2 -0.9898726 -0.9972926 -0.9938510 -0.9792892
## 3 -0.9884618 -0.9956321 -0.9915318 -0.9837031
## 4 -0.9911194 -0.9966410 -0.9933289 -0.9865418
## 5 -0.9913545 -0.9964730 -0.9945110 -0.9928271
## 6 -0.9916216 -0.9960147 -0.9930906 -0.9942950
## tBodyAccMagStd tGravityAccMagMean tGravityAccMagStd tBodyAccJerkMagMean
## 1 -0.9505515 -0.9594339 -0.9505515 -0.9933059
## 2 -0.9760571 -0.9792892 -0.9760571 -0.9912535
## 3 -0.9880196 -0.9837031 -0.9880196 -0.9885313
## 4 -0.9864213 -0.9865418 -0.9864213 -0.9930780
## 5 -0.9912754 -0.9928271 -0.9912754 -0.9934800
## 6 -0.9952490 -0.9942950 -0.9952490 -0.9930177
## tBodyAccJerkMagStd tBodyGyroMagMean tBodyGyroMagStd tBodyGyroJerkMagMean
## 1 -0.9943364 -0.9689591 -0.9643352 -0.9942478
## 2 -0.9916944 -0.9806831 -0.9837542 -0.9951232
## 3 -0.9903969 -0.9763171 -0.9860515 -0.9934032
## 4 -0.9933808 -0.9820599 -0.9873511 -0.9955022
## 5 -0.9958537 -0.9852037 -0.9890626 -0.9958076
## 6 -0.9954243 -0.9858944 -0.9864403 -0.9952748
## tBodyGyroJerkMagStd fBodyAccMeanX fBodyAccMeanY fBodyAccMeanZ
## 1 -0.9913676 -0.9947832 -0.9829841 -0.9392687
## 2 -0.9961016 -0.9974507 -0.9768517 -0.9735227
## 3 -0.9950910 -0.9935941 -0.9725115 -0.9833040
## 4 -0.9952666 -0.9954906 -0.9835697 -0.9910798
## 5 -0.9952580 -0.9972859 -0.9823010 -0.9883694
## 6 -0.9952050 -0.9966567 -0.9869395 -0.9927386
## fBodyAccStdX fBodyAccStdY fBodyAccStdZ fBodyAccMeanFreqX
## 1 -0.9954217 -0.9831330 -0.9061650 0.25248290
## 2 -0.9986803 -0.9749298 -0.9554381 0.27130855
## 3 -0.9963128 -0.9655059 -0.9770493 0.12453124
## 4 -0.9963121 -0.9832444 -0.9902291 0.02904438
## 5 -0.9986065 -0.9801295 -0.9919150 0.18108977
## 6 -0.9976438 -0.9922637 -0.9970459 0.15738377
## fBodyAccMeanFreqY fBodyAccMeanFreqZ fBodyAccJerkMeanX fBodyAccJerkMeanY
## 1 0.13183575 -0.05205025 -0.9923325 -0.9871699
## 2 0.04286364 -0.01430976 -0.9950322 -0.9813115
## 3 -0.06461056 0.08267692 -0.9909937 -0.9816423
## 4 0.08030227 0.18569468 -0.9944466 -0.9887272
## 5 0.05798789 0.55978632 -0.9962920 -0.9887900
## 6 0.31883523 0.60559943 -0.9948507 -0.9882443
## fBodyAccJerkMeanZ fBodyAccJerkStdX fBodyAccJerkStdY fBodyAccJerkStdZ
## 1 -0.9896961 -0.9958207 -0.9909363 -0.9970517
## 2 -0.9897398 -0.9966523 -0.9820839 -0.9926268
## 3 -0.9875663 -0.9912488 -0.9814148 -0.9904159
## 4 -0.9913542 -0.9913783 -0.9869269 -0.9943908
## 5 -0.9906244 -0.9969025 -0.9886067 -0.9929065
## 6 -0.9901575 -0.9952180 -0.9901788 -0.9930667
## fBodyAccJerkMeanFreqX fBodyAccJerkMeanFreqY fBodyAccJerkMeanFreqZ
## 1 0.87038451 0.21069700 0.26370789
## 2 0.60851352 -0.05367561 0.06314827
## 3 0.11543400 -0.19343634 0.03825433
## 4 0.03579805 -0.09303585 0.16809523
## 5 0.27335020 0.07913538 0.29238418
## 6 0.32883589 0.05477140 0.32094497
## fBodyGyroMeanX fBodyGyroMeanY fBodyGyroMeanZ fBodyGyroStdX fBodyGyroStdY
## 1 -0.9865744 -0.9817615 -0.9895148 -0.9850326 -0.9738861
## 2 -0.9773867 -0.9925300 -0.9896058 -0.9849043 -0.9871681
## 3 -0.9754332 -0.9937147 -0.9867557 -0.9766422 -0.9933990
## 4 -0.9871096 -0.9936015 -0.9871913 -0.9928104 -0.9916460
## 5 -0.9824465 -0.9929838 -0.9886664 -0.9859818 -0.9919558
## 6 -0.9848902 -0.9927862 -0.9807784 -0.9852871 -0.9916595
## fBodyGyroStdZ fBodyGyroMeanFreqX fBodyGyroMeanFreqY fBodyGyroMeanFreqZ
## 1 -0.9940349 -0.25754888 0.09794711 0.54715105
## 2 -0.9897847 -0.04816744 -0.40160791 -0.06817833
## 3 -0.9873282 -0.21668507 -0.01726417 -0.11072029
## 4 -0.9886776 0.21686246 -0.13524536 -0.04972798
## 5 -0.9879443 -0.15334258 -0.08840273 -0.16223039
## 6 -0.9853661 -0.36303968 -0.13323831 0.19483324
## fBodyAccMagMean fBodyAccMagStd fBodyAccMagMeanFreq
## 1 -0.9521547 -0.9561340 -0.08843612
## 2 -0.9808566 -0.9758658 -0.04414989
## 3 -0.9877948 -0.9890155 0.25789914
## 4 -0.9875187 -0.9867420 0.07358150
## 5 -0.9935909 -0.9900635 0.39431033
## 6 -0.9948360 -0.9952833 0.43796212
## fBodyBodyAccJerkMagMean fBodyBodyAccJerkMagStd
## 1 -0.9937257 -0.9937550
## 2 -0.9903355 -0.9919603
## 3 -0.9892801 -0.9908667
## 4 -0.9927689 -0.9916998
## 5 -0.9955228 -0.9943890
## 6 -0.9947329 -0.9951562
## fBodyBodyAccJerkMagMeanFreq fBodyBodyGyroMagMean fBodyBodyGyroMagStd
## 1 0.3469885 -0.9801349 -0.9613094
## 2 0.5320605 -0.9882956 -0.9833219
## 3 0.6607950 -0.9892548 -0.9860277
## 4 0.6789213 -0.9894128 -0.9878358
## 5 0.5590577 -0.9914330 -0.9890594
## 6 0.2469096 -0.9905000 -0.9858609
## fBodyBodyGyroMagMeanFreq fBodyBodyGyroJerkMagMean
## 1 -0.1289889 -0.9919904
## 2 -0.2719585 -0.9958539
## 3 -0.2127279 -0.9950305
## 4 -0.0356842 -0.9952207
## 5 -0.2735820 -0.9950928
## 6 -0.2973291 -0.9951433
## fBodyBodyGyroJerkMagStd fBodyBodyGyroJerkMagMeanFreq
## 1 -0.9906975 -0.07432303
## 2 -0.9963995 0.15807454
## 3 -0.9951274 0.41450281
## 4 -0.9952369 0.40457253
## 5 -0.9954648 0.08775301
## 6 -0.9952387 0.01995331
Averaging data for subject, activity and variable into tidy data set library(reshape2 )
library(dplyr ) ##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:plyr':
##
## arrange, count, desc, failwith, id, mutate, rename, summarise,
## summarize
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
finaldata.melted <- melt(finaldata , id = c(" subject" " activity" groupeddata <- group_by(finaldata.melted , subject ,activity ,variable )
summarydata <- summarize(groupeddata , avg = mean(value , na.rm = T ))
head(summarydata )## # A tibble: 6 x 4
## # Groups: subject, activity [1]
## subject activity variable avg
## <int> <fct> <fct> <dbl>
## 1 1 LAYING tBodyAccMeanX 0.222
## 2 1 LAYING tBodyAccMeanY -0.0405
## 3 1 LAYING tBodyAccMeanZ -0.113
## 4 1 LAYING tBodyAccStdX -0.928
## 5 1 LAYING tBodyAccStdY -0.837
## 6 1 LAYING tBodyAccStdZ -0.826