ncbi_taxonomy.hosts

Python

In [1]:

import bedrock_bio as bb

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

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

Out[1]:

	sources	taxon_id	potential_hosts
0	[{'url': 'https://ftp.ncbi.nlm.nih.gov/pub/tax...	1000288	[human, vertebrates]
1	[{'url': 'https://ftp.ncbi.nlm.nih.gov/pub/tax...	1000289	[human, vertebrates]
2	[{'url': 'https://ftp.ncbi.nlm.nih.gov/pub/tax...	1000290	[human, vertebrates]
3	[{'url': 'https://ftp.ncbi.nlm.nih.gov/pub/tax...	1000291	[human, vertebrates]
4	[{'url': 'https://ftp.ncbi.nlm.nih.gov/pub/tax...	1000292	[human, vertebrates]

R

In [1]:

library(bedrockbio)

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

head(df)

Out[1]:

Sample output (5 rows, showing 1 of 3 columns)
   taxon_id
   --------
0  1000288
1  1000289
2  1000290
3  1000291
4  1000292

Description

Theoretical hosts reported by NCBI for taxonomy nodes, one row per taxon.

Partitions

Not partitioned.

Schema

Column	Type	Description
sources	STRUCT(url TEXT, filename TEXT, last_modified_at TIMESTAMPTZ, sha256 TEXT)[]	Source provenance for the row.
taxon_id	TEXT	Taxonomy ID for the organism with reported hosts.
potential_hosts	TEXT[]	Theoretical host names, split from NCBI’s comma-delimited field.