Just hacking around with R
Course project for "Getting and Cleaning Data" on Coursera
The raw data are obtained and processed to tidy data which are outputted to tidyData.txt, all by the R script run_analysis.R. The output and can be read and viewed in R with:
readData <- read.table("tidyData.txt", header = TRUE)
View(readData)
run_analysis.R uses the dplyr and tidyr packages to do the following:
- Downloads the raw data
- Merges the training and the test sets to create one data set.
- Extracts only the measurements on the mean and standard deviation for each measurement.
- Uses descriptive activity names to name the activities in the data set
- Appropriately label the data set (features) with descriptive variable names.
- From the data set above, create a second, independent tidy data set with the average of each variable for each activity and each subject. This is done using the "group_by" and "summarize_each" functions of dplyr.