CODEBOOK.md

CODE BOOK

This book describes the variables, the data, and any transformations or work that I performed to clean up the data.

1. Merges the training and the test sets to create one data set

• X_merge_data
• y_merge_data
• subject_merge_data

2. Extracts only the measurements on the mean and standard deviation for each measurement

• extract

3. Uses descriptive activity names to name the activities in the data set.

• y_merge_name_data

4. Appropriately labels the data set with descriptive variable names.

• names(y_merge_name_data)[1]<- "activities" activities : The type of activity performed when the corresponding measurements were taken.
• names(subject_merge_data)[1]<- "subject" subject : The ID of the subject.
• names(extract)<- sliced[[2]]

5. From the data set in step 4, creates a second, independent tidy data set with the average of each variable for each activity and each subject.

• tidy_data<- ddply(merged_data, .(subject, activities), function(x){colMeans(x\[,3:length(names(merged_data))\])}) : to create tidy data with w.r.t to activity and subject
• write.table(tidy_data, "tidy_averages_data.txt", row.name=FALSE) : writing data

run_analysis.R : It is the anaylsis R script created by me.

tidy_averages_data.txt : It is the tidy data output created after running run_analysis.R script.