Learn how to connect several essential tools to develop a simple yet intuitive dashboard using Streamlit, Plotly, DuckDB, and Pandas to visualize data from a JSON file.
This page details the command-line utility for the Embedding Atlas, a tool for exploring large text datasets with metadata. It covers installation, data loading (local and Hugging Face), visualization of embeddings using SentenceTransformers and UMAP, and usage instructions with available options.
This video course introduces DuckDB, an open-source database for data analytics in Python. It covers creating databases from files (Parquet, CSV, JSON), querying with SQL and the Python API, concurrent access, and integration with pandas and Polars.
Use a new spreadsheet app to analyze large CSV files fast and locally.
An in-process analytics database, DuckDB can work with surprisingly large data sets without having to maintain a distributed multiserver system. Best of all? You can analyze data directly from your Python app.
