README.Rmd

---
output: github_document
---


```{r setup, echo = FALSE, message = FALSE, results = 'hide'}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 8,
  fig.height = 6,
  fig.path = "figs/",
  echo = TRUE
)

```



# Welcome to the *linelist* package!

[![Travis build status](https://travis-ci.org/reconhub/linelist.svg?branch=master)](https://travis-ci.org/reconhub/linelist)
[![Codecov test coverage](https://codecov.io/gh/reconhub/linelist/branch/master/graph/badge.svg)](https://codecov.io/gh/reconhub/linelist?branch=master)

This package is dedicated to simplifying the cleaning and standardisation of
[line list](https://outbreaktools.ca/background/line-lists/) data. Considering a case line list `data.frame`, it aims to:

- standardise the variables names, replacing all non-ascii characters with their
  closest latin equivalent, removing blank spaces and other separators,
  enforcing lower case capitalisation, and using a single separator between
  words
  
- standardise the labels used in all variables of type `character` and `factor`,
  as above

- set `POSIXct` and `POSIXlt` to `Date` objects

- extract dates from a messy variable, automatically detecting formats, allowing
  inconsistent formats, and dates flanked by other text
  


## Installing the package

To install the current stable, CRAN version of the package, type:
```{r install, eval = FALSE}
install.packages("linelist")
```

To benefit from the latest features and bug fixes, install the development, *github* version of the package using:
```{r install2, eval = FALSE}
devtools::install_github("reconhub/linelist")
```

Note that this requires the package *devtools* installed.

# Quick example

Let us consider a messy `data.frame` as an example: 

```{r toy_data}
library(linelist)
example_data <- messy_data(10)
example_data
```

We then use the `clean_data()` command to get nice, clean data!

```{r clean_data}
clean_data(example_data, guess_dates = TRUE)
```


# What does it do?

Procedures to clean data, first and foremost aimed at `data.frame` formats,
include:

- `clean_data()`: the main function, taking a `data.frame` as input, and doing all
  the variable names, internal labels, and date processing described above
  
- `clean_variable_names()`: like `clean_data`, but only the variable names

- `clean_variable_labels()`: like `clean_data`, but only the variable labels
 
- `clean_variable_spelling()`: provided with a dictionary, will correct the
  spelling of values in a variable and can globally correct commonly mis-spelled
  words.

- `clean_dates()`: like `clean_data`, but only the dates

- `guess_dates()`: find dates in various, unspecified formats in a messy
  `character` vector
  



## Getting help online

Bug reports and feature requests should be posted on *github* using the [*issue*](http://github.com/reconhub/linelist/issues) system. All other questions should be posted on the **RECON forum**: <br>
[http://www.repidemicsconsortium.org/forum/](http://www.repidemicsconsortium.org/forum/)

Contributions are welcome via **pull requests**.

Please note that this project is released with a [Contributor Code of Conduct](CONDUCT.md). By participating in this project you agree to abide by its terms.