Data Science & Numerical Computing Packages
Numerical computing, dataframes, and scientific-analysis libraries used across research and production data pipelines (NumPy, pandas, SciPy).
Packages in Data Science & Numerical Computing
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pandas
The Python DataFrame library for fast, flexible, and expressive data analysis and manipulation.
Datasets
One-line loading and fast, Arrow-backed processing for thousands of ML datasets
Seaborn
A Python statistical data visualization library built on matplotlib, for attractive charts with minimal code
PySpark
Python API for Apache Spark, the unified engine for large-scale distributed data processing
yfinance
Pythonic access to Yahoo Finance market data, returned as ready-to-use pandas DataFrames.
Apache DataFusion
The extensible, Arrow-native SQL and DataFrame query engine for building fast analytical systems in Rust.
deltalake
Native Rust-powered Python binding for Delta Lake, giving pandas, Polars, and Arrow workflows ACID table reads and writes without a JVM.
GeoPandas
Add support for geographic vector data to pandas dataframes
marimo
A reactive Python notebook that's reproducible, git-friendly, and deployable as scripts or apps.
Ibis
A portable Python dataframe library with a lazy expression API across 20+ backends.
AWS SDK for pandas
Pandas on AWS - integrate DataFrames with Athena, Glue, Redshift, S3, and more.
chDB
In-process OLAP SQL engine powered by ClickHouse, embedded directly in Python
ConnectorX
The fastest, most memory-efficient way to load data from databases into Python and Rust DataFrames.
tabula-py
Extract tables from PDF files directly into pandas DataFrames.
DataComPy
Compare Pandas, Polars, Spark, and Snowpark DataFrames with human-readable difference reports.
