Tags Dataset Schema
The tags dataset contains all tag definitions used for categorizing markets. Tags provide a way to filter and group related markets.
Updated Daily
This dataset is updated daily after normalized files are generated.
Download
curl -L "https://api.telonex.io/v1/datasets/polymarket/tags" -o tags.parquet
import pandas as pd
df = pd.read_parquet("https://api.telonex.io/v1/datasets/polymarket/tags")
Or using the Python SDK:
from telonex import get_tags_dataframe
df = get_tags_dataframe(exchange="polymarket")
Schema
| Field | Type | Description |
|---|---|---|
exchange | string | Exchange name (e.g., polymarket). |
tag_id | string | Unique identifier for the tag (Polymarket's internal ID). |
tag_slug | string | URL-friendly identifier (e.g., politics, sports, crypto). |
tag_label | string | Human-readable display label (e.g., "Politics", "Sports", "Crypto"). |
Example: List All Tags
from telonex import get_tags_dataframe
tags = get_tags_dataframe(exchange="polymarket")
print(tags[['tag_slug', 'tag_label']].to_string())
Example: Find Markets by Tag
The tags field in the markets dataset contains a list of tag slugs. To find markets with a specific tag:
from telonex import get_markets_dataframe
df = get_markets_dataframe(exchange="polymarket")
# Find all markets tagged with "politics"
politics_markets = df[df['tags'].apply(lambda t: 'politics' in t)]
print(f"Found {len(politics_markets)} politics markets")
print(politics_markets[['slug', 'question']].head())