metadata
dataset_info:
features:
- name: tag_string
dtype: string
- name: month
dtype: string
- name: tag_count
dtype: int64
- name: tag_type
dtype: string
splits:
- name: train
num_bytes: 441037453
num_examples: 9157080
download_size: 45256839
dataset_size: 441037453
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataproc5/metrics-danbooru2025-tag-counts
import unibox as ub
from dataproc5.pipelines.danbooru.nodes import count_tags_by_month
df = ub.loads("hf://trojblue/danbooru2025-metadata").to_pandas()
tag_counts = count_tags_by_month(df)
Dataset Overview
tag_count
provides aggregated tag usage statistics from the Danbooru2025 dataset. Each entry corresponds to a specific tag's usage count, grouped by month and tag type.
Columns
tag_string
: The text of the tag (e.g., "landscape").month
: The month inYYYY-MM
format when the tag was used.tag_count
: The total occurrences of the tag in the given month.tag_type
: The category of the tag:"artist"
: Artist names."character"
: Character names."copyright"
: Copyrighted works or IPs."general"
: General descriptive tags."meta"
: Meta information tags.
Source Data
- Derived from Danbooru2025 image metadata.
- Tags are extracted from columns:
tag_string_artist
,tag_string_character
,tag_string_copyright
,tag_string_general
, andtag_string_meta
.
dataproc5/metrics-danbooru2025-monthly-tag-counts
(Auto-generated summary)
Basic Info:
- Shape: 9157080 rows × 4 columns
- Total Memory Usage: 1.77 GB
- Duplicates: 0 (0.00%)
Column Stats:
Error generating stats table.
Column Summaries:
→ tag_string (object)
- Unique values: 859311
→ month (object)
- Unique values: 240
→ tag_count (int64)
- Min: 1.000, Max: 119913.000, Mean: 36.142, Std: 544.501
→ tag_type (object)
- Unique values: 5
- 'general': 3201711 (34.96%)
- 'artist': 2907214 (31.75%)
- 'character': 2413530 (26.36%)
- 'copyright': 585905 (6.40%)
- 'meta': 48720 (0.53%)
Sample Rows (first 3):
tag_string month tag_count tag_type
! 2005-05 2 general
! 2005-06 16 general
! 2005-07 11 general
Usage Example:
import unibox as ub
df = ub.loads("hf://dataproc5/metrics-danbooru2025-monthly-tag-counts").to_pandas()
Saving to dataset:
import unibox as ub
ub.saves(df, "hf://dataproc5/metrics-danbooru2025-monthly-tag-counts")
(last updated: 2025-04-18 23:24:01.068022)