pandas-td
Pandas extension for Treasure Data
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a Treasure Data account and API key (set via TD_API_KEY environment variable) to authenticate queries.
- 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 · maintenance · safety
Apache License 2.0 (permissive) — Licensed under Apache License 2.0 (permissive), so commercial and private use are unrestricted, but the package is no longer maintained.
last release 2019-03-29 (2695 days) · last repo commit 2020-03-25 · 38 stars · archived
0 known vulnerabilities (OSV.dev, 2026-08-14) · 92,050 downloads/mo, #13,483 on PyPI
Alternatives
Verify before relying
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)- 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.
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The package is no longer maintained and was archived in 2020.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 on it.
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
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.
Requires a Treasure Data account and API key (set via TD_API_KEY environment variable) to authenticate queries.
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)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
| License | Apache License 2.0 permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Abandoned 2,695 days since the last release |
| Last repo commit | repository archived |
| First released | |
| Downloads | 92,050 / month, #13,483 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaEnvironment :: ConsoleFramework :: IPythonIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentTopic :: Software Development |
Evidence: pandas_td-0.10.0-py2.py3-none-any.whl
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See also pytd · td-client · pandas_access · gspread-dataframe · dtale · pandas-read-xml · df2gspread · qpd · gspread-pandas · pandasql