---
title: "Bulk analysis with rcites"
author: "rcites team"
date: 15-08-2018
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Bulk analysis with rcites}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
editor_options:
  chunk_output_type: console
---




## Broad taxon concept queries

If you want to query all taxa, you can use `spp_taxonconcept()` with
`query_taxon = ""` (assuming your token is already set up):


```r
res_cms <- spp_taxonconcept("", taxonomy = "CMS") #slow
```

```
#>  ℹ Retrieving info from page 1 ........................ ✔
#>  ℹ 10 pages available, retrieving info from 9 more
#>  ℹ Retrieving info from page 2 ........................ ✔
#>  ℹ Retrieving info from page 3 ........................ ✔
#>  ℹ Retrieving info from page 4 ........................ ✔
#>  ℹ Retrieving info from page 5 ........................ ✔
#>  ℹ Retrieving info from page 6 ........................ ✔
#>  ℹ Retrieving info from page 7 ........................ ✔
#>  ℹ Retrieving info from page 8 ........................ ✔
#>  ℹ Retrieving info from page 9 ........................ ✔
#>  ℹ Retrieving info from page 10 ....................... ✔
```

```r
dim(res_cms$general)
```

```
#>  [1] 2541    7
```

Alternatively, you can retrieve, for example, the first three pages of results
returned by the API.


```r
res_cites <- spp_taxonconcept("", page = 1:2)
```

```
#>  ℹ Retrieving info from page 1 ........................ ✔
#>  ℹ 167 pages available, retrieving info from 1 more
#>  ℹ Retrieving info from page 2 ........................ ✔
```

```r
dim(res_cites$general)
```

```
#>  [1] 1000    8
```

## Retrieving information for a set of taxon_concept ID

All `spp_` functions (i.e. `spp_distributions()`, `spp_eu_legislation()`,
`spp_cites_legislation()` and `spp_references()`) can handle a vector of
taxon_id which allows bulk analysis.
Below we exemplify this feature for the four functions.

### spp_distributions()


```r
vc_txn <- c('4521', '3210', '10255')
res1 <- spp_distributions(taxon_id = vc_txn, verbose = FALSE)
## Number of countries concerned per taxon ID
table(res1$distributions$taxon_id)
```

```
#>  
#>  10255  3210  4521 
#>     15     8    42
```



### spp_cites_legislation()


```r
res2 <- spp_cites_legislation(taxon_id = vc_txn, verbose = FALSE)
res2$cites_listings
```

```
#>  # A tibble: 12 × 7
#>     taxon_id id    taxon_concept_id is_current appendix change_type effective_at
#>     <chr>    <chr> <chr>            <lgl>      <chr>    <chr>       <chr>       
#>   1 4521     30344 4521             TRUE       I        +           2017-01-02  
#>   2 4521     30115 4521             TRUE       II       +           2019-11-26  
#>   3 4521     32160 4521             TRUE       II       R+          2019-11-26  
#>   4 4521     32161 4521             TRUE       II       R+          2019-11-26  
#>   5 4521     32156 4521             TRUE       II       R+          2019-11-26  
#>   6 4521     32158 4521             TRUE       II       R+          2019-11-26  
#>   7 4521     32154 4521             TRUE       II       R+          2019-11-26  
#>   8 4521     32159 4521             TRUE       II       R+          2019-11-26  
#>   9 4521     32157 4521             TRUE       II       R+          2019-11-26  
#>  10 4521     32155 4521             TRUE       II       R+          2019-11-26  
#>  11 3210     4661  3210             TRUE       II       +           1987-10-22  
#>  12 10255    4645  10255            TRUE       I        +           2005-01-12
```

### spp_eu_legislation()




```r
res3 <- spp_eu_legislation(taxon_id = vc_txn, verbose = FALSE)
res3$eu_listings
```

```
#>  # A tibble: 4 × 7
#>    taxon_id id    taxon_concept_id is_current annex change_type effective_at
#>    <chr>    <chr> <chr>            <lgl>      <chr> <chr>       <chr>       
#>  1 4521     31788 4521             TRUE       A     +           2019-12-14  
#>  2 4521     31876 4521             TRUE       B     +           2019-12-14  
#>  3 3210     30578 3210             TRUE       B     +           2019-12-14  
#>  4 10255    30516 10255            TRUE       A     +           2019-12-14
```


### spp_references()




```r
res4 <- spp_references(taxon_id = vc_txn, verbose = FALSE)
## Number of references per taxon ID
table(res4$references$taxon_id)
```

```
#>  
#>  10255  3210  4521 
#>      1     3    15
```
