---
title: "qualitycontrol"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{qualitycontrol}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```


<!-- README.md is generated from README.Rmd. Please edit that file -->

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

# `qualitycontrol`


The goal of `qualitycontrol` is to set a data quality control framework

## Installation

You can install the `qualitycontrol` from [GitHub](https://github.com/) with:

```{r, eval = FALSE}
# install.packages("devtools")
devtools::install_github("luisgarcez11/qualitycontrol")
```

### Data

The `als_data` dataset will be used to guide you through the package functionality. This data is not real, but based on data retrieved from Amyotrophic Lateral Sclerosis patients.

```{r example, eval = TRUE}
library(qualitycontrol)
als_data
```

### QC mapping 

The `als_data_qc_mapping` is an `R list` which contains 3 tables specifying all the tests used for quality control.

#### Missing
```{r}
als_data_qc_mapping$missing
```

#### Inconsistencies
```{r}
als_data_qc_mapping$inconsistencies
```

#### Out of range values
```{r}
als_data_qc_mapping$range
```


### `qc_data` function

`qc_data` takes as arguments the data to be quality controlled and the QC mapping containing the tests to be applied.

```{r}
qc_data(als_data, als_data_qc_mapping)
```

 This will return a table with all the findings. If you want to save it, you can specify the path to be saved in `output_file`.