analysis file

run_analysis.R

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+# Download the file and extract it to your R working Directory
+# https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip
+# read data set X
+training <- read.table("UCI HAR Dataset/train/X_train.txt")
+test <- read.table("UCI HAR Dataset/test/X_test.txt")
+# merge Data set X
+XCombined <- rbind(training, test)
+
+# read data set subject
+training <- read.table("UCI HAR Dataset/train/subject_train.txt")
+test <- read.table("UCI HAR Dataset/test/subject_test.txt")
+# merge data set X
+SCombined <- rbind(training, test )
+
+# read data set Y
+training <- read.table("UCI HAR Dataset/train/y_train.txt")
+test <- read.table("UCI HAR Dataset/test/y_test.txt")
+# merge data set Y
+YCombined <- rbind(training, test)
+
+# Extract mean and standard deviation for each measurement
+features <- read.table("UCI HAR Dataset/features.txt")
+colsNeeded <- grep(".*mean\\(\\)|.*std\\(\\)", features$MeasureName)
+XCombined <- XCombined[,colsNeeded]
+
+#Add descriptive activity names to name the activityLabels in the data set
+names(YCombined) <- "activity"
+activityLabels <- read.table("UCI HAR Dataset/activity_labels.txt")
+activityLabels[, 2] = gsub("_", "", tolower(as.character(activityLabels[, 2])))
+YCombined[,1] = activityLabels[YCombined[,1], 2]
+
+names(SCombined) <- "subject"
+merged <- cbind(SCombined, YCombined, XCombined)
+write.table(merged, "merged-data.txt")
+
+# make averages data set
+
+uniqueSubjects <- unique(SCombined)[,1] 
+numCols <- dim(merged)[2]
+result <- merged[1:(length(unique(SCombined)[,1])*length(activityLabels[,1])), ]
+
+row = 1
+for (sub in 1:length(unique(SCombined)[,1])) {
+  for (act in 1:length(activityLabels[,1])) {
+    result[row, 1] = uniqueSubjects[sub]
+    result[row, 2] = activityLabels[act, 2]
+    tmp <- merged[merged$subject==sub & merged$activity==activityLabels[act, 2], ]
+    result[row, 3:numCols] <- colMeans(tmp[, 3:numCols])
+    row = row+1
+  }
+}
+write.table(result, "averages.txt")