---
title: "Accessing Clean UNAIDS Data"
output: rmarkdown::html_vignette
description: |
  This vignette addresses how to pull the clean 2020 UNAIDS Estimates from Google Drive to R.
vignette: >
  %\VignetteIndexEntry{accessing-clean-unaids}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
   comment = "#>",
      eval = TRUE, 
      echo = TRUE
)
options(rmarkdown.html_vignette.check_title = FALSE)
```

### Introduction

This vignette covers how to access the clean and tidy annual UNAIDS Estimates from [GitHub Releases](https://github.com/USAID-OHA-SI/mindthegap/releases). The `mindthegap` package uses a cleaning function (`munge_edms`) (formerly `munge_unaids`) to process, munge, and tidy the UNAIDS HIV Estimates output from the [EDMS database](https://edms.unaids.org/) once new estimates are available annually (around July) and `load_unaids` to load this cleaned data into your session.

Let's start by loading the `mindthegap` package.

```{r setup, message = FALSE}
library(mindthegap)
library(knitr)
```

### Pull clean data from GitHub Releases

When new data are released annually, our team extracts the data from the UNAIDS database and runs `munge_edms` on it to clean and tidy the dataset, including new variables such as a `pepfar` flag to denote whether a country is a PEPFAR country or not and an `estimate_flag` to indicate estimates that are an approximation (previously contained a "\<" or "\>"). In order to make this data accessible outside of R and cut down on the processing time, we uploaded the clean UNAIDS data to the [package releases](https://github.com/USAID-OHA-SI/mindthegap/releases);  users can easily access this data by running `load_unaids` with R or directly downloading the data file.

To use `load_unaids`, the user just needed to specify whether they want to return all countries or just PEPFAR ones (`pepfar_only = TRUE`), the default.


```{r, message = FALSE}
df_unaids <- load_unaids(pepfar_only = TRUE)

kable(head(df_unaids), format = "html")
```