{"push_id":555022330,"size":1,"distinct_size":1,"ref":"refs/heads/master","head":"dc0160030739be2f70644d8a0ce759bdbe17dd24","before":"9c002e5bc2e3a956a24976e0eedcc3b420273bd3","commits":[{"sha":"dc0160030739be2f70644d8a0ce759bdbe17dd24","author":{"email":"a2b62bf38d1d0baeab7140b670fbfddeee42989a@users.noreply.github.com","name":"Susan Z Martin"},"message":"Update Codebook.md\n\nThis Codebook details the data downloaded from the UCI Machine Learning Repository (http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones), describes briefly how that data was collected and transformed into 'feature vectors', how the variable names were altered to make them both adherent to R programming 'best practices' as well as rendering them suitable for performing dplyr functions, and finally describes the 88 variables present in the end product of the run_analysis.R script - a tidy data frame containing the mean of each numerical variable for each of the 30 subjects and 6 activities they performed for the study.","distinct":true,"url":"https://api.github.com/repos/SusanZMartin/Getting-and-Cleaning-Data-Course-Project/commits/dc0160030739be2f70644d8a0ce759bdbe17dd24"}]}