{"id":28679250,"url":"https://github.com/antoniojbt/episcout","last_synced_at":"2026-03-08T06:31:24.526Z","repository":{"id":236125084,"uuid":"150758055","full_name":"antoniojbt/episcout","owner":"antoniojbt","description":"Facilitates cleaning, exploring and visualising large epidemiological datasets.","archived":false,"fork":false,"pushed_at":"2025-08-25T18:10:40.000Z","size":1220,"stargazers_count":2,"open_issues_count":12,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-08-25T19:07:50.990Z","etag":null,"topics":["epidemiology","r","wrangling"],"latest_commit_sha":null,"homepage":"","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/antoniojbt.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"COPYING","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2018-09-28T15:10:39.000Z","updated_at":"2025-08-25T17:45:56.000Z","dependencies_parsed_at":"2025-04-25T17:42:14.306Z","dependency_job_id":"7b1ae3e3-b16e-466b-8204-c2ccfc2c17d0","html_url":"https://github.com/antoniojbt/episcout","commit_stats":null,"previous_names":["antoniojbt/episcout"],"tags_count":4,"template":false,"template_full_name":null,"purl":"pkg:github/antoniojbt/episcout","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/antoniojbt%2Fepiscout","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/antoniojbt%2Fepiscout/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/antoniojbt%2Fepiscout/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/antoniojbt%2Fepiscout/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/antoniojbt","download_url":"https://codeload.github.com/antoniojbt/episcout/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/antoniojbt%2Fepiscout/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30247323,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-08T05:41:50.788Z","status":"ssl_error","status_checked_at":"2026-03-08T05:41:39.075Z","response_time":56,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["epidemiology","r","wrangling"],"created_at":"2025-06-14T01:04:04.342Z","updated_at":"2026-03-08T06:31:24.510Z","avatar_url":"https://github.com/antoniojbt.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)\n[![R](https://github.com/antoniojbt/episcout/actions/workflows/r-cmd-check.yml/badge.svg)](https://github.com/antoniojbt/episcout/actions/workflows/r-cmd-check.yml)\n[![codecov](https://codecov.io/gh/AntonioJBT/episcout/branch/master/graph/badge.svg)](https://codecov.io/gh/AntonioJBT/episcout)\n\n# episcout\n\nepiscout provides helper functions for cleaning, exploring and visualising large datasets. It wraps common preprocessing and descriptive tasks so you can focus on analysis. The package builds on the **tidyverse** and **data.table** ecosystems for fast and flexible data manipulation.\n\n## Features\n\n* **Cleaning** – `epi_clean_*` functions tidy raw data and detect issues such as duplicates or inconsistent labels.\n* **Statistics** – `epi_stats_*` functions create summary tables and descriptive statistics in a single call.\n* **Plotting** – `epi_plot_*` wrappers make it straightforward to produce common graphs with *ggplot2* and *cowplot*.\n* **Utilities** – `epi_utils_*` helpers cover tasks like parallel processing and logging.\n\n## Installation\n\n\u003c!--- \nYou can install the released version of episcout from [CRAN](https://CRAN.R-project.org) with:\n\n``` r\ninstall.packages(\"episcout\")\n```\n---\u003e\n\nInstall from GitHub:\n``` r\ninstall.packages(\"devtools\")\nlibrary(devtools)\ninstall_github(\"AntonioJBT/episcout\")\n```\n\n## Getting Started\n\nFunctions are grouped by purpose, e.g.:\nepi_clean_* for data wrangling/cleanup.\nepi_stats_* for generating descriptive statistics and contingency tables.\nepi_plot_* for plotting (wrappers around ggplot2 and cowplot).\nepi_utils_* for utilities such as parallel processing, logging, etc.\nMiscellaneous helpers such as epi_read/epi_write.\n\n## Example\n\nThis is a basic example of things you can do with episcout:\n\n``` r\nlibrary(episcout)\n\n# A data frame:\nn \u003c- 20\ndf \u003c- data.frame(var_id = rep(1:(n / 2), each = 2),\n                 var_to_rep = rep(c('Pre', 'Post'), n / 2),\n                 x = rnorm(n),\n                 y = rbinom(n, 1, 0.50),\n                 z = rpois(n, 2)\n                 )\n# Print the first few rows and last few rows:\ndim(df)\nepi_head_and_tail(df, rows = 2, cols = 2)\nepi_head_and_tail(df, rows = 2, cols = 2, last_cols = TRUE)\n\n\n# Get all duplicates:\ncheck_dups \u003c- epi_clean_get_dups(df, 'var_id', 1)\ndim(check_dups)\ncheck_dups\n\n# Get summary descriptive statistics for numeric/integer column:\nnum_vec \u003c- df$x\ndesc_stats \u003c- epi_stats_numeric(num_vec)\nclass(desc_stats)\nlapply(desc_stats, class)\ndesc_stats\n\n# And many more functions for cleaning, stats and plotting that do things a bit faster or more conveniently and I couldn't easily find in other packages.\n```\n\n## Contribute\n\n- [Issue Tracker](https://github.com/AntonioJBT/episcout/issues)\n\n- Pull requests welcome!\n\n\nSupport\n-------\n\nIf you have any issues, pull requests, etc. please report them in the issue tracker. \n\n## News\n\n- Version 0.1.3\n  Improved coverage tests, added a few wrappers, slightly improved documentation\n  \n- Version 0.1.2\n  Minor bug fixes and internal improvements\n\n- Version 0.1.1\n  First release\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fantoniojbt%2Fepiscout","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fantoniojbt%2Fepiscout","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fantoniojbt%2Fepiscout/lists"}