# Get column definitions for the underlying table
columns = ouro.datasets.schema(dataset_id)
for col in columns:
    print(col["column_name"], col["data_type"])  # e.g., age integer, name text

# Option 1: All rows as a Pandas DataFrame
df = ouro.datasets.query(dataset_id)
print(df.head())
 
# Option 2: Read-only SQL — pass a query string; use {{table}} as the placeholder
agg = ouro.datasets.query(
    dataset_id,
    "SELECT col, count(*) AS n FROM {{table}} GROUP BY col ORDER BY n DESC",
)

import pandas as pd
 
# Update dataset metadata
updated = ouro.datasets.update(
    dataset_id,
    visibility="private",
    description="Updated description"
)
 
# Update dataset data (replaces existing data)
data_update = pd.DataFrame([
    {"name": "Charlie", "age": 33},
    {"name": "Diana", "age": 28},
])
updated = ouro.datasets.update(dataset_id, data=data_update)