ncbi_taxonomy.divisions

Python

In [1]:

import bedrock_bio as bb

rel = bb.load_table('ncbi_taxonomy.divisions')

df = rel.limit(5).pl()  # Polars
df = rel.limit(5).df()  # Pandas
df.head()

Out[1]:

	sources	division_id	genbank_division_code	name	comment
0	[{'url': 'https://ftp.ncbi.nlm.nih.gov/pub/tax...	0	BCT	Bacteria	NaN
1	[{'url': 'https://ftp.ncbi.nlm.nih.gov/pub/tax...	1	INV	Invertebrates	NaN
2	[{'url': 'https://ftp.ncbi.nlm.nih.gov/pub/tax...	10	VRT	Vertebrates	NaN
3	[{'url': 'https://ftp.ncbi.nlm.nih.gov/pub/tax...	11	ENV	Environmental samples	Anonymous sequences cloned directly from the e...
4	[{'url': 'https://ftp.ncbi.nlm.nih.gov/pub/tax...	2	MAM	Mammals	NaN

R

In [1]:

library(bedrockbio)

lf <- load_table("ncbi_taxonomy.divisions")
df <- head(lf, 5) |> collect()

head(df)

Out[1]:

Sample output (5 rows, showing 4 of 5 columns)
   division_id | genbank_division_code | name                  | comment
   ----------- | --------------------- | --------------------- | ------------------------
0  0           | BCT                   | Bacteria              | —
1  1           | INV                   | Invertebrates         | —
2  10          | VRT                   | Vertebrates           | —
3  11          | ENV                   | Environmental samples | Anonymous sequences clo…
4  2           | MAM                   | Mammals               | —

Description

NCBI Taxonomy divisions used by taxonomy nodes, one row per division.

Partitions

Not partitioned.

Schema

Column	Type	Description
sources	STRUCT(url TEXT, filename TEXT, last_modified_at TIMESTAMPTZ, sha256 TEXT)[]	Source provenance for the row.
division_id	TEXT	NCBI Taxonomy division ID.
genbank_division_code	TEXT	Three-character GenBank division code, such as BCT, PLN, VRT, or MAM.
name	TEXT	NCBI division name.
comment	TEXT	Free text NCBI division comment, if supplied.