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https://github.com/annakrystalli/seabirddietdb

Seabird Diet (stomach content) Database collected around the British Isles (1933 - 2017)

https://github.com/annakrystalli/seabirddietdb

Science Score: 26.0%

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    CITATION.cff file
  • ✓
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    Found codemeta.json file
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    Found .zenodo.json file
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    Scientific vocabulary similarity
    Low similarity (17.1%) to scientific vocabulary
Last synced: 11 months ago · JSON representation

Repository

Seabird Diet (stomach content) Database collected around the British Isles (1933 - 2017)

Basic Info
Statistics
  • Stars: 2
  • Watchers: 4
  • Forks: 0
  • Open Issues: 5
  • Releases: 0
Created about 8 years ago · Last pushed almost 7 years ago
Metadata Files
Readme License

README.Rmd 

---
output: github_document
---



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


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


The goal of seabirddietDB is to provide access and tools to interact with a database of seabird diets collected around the British Isles.

## Installation

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

``` r
# install.packages("remotes")
remotes::install_github("annakrystalli/seabirddietDB")
```

## Data 

For more details on the dataset, check out the [full documentation](https://annakrystalli.me/seabirddietDB/)


## Example

To access the data simply load the package. The data is then available

```{r print-seabirddiet}
library(seabirddietDB)

```


```{r, eval=FALSE}
seabirddiet
```

```{r, echo=FALSE}
tibble::as_tibble(seabirddiet)
```


A version with more formal data types/structures in the columns (ie geographic information stored as `sf`, categorical data as factors etc) is also available. Note that you will need package `sf` installed to load this version of the data.

```{r print-seabirddiet_, eval=FALSE}
class(seabirddiet_)
```


## Helpers

### metadata

A number of metadata datasets are included with the package: `attributes`, `references` and `classification`. Load them as you would one of the datasets, e.g. :

```{r}
references
```



### List
List predators

```{r}
sbd_predators()
```

List prey

```{r}
sbd_prey(verbose = TRUE)
```

### Filter data
#### filter predator
```{r}
sbd_filter(pred_species = "Fratercula arctica")
```

#### filter metrics

```{r}

sbd_filter(pred_species = "Fratercula arctica", metrics = "freq_biomass")
```

#### filter prey
```{r}
sbd_filter(prey_taxon = c("Cottidae", "Actinopterygii"))
```

#### filter year

```{r}
sbd_filter(year = 1973:1976)
```



#### filter multiple
```{r}
sbd_filter(year = 1973:1976, pred_species = "Uria aalge", prey_taxon = "Gadidae")
```



### Plot data

There are additional helpers for interactive plotting of data

```{r plot-year}
sbd_plot_predators(year = 1973)
```


***

To cite use

```{r}
citation("seabirddietDB")
```

Owner

  • Name: Anna Krystalli
  • Login: annakrystalli
  • Kind: user
  • Location: Syros, Greece
  • Company: @r-rse

Research Software Engineering Service in #rstats at @r-rse. Ex @RSE-Sheffield. Editor @ropensci. Core team member @reprohack. Available for hire! 🚀😎

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  • annakrystalli (20)
  • agnesolin (1)
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