Skip to content

Latest commit

 

History

History
37 lines (19 loc) · 1.78 KB

README.md

File metadata and controls

37 lines (19 loc) · 1.78 KB
Raw

  1. The script run_analysis.R , downloads the file https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip and saves in the working directory as wearable.zip and unzips it.

  2. The script ignores the raw data files in the directories "UCI HAR Dataset/train/Inertial Signals" and "UCI HAR Dataset/test/Inertial Signals"

  3. The script then reads data from featurs.txt and activity_labels.txt

  4. Only the features that contain the string -mean() or -std() in the feature name are selected

  5. The names of the features are modified to a. Convert the uppercase characters to lowercase b. Remove the characters - ( )

  6. The script then reads data from X_train.txt ,y_train.txt ,subject_train.txt . It reads only the columns selected in step 4 from the file X_train

  7. The script then reads data from X_test.txt ,y_test.txt ,subject_test.txt . It reads only the columns selected in step 4 from the file X_test

  8. The script combines rows from y_train.txt and y_test.txt into "y_all" data frame

  9. The script combines rows from subject_train.txt and subject_test.txt into "subject" data frame

  10. The script merges y_all and subject data frames into "adt" data frame

  11. The script combines rows from x_train.txt and x_test.txt into "x_data" data frame

  12. The script then merges data frames "adt" and "activity_labels" into "activity" data frame

  13. The script then combines columns from x_data and activity into data frame "all_data"

  14. The script removes column activityid from the dataframe "all_data"

  15. The script then creates a second, independent tidy data set "data_ave_by_subject_activity" with the average of each variable for each activity and each subject

  16. The script then writes the new tidy dataset into file tidydata.txt in to working directory