README.Rmd

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output: github_document
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# insectcleanr

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The goal of insectcleanr is to provide functions for building cleaned data tables of insect data.  This code package was developed for internal use by a SESYNC pursuit team by SESYNC data science staff. 

## Publication and Citation

This package has been published on [Zenodo](https://zenodo.org/record/4555787).  It should be cited with the [DOI](https://doi.org/10.5281/zenodo.4555787) as:  

Rachael E. Blake, & Rebecca Turner. (2021, February 22). reblake/insectcleanr: Initial release (Version 0.1). Zenodo. http://doi.org/10.5281/zenodo.4555787

## Installation

You can install the latest version of insectcleanr from [GitHub](https://github.com/reblake/insectcleanr) with:

```{r installation, message=FALSE, warning=FALSE, eval=FALSE}
# install.packages("devtools")
devtools::install_github("reblake/insectcleanr")
```

## Example

Example data in this package is courtesy of 
Morimoto, N., Kiritani, K., Yamamura, K., & Yamanaka, T. (2019). Finding indications of lag time, saturation and trading inflow in the emergence record of exotic agricultural insect pests in Japan. Applied Entomology and Zoology, 54(4), 437-450. [DOI:10.1007/s13355-019-00640-2](https://doi.org/10.1007/s13355-019-00640-2)

This is a basic example which shows you how to get accepted taxonomic information for insect taxa from GBIF.

```{r example, warning=FALSE, message=FALSE}
library(insectcleanr)

# list the path(s) to your raw data files
# your path will look different than this; this path loads the example data included in this package
file_list <- system.file("extdata", "Japan_taxa.xlsx", package = "insectcleanr", mustWork = TRUE)

# read in raw data and separate out taxonomic information
taxa_list <- lapply(file_list, separate_taxonomy) %>%
             purrr::reduce(full_join) %>%  # join list of dataframes into one dataframe
             distinct(genus_species) %>%  # get unique taxa names
             arrange(genus_species) %>%  # alphabetical order by taxa name
             select(genus_species) %>%  # select only the column with taxa names
             unlist(., use.names = FALSE)  # make taxa names into a vector
              
# get accepted taxonomic information from GBIF
taxa_accepted <- lapply(taxa_list, get_accepted_taxonomy)
```

A full workflow for making a taxonomy table and other tables is available in the vignettes.