pandas-td

What it is and what it does

Pandas-TD is a deprecated bridge between pandas and Treasure Data, a cloud data warehouse. It lets you run SQL queries against Treasure Data tables and pull results directly into pandas DataFrames for local analysis, or write DataFrames back to Treasure Data tables. The package integrates with Jupyter notebooks via magic functions for interactive querying.

The package is no longer maintained and was archived in 2020. The maintainers explicitly recommend using pytd instead for any new work. If you have existing code using pandas-td, migration to pytd is the supported path forward.

Use it for:

• Pull Treasure Data query results into pandas for exploratory data analysis and visualization.
• Load a Treasure Data table into a DataFrame with optional row limits for sampling large datasets.
• Write analysis results from a pandas DataFrame back to a Treasure Data table for persistence and sharing.
• Use Jupyter magic functions to interactively query Treasure Data without writing explicit Python code.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Pandas-TD connects pandas DataFrames to Treasure Data's cloud analytics platform, enabling you to query and load data from Treasure Data into pandas for analysis and write results back to tables.

No. The package is abandoned, archived since 2020, and the maintainers explicitly direct users to pytd instead. Do not install for new projects. If you have legacy code using pandas-td, plan a migration to pytd.

Install

pandas-td on PyPI

pip install pandas-td

uv add pandas-td

poetry add pandas-td

Installing pandas-td

Before you install

Installation is straightforward with no runtime dependencies, but the package is abandoned as of 2020-03-25 and archived on GitHub. The maintainers explicitly recommend migrating to pytd instead.

License in practice

Licensed under Apache License 2.0 (permissive), so commercial and private use are unrestricted, but the package is no longer maintained.

Quickstart

pip install pandas-td

import pandas_td as td
engine = td.create_engine('presto:sample_datasets')
df = td.read_td('select * from www_access', engine)

Requires a Treasure Data account and API key (set via TD_API_KEY environment variable) to authenticate queries.

Verify before relying

• Whether the package still works with current versions of pandas and Python given its 2020 abandonment date.
• Whether Treasure Data's backend API has changed in ways that would break this client since its last release.

Package facts

Evidence: pandas_td-0.10.0-py2.py3-none-any.whl

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