{"push_id":1348035952,"size":1,"distinct_size":1,"ref":"refs/heads/master","head":"7287e5a957d4d33d653664c1717ab1399e16d307","before":"3d3a2d8a340e4992faf504fe14a1d6e559e8f28e","commits":[{"sha":"7287e5a957d4d33d653664c1717ab1399e16d307","author":{"name":"tjinka","email":"30a4224bceb90cd6e16a14cfc1ac1c136374318e@gmail.com"},"message":"Delete README.md\n\n\r\nThe projects purpose is to demonstrate persons ability to collect, work with, and clean a data set with a goal of preparing tidy data that can be used for future analysis. \r\n\r\nrun_analysis.R performs the following in this project:\r\n\r\nMerging: \r\nMerges the training and the test sets and creates one single data set.\r\n\r\nExtracting:\r\nExtracts only the measurements on the mean and standard deviation for each measurement in the data.\r\n\r\nDescription:\r\nUses descriptive activity names to name the activities in the data set\r\n\r\nLabelling:\r\nLabels the data set with descriptive activity names.\r\n\r\nAn independent tidy data set is created with the average of each variable for each activity and each subject.\r\nrun_analysis.R\r\n\r\nIt works by downloading the dataset to working directory, unzips file into the UCI HAR Dataset folder.\r\nTrain and test data sets are loaded, appended into one data frame using rbind\r\nMean and SD are extracted using grep.\r\nColumn names are cleaned, applied to the x data frame.\r\nConverts dataset to lowercase and subject column names are named \r\nThree data sets are merged and exported to txt file into the project folder in the same working directory.\r\nMean of activities and subjects are created as tidy data set, exported as txt file, named average.txt\r\nR code is with str for easier preview of the two final data sets.","distinct":true,"url":"https://api.github.com/repos/tjinka/Getting-Cleaning-Final-Project/commits/7287e5a957d4d33d653664c1717ab1399e16d307"}]}
{"actor":{"display_login":"tjinka"}}