taxizedb

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taxizedb - Tools for Working with Taxonomic Databases on your Machine

taxize is a heavily used taxonomic toolbelt package in R - However, it makes web requests for nearly all methods. That is fine for most cases, but when the user has many, many names it is much more efficient to do requests to a local SQL database.

Not all taxonomic databases are publicly available, or possible to mash into a SQLized version. Taxonomic DB’s supported thus far:

Get in touch in the issues with any ideas on new data sources.

This package for each data sources performs the following tasks:

install

cran version

install.packages("taxizedb")

dev version

devtools::install_github("ropensci/taxizedb")
library("taxizedb")
library("dplyr")

start your SQL DBs

Remember to start your PostgreSQL database for ITIS and ThePlantList and your MySQL database for COL

Download and load DBs

ITIS

x <- db_download_itis()
db_load_itis(x)

The Plant List (TPL)

x <- db_download_tpl()
db_load_tpl(x)

Catalogue of Life (COL)

x <- db_download_col()
db_load_col(x)

connect to the DBs

ITIS

src <- src_itis(user = "<user name>", password = "<password>")

TPL

src <- src_tpl()

COL

src <- src_col()

query with SQL syntax

sql_collect(src, "select * from hierarchy limit 5")
#> # A tibble: 5 x 5
#>                     hierarchy_string    tsn parent_tsn level childrencount
#> *                              <chr>  <int>      <int> <int>         <int>
#> 1                             202422 202422          0     0        154282
#> 2                      202422-846491 846491     202422     1          2666
#> 3               202422-846491-660046 660046     846491     2          2654
#> 4        202422-846491-660046-846497 846497     660046     3             7
#> 5 202422-846491-660046-846497-846508 846508     846497     4             6
# or pipe the src to sql_collect
src %>% sql_collect("select * from hierarchy limit 5")
#> # A tibble: 5 x 5
#>                     hierarchy_string    tsn parent_tsn level childrencount
#> *                              <chr>  <int>      <int> <int>         <int>
#> 1                             202422 202422          0     0        154282
#> 2                      202422-846491 846491     202422     1          2666
#> 3               202422-846491-660046 660046     846491     2          2654
#> 4        202422-846491-660046-846497 846497     660046     3             7
#> 5 202422-846491-660046-846497-846508 846508     846497     4             6

use dplyr verbs

get a tbl

hiers <- src %>% tbl("hierarchy")
#> # Source:   table<hierarchy> [?? x 5]
#> # Database: postgres 9.6.0 [[email protected]:5432/ITIS]
#>                                              hierarchy_string    tsn parent_tsn level childrencount
#>                                                         <chr>  <int>      <int> <int>         <int>
#>  1                                                     202422 202422          0     0        154282
#>  2                                              202422-846491 846491     202422     1          2666
#>  3                                       202422-846491-660046 660046     846491     2          2654
#>  4                                202422-846491-660046-846497 846497     660046     3             7
#>  5                         202422-846491-660046-846497-846508 846508     846497     4             6
#>  6                  202422-846491-660046-846497-846508-846553 846553     846508     5             5
#>  7           202422-846491-660046-846497-846508-846553-954935 954935     846553     6             3
#>  8      202422-846491-660046-846497-846508-846553-954935-5549   5549     954935     7             2
#>  9 202422-846491-660046-846497-846508-846553-954935-5549-5550   5550       5549     8             0
#> 10           202422-846491-660046-846497-846508-846553-954936 954936     846553     6             0
#> # ... with more rows

select certain fields

hiers %>% select(tsn, level)
#> # Source:   lazy query [?? x 2]
#> # Database: postgres 9.6.0 [[email protected]:5432/ITIS]
#>       tsn level
#>     <int> <int>
#>  1 202422     0
#>  2 846491     1
#>  3 660046     2
#>  4 846497     3
#>  5 846508     4
#>  6 846553     5
#>  7 954935     6
#>  8   5549     7
#>  9   5550     8
#> 10 954936     6
#> # ... with more rows

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