Apache Superset is a Data Visualization and Data Exploration Platform
- superset
- apache
- apache-superset
- data-visualization
Repository Index
47,133 repositories indexed
1–24 of 147 · Most stars
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
- data-analysis
- pandas
- flexible
- alignment
Kronos: A Foundation Model for the Language of Financial Markets
Streamlit — A faster way to build and share data apps.
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
- machine-learning
- models
- ui
- ui-components
🕸️ Web apps in pure Python 🐍
- python
- framework
- open-source
- gui
Data Apps & Dashboards for Python. No JavaScript Required.
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
- notebooks
- python
- data-science
- machine-learning
matplotlib: plotting with Python
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
Best Practices on Recommendation Systems
- machine-learning
- recommender
- ranking
- deep-learning
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
- forecasting
- r
- python
Turns Data and AI algorithms into production-ready web applications in no time.
Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
- ipython
- jupyter
- data-science
- python
Topic Modelling for Humans
- gensim
- topic-modeling
- information-retrieval
- machine-learning
🦉 Data Versioning and ML Experiments
- data-science
- machine-learning
- reproducibility
- data-version-control
Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through R&D-Agent, which lets AI drive data-driven AI. 🔗https://aka.ms/RD-Agent-Tech-Report
- agent
- ai
- automation
- data-mining
100 numpy exercises (with solutions)
Statistical data visualization in Python
Parallel computing with task scheduling
- dask
- python
- pydata
- numpy
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
- pandas-profiling
- pandas-dataframe
- statistics
- jupyter-notebook
NumPy & SciPy for GPU
- cuda
- cudnn
- cublas
- cusolver
Rich MySQL Terminal Client with AutoCompletion, Syntax Highlighting, and Dataframes