run_analysis.R

library(dplyr)

#######################################library###############################################

filename <- "Coursera_DS3_Final.zip"
                    ##Checking if archive already exists##
if (!file.exists(filename)){
  fileURL <- "https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip"
  download.file(fileURL, filename, method="curl")
} 
                        ##Checking if folder exists##
if (!file.exists("UCI HAR Dataset")) { 
  unzip(filename) 
}
                        ##Assigning data frames##
features <- read.table("UCI HAR Dataset/features.txt", col.names = c("n","functions"))
activities <- read.table("UCI HAR Dataset/activity_labels.txt", col.names = c("code", "activity"))
subject_test <- read.table("UCI HAR Dataset/test/subject_test.txt", col.names = "subject")
x_test <- read.table("UCI HAR Dataset/test/X_test.txt", col.names = features$functions)
y_test <- read.table("UCI HAR Dataset/test/y_test.txt", col.names = "code")
subject_train <- read.table("UCI HAR Dataset/train/subject_train.txt", col.names = "subject")
x_train <- read.table("UCI HAR Dataset/train/X_train.txt", col.names = features$functions)
y_train <- read.table("UCI HAR Dataset/train/y_train.txt", col.names = "code")

                     ##merging the information##
X <- rbind(x_train, x_test)
Y <- rbind(y_train, y_test)
Subject <- rbind(subject_train, subject_test)
Merged_Data <- cbind(Subject, Y, X)

                    ##selecting only the measurements on the mean and standard##
                               ##deviation for each measurement##
TidyData <- Merged_Data %>% select(subject, code, contains("mean"), contains("std"))

            ##assigning activity names to name the activities in the data set##
TidyData$code <- activities[TidyData$code, 2]

            ##Properly label the data set##
names(TidyData)[2] = "activity"
names(TidyData)<-gsub("-freq()", "Frequency", names(TidyData), ignore.case = TRUE)
names(TidyData)<-gsub("BodyBody", "Body", names(TidyData))
names(TidyData)<-gsub("angle", "Angle", names(TidyData))
names(TidyData)<-gsub("gravity", "Gravity", names(TidyData))
names(TidyData)<-gsub("Mag", "Magnitude", names(TidyData))
names(TidyData)<-gsub("^t", "Time", names(TidyData))
names(TidyData)<-gsub("^f", "Frequency", names(TidyData))
names(TidyData)<-gsub("tBody", "TimeBody", names(TidyData))
names(TidyData)<-gsub("Acc", "Accelerometer", names(TidyData))
names(TidyData)<-gsub("-mean()", "Mean", names(TidyData), ignore.case = TRUE)
names(TidyData)<-gsub("Gyro", "Gyroscope", names(TidyData))
names(TidyData)<-gsub("-std()", "STD", names(TidyData), ignore.case = TRUE)


FinalData <- TidyData %>%
  group_by(subject, activity) %>%
  summarise_all(list(mean))