Superset Accessor for Pandas DataFrames 🚀

Note: The code docs AI-generated so may not be perfect (or even right lol).

Upload your DataFrame to Superset as a dataset for rapid visualization.

Notes

• Ensure you have a database or datasource in Superset that supports CSV uploads.
• Ensure API access is enabled.
• To maintain a clean and organized Superset environment:
  • Within Superset create a dedicated database or datasource (specified by the database_name parameter in the configure function) for this package.
  • Consistently use the same database or datasource name when uploading data, as the package overwrites existing data by default.
• Call SupersetAccessor.configure at least once before using the as_dataset accessor.

Installation

Install the package via pip:

pip install dataframe-to-superset

Usage

import pandas as pd
from dataframe_to_superset import SupersetAccessor

SupersetAccessor.configure(
    base_url="https://superset",
    username="your_username",
    password="your_password",
    provider="your_auth_provider",  # e.g., "ldap" or "db"
    database_name="your_database_name",
    schema="your_schema_name",  # optional, defaults to "public"
)

data = {"name": ["Alice", "Bob"], "age": [25, 30]}
df = pd.DataFrame(data)

url = df.superset.as_dataset("people")
print(url)

# Another example
data = {"animal": ["Wolf", "Cat"], "Sound": ["Howl", "Meow"]}
df = pd.DataFrame(data)

url = df.superset.as_dataset("animal_sounds", verbose_return = True)
print(url)

Configuration Parameters for configure Function

Parameters for as_dataset Method

Return Types for as_dataset Method