No. 8 of 36 ·Data Transformation Tools

pandas

Windows · Mac · Linux · Self-hosted

Freedom report

Three barsScore 6.5

Free tierA free tier is on its own pricing page
Open codeNo open-source code on record
Runs widely3 of 6 device platforms
DocumentedPlans, terms and facts published

pandas is ranked #8 of 36 in data transformation tools on Freedom251. It runs on Linux, macOS, Self-hosted, Windows. There is a free plan.

pandas plans and pricing

All plans

pandas Free Open-source Python library · Install via conda-forge, PyPI, or source code pandas.pydata.org · 5 Oct 2026

Compared on data transformation tools

Deployment model: self_hosted
Transformation interface: code
Supported data formats: CSV, delimited text, fixed-width text, clipboard, Excel, OpenDocument, JSON, HTML, XML, LaTeX, HDF5, Feather, Parquet, Apache Iceberg, ORC, SQL, Google BigQuery, Stata, SAS, SPSS, Python Pickle
Data quality checks: Yes

Best pandas alternatives

See all 20

Two bars jq Free tier No. 1Free6.6 Two bars Apache Beam Free tier No. 2Free6.5 Two bars Bruin for Customer Success Free tier No. 3Free6.5 Two bars csvkit Free tier No. 4Free6.5 Two bars dbplyr Free tier No. 5Free6.5 Two bars KNIME Analytics Platform Free tier No. 6Free6.5

The record

Purpose: pandas is an open-source tool for data analysis and manipulation built on Python.
DataFrames: It provides an efficient DataFrame object for data manipulation with integrated indexing.
Data formats: It reads and writes formats including CSV, Excel, SQL, JSON, and Parquet.
Analysis: It supports filtering, summary statistics, custom aggregation, reshaping, pivoting, joins, and merges.
Time series: It includes tools for date, time, and time-indexed data, including date-range and frequency operations.
Visualization: It provides plotting that uses Matplotlib.
Integrations: Optional dependencies add features for Excel, SQL databases, cloud storage such as Amazon S3 and Google Cloud Storage, plotting, and other tasks.
Installation: The pandas development team distributes it through conda-forge, PyPI, and source code on GitHub.
Supported systems: The documentation describes installation on Linux, macOS, and Windows.
Dependencies: pandas requires NumPy and python-dateutil; tzdata is required on Windows and Pyodide.
Optional requirements: Some methods require optional dependencies; for example, reading HDF5 requires PyTables and Markdown output requires tabulate.
Performance: The library says critical code paths are written in Cython or C.
Project: The project is affiliated with the NumFOCUS Foundation and releases its software under a BSD or similar open-source license.
Support: The website directs users to ask questions on Stack Overflow and provides documentation and community tutorials.
Price from: Free

Where it ranks on Freedom251

Best Data Transformation Tools in 2026#8 of 36

Is pandas yours?

Claim it for free: prove the domain, then correct facts, plans and screenshots. An editor reviews every change.

Claim it free Promote pandas

Sources

pandas.pydata.org· checked 5 Oct 2026
pandas.pydata.org/about/index.html· checked 5 Oct 2026
pandas.pydata.org/docs/getting_started/index.html· checked 5 Oct 2026
pandas.pydata.org/pandas-docs/stable/getting_started/inst· checked 5 Oct 2026
pandas.pydata.org/about/governance.html· checked 5 Oct 2026