{"id":16368697,"url":"https://github.com/simoneb/coursera-getting-and-cleaning-data-course-project","last_synced_at":"2026-02-26T22:30:20.976Z","repository":{"id":27679745,"uuid":"31165974","full_name":"simoneb/coursera-getting-and-cleaning-data-course-project","owner":"simoneb","description":null,"archived":false,"fork":false,"pushed_at":"2015-02-22T15:01:42.000Z","size":132,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":3,"default_branch":"master","last_synced_at":"2024-12-31T07:13:37.412Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/simoneb.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2015-02-22T14:45:56.000Z","updated_at":"2015-02-22T15:01:43.000Z","dependencies_parsed_at":"2022-09-03T03:14:12.398Z","dependency_job_id":null,"html_url":"https://github.com/simoneb/coursera-getting-and-cleaning-data-course-project","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/simoneb%2Fcoursera-getting-and-cleaning-data-course-project","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/simoneb%2Fcoursera-getting-and-cleaning-data-course-project/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/simoneb%2Fcoursera-getting-and-cleaning-data-course-project/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/simoneb%2Fcoursera-getting-and-cleaning-data-course-project/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/simoneb","download_url":"https://codeload.github.com/simoneb/coursera-getting-and-cleaning-data-course-project/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239869220,"owners_count":19710485,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-10-11T02:53:33.617Z","updated_at":"2025-02-20T16:14:21.740Z","avatar_url":"https://github.com/simoneb.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"Coursera Getting and Cleaning Data Course Project\n========\n\nThis document explains how the script works.\n\n## Prerequisites\n\nIn order to run the script you should clone this repository and make sure that the R packages `plyr` and `dplyr` are installed.\n\nYou'll also need to have the original Samsung set data in a folder named *UCI HAR Dataset* in the repository directory. The original set wasn't included because too big to be conveniently transferred via Git.\n\n## How it works\n\n### Preparation\n\nThe script creates two common variables:\n\n- `features`: holds the meaningful names of the features, from the `features.txt` file\n- `activities`: holds the descriptive names of the activities, from the `activity_labels.txt` file\n\nThe script also defines three functions for the operations to be executed on the test and training sets:\n\n- `readset`: reads the data of the set given the path to the CSV file in a data frame and assigns `features` to variable names, as to give them menaingful names\n- `readsetactivities`: reads and joins the labels of each test set (either `y_text.txt` or `y_train.txt`) with `activities`, in order to give numeric activities in each set a descriptive name\n- `readsetsubjects`: reads the subjects of each set into a data frame\n\n### Set creation\n\nFor each of the test and train sets a grouping variable is created which contains 4 variables:\n\n- `set`: the result of executing `readset` on either `X_test.txt` or `X_train.txt`\n- `activities`: the result of executing `readsetactivities` on either `y_test.txt` or `y_train.txt`\n- `subjects`: the result of executing `readsetsubjects` on either `subject_test.txt` or `subject_train.txt`\n- `fullset`: the result of `cbind`ing `activities`, `subjects` and `set`\n\n### Set merging\n\nThen the two `fullset`s are *merged* by binding all their rows together with `rbind` and only the columns containing *means* and *stds* of measures (in addition to subjects and activities) are extracted with a regular expression\n\n### Final result\n\nThe final result is obtained by grouping the merged and column-filtered data frame by subject and activity and computing the mean of all the remaining rows for each group","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsimoneb%2Fcoursera-getting-and-cleaning-data-course-project","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsimoneb%2Fcoursera-getting-and-cleaning-data-course-project","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsimoneb%2Fcoursera-getting-and-cleaning-data-course-project/lists"}