pandasql
sqldf for pandas
Decision gist · record as of 2026-08-14
No. The package is abandoned (last release 2016, no commits since July 2024 in archived repo) and has high install friction. Modern alternatives like DuckDB or Polars provide SQL-on-DataFrames with active maintenance, better performance, and compatibility with current Python versions. Use pandasql only if you have legacy code already depending on it; do not start new projects with it.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires pandas to be installed separately; no explicit Python version support declared.
- Abandoned package may have compatibility issues with modern Python and pandas versions.
- High install friction due to distribution format (egg and tarball only, no wheels).
License · maintenance · safety
(unclear) — MIT-like permissive license (copyright notice and permission text present) with no SPDX identifier recorded. Permissive for use but license treatment is marked unclear, so verify the exact terms before relying on it commercially.
last release 2016-04-20 (3768 days) · last repo commit 2024-07-24 · 1,349 stars · archived
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,963,671 downloads/mo, #3,405 on PyPI
Alternatives
Verify before relying
pip install pandasql
from pandasql import sqldf
pysqldf = lambda q: sqldf(q, globals())
result = pysqldf("SELECT * FROM my_dataframe LIMIT 10;")- Whether pandasql works with current pandas versions (last release 2016, pandas has evolved significantly)
- Exact Python version compatibility (requires_python is unspecified)
- Whether SQLite syntax coverage is complete for modern SQL features
What it is and what it does
pandasql is a thin wrapper that translates SQL queries into pandas operations, using SQLite syntax as the query language. It automatically detects pandas DataFrames in the calling scope and treats them as SQL tables, allowing you to write SELECT, JOIN, GROUP BY, and other SQL statements against them. The main entry point is the sqldf function, which takes a SQL query string and a namespace dict (typically globals() or locals()) to resolve DataFrame names.
The package was designed to lower the barrier for people familiar with SQL but new to pandas, providing a more intuitive interface for data manipulation and cleaning. However, it has been abandoned since 2016 with no active maintenance, creating significant compatibility concerns for modern Python and pandas environments.
Use it for
- Migrate SQL-based data workflows to Python without rewriting queries as pandas method chains
- Join multiple DataFrames using familiar SQL INNER/LEFT/RIGHT JOIN syntax
- Perform GROUP BY aggregations and window functions on DataFrames using SQL
- Prototype data transformations quickly if you think in SQL rather than pandas idioms
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
No.
The package is abandoned (last release 2016, no commits since July 2024 in archived repo) and has high install friction. Modern alternatives like DuckDB or Polars provide SQL-on-DataFrames with active maintenance, better performance, and compatibility with current Python versions. Use pandasql only if you have legacy code already depending on it; do not start new projects with it.
Install
pandasql on PyPI
Before you install
High install friction due to distribution format (egg and tarball only, no wheels). Package is abandoned as of 2016 with no maintenance since then, creating compatibility risk with modern Python and pandas versions.
Requires pandas to be installed separately; no explicit Python version support declared. Abandoned package may have compatibility issues with modern Python and pandas versions.
License in practice
MIT-like permissive license (copyright notice and permission text present) with no SPDX identifier recorded. Permissive for use but license treatment is marked unclear, so verify the exact terms before relying on it commercially.
Quickstart
pip install pandasql
from pandasql import sqldf
pysqldf = lambda q: sqldf(q, globals())
result = pysqldf("SELECT * FROM my_dataframe LIMIT 10;")Verify before relying
- Whether pandasql works with current pandas versions (last release 2016, pandas has evolved significantly)
- Exact Python version compatibility (requires_python is unspecified)
- Whether SQLite syntax coverage is complete for modern SQL features
Package facts
| License | Not declared unclear |
| Python support | Not specified |
| Install friction | High. Source build required |
| Runtime dependencies | None |
| Maintenance | Abandoned 3,768 days since the last release |
| Last repo commit | repository archived |
| First released | |
| Downloads | 1,963,671 / month, #3,405 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: pandasql-0.7.3-py2.7.egg; pandasql-0.7.3.tar.gz
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