##import some requested module library(dplyr) library(reshape2)

##The X Y subject data from file ##I have save the file to ./data/Dataset ##Because the file's name is too long >_< x_test <- read.table("./data/Dataset/test/X_test.txt") y_test <- read.table("./data/Dataset/test/y_test.txt") x_train <- read.table("./data/Dataset/train/X_train.txt") y_train <- read.table("./data/Dataset/train/y_train.txt") subject_test <- read.table("./data/Dataset/test/subject_test.txt") subject_train <- read.table("./data/Dataset/train/subject_train.txt") activity_label <- read.table("./data/Dataset/activity_labels.txt")

##Get the Name and Combin the test and train features <- read.table("./data/Dataset/features.txt") allx <- rbind(x_test,x_train) names(allx) <- features[,2]

##Merges the label and ##Uses descriptive activity names to name the activities in the data set alllabel <- rbind(y_test,y_train) alllabel$V2 <- activity_label[alllabel$V1,"V2"]

##Extracts only the measurements on the mean and standard deviation for each measurement. all <- allx[,grep("mean\(\)|std\(\)",names(allx))]

##Appropriately labels the data set with descriptive variable names. names(all)<-gsub("std\(\)", "Std", names(all)) names(all)<-gsub("mean\(\)", "Mean", names(all)) names(all)<-gsub("^t", "Time", names(all)) names(all)<-gsub("^f", "Frequency", names(all)) names(all)<-gsub("Acc", "Accelerometer", names(all)) names(all)<-gsub("Gyro", "Gyroscope", names(all)) names(all)<-gsub("Mag", "Magnitude", names(all)) names(all)<-gsub("BodyBody", "Body", names(all)) names(all)<-gsub("-","",names(all))

##Merge all the data all$activity <- alllabel$V2 all$subject <- rbind(subject_test,subject_train)$V1

##creates a second, independent tidy data set with the average of #each variable for each activity and each subject. melted <- melt(all,id=c("activity","subject")) ans <- dcast(melted,subject+activity ~ variable,mean)

##Save to the file write.table(ans, file = "tidydata.txt", row.name=FALSE)