Coursera-cleaning Data Project Krishna Wednesday, August 20, 2014 ##Input the X_Train and X_Test Files X_Train<-read.table("C:/Users/srikrish/Downloads/UCI HAR Dataset/train/X_train.txt",sep="",col.names=(1:561),fill=FALSE,strip.white=TRUE) X_Test<-read.table("C:/Users/srikrish/Downloads/UCI HAR Dataset/test/X_test.txt",sep="",col.names=(1:561),fill=FALSE,strip.white=TRUE) ##Input the Y_Train and Y_Test Files Y_Train<-read.table("C:/Users/srikrish/Downloads/UCI HAR Dataset/train/Y_train.txt",sep="",col.names=("Activity_Labels"),fill=FALSE,strip.white=TRUE) Y_Test<-read.table("C:/Users/srikrish/Downloads/UCI HAR Dataset/test/Y_test.txt",sep="",col.names=("Activity_Labels"),fill=FALSE,strip.white=TRUE) ##Input the Subject Train and Test Files Subject_Train<-read.table("C:/Users/srikrish/Downloads/UCI HAR Dataset/train/subject_train.txt",sep="",col.names=("Subjects"),fill=FALSE,strip.white=TRUE) Subject_Test<-read.table("C:/Users/srikrish/Downloads/UCI HAR Dataset/test/subject_test.txt",sep="",col.names=("Subjects"),fill=FALSE,strip.white=TRUE)
##Appending both Subject_Train and Y_Train with X_Train Dataset Train<-cbind(Subject_Train,Y_Train,X_Train) Test<-cbind(Subject_Test,Y_Test,X_Test)
##Merging the Train and Test Datasets Final<-rbind(Train,Test) Final<-Final[order(Final$Subjects,Final$Activity_Labels),]
dim(Final)
##Extract only the Mean and Standard Deviation for Each Measurement variables=c(1:2,3:8,43:48,83:88,123:128,163:168,203:204,216,217,229,230,242,243,255,256,268:273,347:352,426:431,505:506,518,519,531,532,544,545) Final_mean_sdv<-Final[,variables]
##Naming the Activity Labels Final_mean_sdv$Activity_Labels<-factor(Final_mean_sdv$Activity_Labels,levels=c(1,2,3,4,5,6),labels=c("Walking","Walking_Upstairs","Walking_Downstairs","Sitting","Standing","Laying"))
##Label the Dataset with Descriptive Variable Names
names(Final_mean_sdv)<-c("Subjects","Activity_Labels","tBodyAcc-meanX","tBodyAcc-meanY","tBodyAcc-meanZ","tBodyAcc-stdX","tBodyAcc-stdY","tBodyAcc-stdZ","tGravityAcc-meanX","tGravityAcc-meanY","tGravityAcc-meanZ","tGravityAcc-stdX","tGravityAcc-stdY","tGravityAcc-stdZ","tBodyAccJerk-meanX","tBodyAccJerk-meanY","tBodyAccJerk-meanZ","tBodyAccJerk-stdX","tBodyAccJerk-stdY","tBodyAccJerk-stdZ","tBodyGyro-meanX","tBodyGyro-meanY","tBodyGyro-meanZ","tBodyGyro-stdX","tBodyGyro-stdY","tBodyGyro-stdZ","tBodyGyroJerk-meanX","tBodyGyroJerk-meanY","tBodyGyroJerk-meanZ","tBodyGyroJerk-stdX","tBodyGyroJerk-stdY","tBodyGyroJerk-stdZ","tBodyAccMag-mean","tBodyAccMag-std","tGravityAccMag-mean","tGravityAccMag-std","tBodyAccJerkMag-mean","tBodyAccJerkMag-std","tBodyGyroMag-mean","tBodyGyroMag-std","tBodyGyroJerkMag-mean","tBodyGyroJerkMag-std","fBodyAcc-meanX","fBodyAcc-meanY","fBodyAcc-meanZ","fBodyAcc-stdX","fBodyAcc-stdY","fBodyAcc-stdZ","fBodyAccJerk-meanX","fBodyAccJerk-meanY","fBodyAccJerk-meanZ","fBodyAccJerk-stdX","fBodyAccJerk-stdY","fBodyAccJerk-stdZ","fBodyGyro-meanX","fBodyGyro-meanY","fBodyGyro-meanZ","fBodyGyro-stdX","fBodyGyro-stdY","fBodyGyro-stdZ","fBodyAccMag-mean","fBodyAccMag-std","fBodyBodyAccJerkMag-mean","fBodyBodyAccJerkMag-std","fBodyBodyGyroMag-mean","fBodyBodyGyroMag-std","fBodyBodyGyroJerkMag-mean","fBodyBodyGyroJerkMag-std")
##Second Dataset with Average of Each variable with Each Activity and Each Subject dim(Final_mean_sdv)
attach(Final_mean_sdv) Aggreg_Final_mean_sdv<-aggregate(Final_mean_sdv,by=list(Subjects,Activity_Labels),FUN=mean,na.rm=TRUE) detach(Final_mean_sdv) Aggreg_Final_mean_sdv$Group.1->Aggreg_Final_mean_sdv$Subjects Aggreg_Final_mean_sdv$Group.2->Aggreg_Final_mean_sdv$Activity_Labels Aggreg_Final_mean_sdv$Group.1<-NULL Aggreg_Final_mean_sdv$Group.2<-NULL
##Editing Text Variables tolower(names(Aggreg_Final_mean_sdv)) ##Lower case of all the variable names ##Final Data Set for Submission for Question No. 5 head(Aggreg_Final_mean_sdv) write.table(Aggreg_Final_mean_sdv,"Final_Submission.txt",sep=c(' ', ' ', '\n'),row.name=FALSE)