v0.5.0

Initial CRAN Release

What's Changed

• Update installation instructions and delete epitrax-report-generator.R by @apulsipher in #77
• Add acknowledgments section to README by @apulsipher in #91
• Make Pretty PDFs by @apulsipher in #75
• Fix button width & add warning if no reports are selected to generate by @NateLanza in #98
• Increase maximum file size to 30MB by @apulsipher in #99
• Add option for trend-only PDF reports by @apulsipher in #101
• Update troubleshooting steps for installation and usage in README by @apulsipher in #102
• Update README with useful instructions from original project by @apulsipher in #106
• Update and improve roxygen and website documentation by @apulsipher in #111
• Prepare for CRAN submission by @apulsipher in #112
• Resolve CRAN v0.5.0 submission notes by @apulsipher in #116
• Update README after CRAN acceptance by @apulsipher in #117

Full Changelog: v0.4.0...v0.5.0

v0.4.0

What's Changed

• Update tests to use tempdir() and to unlink when done by @apulsipher in #65
• Create NEWS.md file with all released versions for epitraxr package by @Copilot in #59
• Add additional vignettes by @apulsipher in #66
• Add comprehensive Copilot instructions for epitraxr development by @Copilot in #61
• Use %||% operator for default NULL values by @apulsipher in #68
• Fix bug with epitrax_write_xlsxs() by @apulsipher in #69
• Rename prep_report_data() to standardize_report_diseases() by @apulsipher in #70
• Update how package handles extracting X yrs of data from intput by @apulsipher in #71
• Create issue templates by @apulsipher in #73
• Add repo management docs by @apulsipher in #74
• Add a Shiny app frontend for report generation by @NateLanza in #72

New Contributors

• @Copilot made their first contribution in #59
• @NateLanza made their first contribution in #72

Full Changelog: v0.3.2...v0.4.0

v0.3.2

What's Changed

• Create grouped reports by @apulsipher in #52
• Create SLCounty-style report by @apulsipher in #46
• Add threshold parameter to get_trend() by @apulsipher in #56
• Add new report combining monthly and YTD stats by @apulsipher in #57
• Complete R package checklist by @apulsipher in #62

Full Changelog: v0.2.2...v0.3.2

v0.2.2

What's Changed

• Verify piped script matches original script behavior by @apulsipher in #31

Full Changelog: v0.2.1...v0.2.2

v0.2.1

What's Changed

• Add method for setting config programmatically by @apulsipher in #29

Full Changelog: v0.2.0...v0.2.1

v0.2.0

What's Changed

• Support pipe operator and add report generation functions for EpiTrax object by @apulsipher in #26

Full Changelog: v0.1.3...v0.2.0

v0.1.3

What's Changed

• Add pkgdown website by @apulsipher in #24
• Create new EpiTrax data object by @apulsipher in #25

New Contributors

• @apulsipher made their first contribution in #24

Full Changelog: v0.1.0...v0.1.3

v0.1.0

epitraxr v0.1.0

Initial release of the epitraxr package for R, providing tools to manipulate EpiTrax data exports and generate standardized reports.

Overview

This is the first release of the epitraxr package, which transforms the original EpiTrax reporting script from epitrax-report-automation into a fully-documented, tested R package. The package provides functions for processing EpiTrax disease surveillance data and generating both internal and public health reports.

Features

Core Modules

• Data Processing (data.R): Functions for validating and formatting EpiTrax data exports, ensuring correct column types and data structure
• Report Generation (reports.R): Comprehensive suite of functions for creating monthly and year-to-date reports in both internal and public formats
• Filesystem Management (filesystem.R): Utilities for managing report directories and file operations
• Helper Functions (helpers.R): Common utilities for data manipulation, including MMWR week calculations and trend analysis

Sample Data

The package includes a sample dataset (inst/sample_data/sample_epitrax_data.csv) generated with realistic disease patterns for testing and examples. The dataset includes:

• Multiple years of data (2019-2024)
• Common diseases with realistic case counts
• Proper MMWR week formatting

Testing

• Comprehensive unit tests for all functions using the tinytest framework
• Test data and configurations included in inst/tinytest/

Documentation

• Full roxygen documentation for all exported functions
• Detailed examples and usage patterns
• MIT license

Dependencies

• lubridate for date handling
• yaml for configuration management
• Base R packages: stats, utils

Contributors

• Andrew Pulsipher (author, maintainer)