Visualize and compare datasets, target values and associations, with one line of code.
Repository Index
47,133 repositories indexed
25–47 of 47 · Most stars
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps. https://deepnote.com/
App to easily query, script, and visualize data from every database, file, and API.
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
A Python package for manipulating 2-dimensional tabular data structures
Build data pipelines with SQL and Python, ingest data from different sources, add quality checks, and build end-to-end flows.
What's in your data? Extract schema, statistics and entities from datasets
:truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
visual data prep powered by python
This repository is a getting started guide to Singer.
NFStream: a Flexible Network Data Analysis Framework.
Visualize large time series data with plotly.py
EvoOntology: A Self-Evolving Ontology Layer for Data Agents ⚙️ EvoOntology插件为Claude Code/Codex 建立&进化本体层
cell detection in calcium imaging recordings
High-assurance AI data visualization IDE & analytics workbench. Natural language to charts with local ground-truth table verification.
CLI utility and Python module for analyzing log files and other data.
The power of Chart.js with Python
Go's answer to pandas + scikit-learn: a batteries-included data analysis library with dataframes, statistics, machine learning, quant, and GPU acceleration. Run Python with seamless two-way variable sharing, or explore data straight from the Insyra CLI.
Turn CSV, Excel, and read-only databases into verified, editable business reports.
Quanfima (Quantitative Analysis of Fibrous Materials)
A lightweight Python package for teaching computational methods through art history. Extract and analyze artist-specific works from WikiArt with built-in visualizations. Designed for digital humanities and computational design courses. Features genre/style analysis, matplotlib integration, and pedagogical clarity over algorithmic complexity.