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https://github.com/helseprofil/orgdata

:package: R package for aggregating original data mostly on enumeration areas level of granularity
https://github.com/helseprofil/orgdata

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:package: R package for aggregating original data mostly on enumeration areas level of granularity

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README

        

---
output:
md_document:
variant: gfm
html_preview: false
---

```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```

# orgdata

[![R-CMD-check](https://github.com/helseprofil/orgdata/workflows/R-CMD-check/badge.svg)](https://github.com/helseprofil/orgdata/actions)
[![Codecov test coverage](https://img.shields.io/codecov/c/github/helseprofil/orgdata?logo=codecov)](https://app.codecov.io/gh/helseprofil/orgdata?branch=main)
[![](https://img.shields.io/badge/lifecycle-stable-green.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable)
[![GitHub R package version (branch)](https://img.shields.io/github/r-package/v/helseprofil/orgdata/main)](https://github.com/helseprofil/orgdata)
[![GitHub R package version (branch)](https://img.shields.io/github/r-package/v/helseprofil/orgdata/dev)](https://github.com/helseprofil/orgdata)

```{r echo=FALSE, results="hide", message=FALSE, eval=FALSE}
library("badger")
```

```{r, echo = FALSE, results='asis', eval=FALSE}
cat(
badge_github_actions(),
badge_codecov("helseprofil/orgdata"),
badge_lifecycle("stable", "green"),
badge_github_version("helseprofil/orgdata", "blue")
)
```

Cleaning, restructuring and aggregating **OR**i**G**inal **DATA** into a
preferred dataset.

## Installation

The easiest way to install *orgdata* is to use `kh_install()` function.

```r
source("https://raw.githubusercontent.com/helseprofil/misc/main/utils.R")
kh_install("orgdata")
```

Update to new version or install the development version via `orgdata`.

```r
orgdata::update_khpackage("orgdata")

# install development versjon
orgdata::update_khpackage("orgdata", branch = "dev")
```

## Usage

To implement the specifications per file group as being registered in the
database can be done using `make_file()` function.

```r
library(orgdata)
# All files under BEFOLKNING group
dt <- make_file("BEFOLKNING")

# Select files with KOBLID
dt <- make_file("BEFOLKNING", koblid = 48)
dt <- make_file("BEFOLKNING", koblid = c(48, 72))

# Select files without KOBLID
dt <- make_file("BEFOLKNING", select = 1) #select the first valid file
dt <- make_file("BEFOLKNING", select = "last") #select the most recent file
```

Use function `make_filegroups()` to process multiple file groups at once.

```r
make_filegroups(BEFOLKNING, LESEFERD, NEET)
```

## Resources

- [Config file](https://github.com/helseprofil/config/blob/main/config-orgdata.yml)
- [Get started](https://helseprofil.github.io/orgdata/articles/get-started.html)
- [Functions overview](https://helseprofil.github.io/orgdata/reference/index.html)
- [General guide](https://helseprofil.github.io/manual/)
- [Conventions](https://helseprofil.github.io/orgdata/articles/standard.html)
- [Video guide](https://youtu.be/PhEQq4iWJCY)