Autoplot

20d ago

Autoplot is a native macOS application that unifies data import, analysis, plotting, and publishing in a single workspace. It lets users import CSV or other tabular data from local files or SFTP, merge files, set delimiters, headers, and encoding, and apply Python‑based transformations locally. The tool includes a full scientific toolkit with plot types (X‑Y, histograms, heat maps, 3D scatter/surface/line plots, categorical charts) and analysis utilities (CCDF, AUC, log‑binned distributions, power‑law fits, scaling relations, correlation matrices and networks). An AI assistant provides conversational help, generates Python/Matplotlib code, and executes actions locally while preserving data privacy. Results can be exported as print‑ready vector PDFs, PNG, JPG, or Python scripts, and multi‑panel figures can be composed and re‑exported without rerunning scripts.

Data ImportPython Flexibility on ImportAnalysis ToolkitPlotting SuiteAI AssistantExport & PublishingLocal‑First Architecture

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Last Updated20d ago

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Key Capabilities

Data Import

Import data from local files or SFTP with one click, set delimiters, headers, encoding, and merge multiple files without writing code.

Python Flexibility on Import

Apply splicing, filtering, or derived columns using assistant‑generated Python that runs locally.

Analysis Toolkit

Perform scientific analyses including CCDF, AUC, log‑binned distributions, power‑law and truncated fits, scaling relations, correlation matrices, and network generation.

Plotting Suite

Create X‑Y plots, histograms with custom fits, heat maps with Gaussian/mixture fits, 3D scatter/surface/line plots, and categorical charts.

AI Assistant

Conversational interface that reads intent and schema, generates Python/Matplotlib code, and runs actions locally while ensuring data never leaves the device.

Export & Publishing

Export figures as print‑ready vector PDFs at journal DPI, PNG, JPG, or as Python scripts; compose multi‑panel boards that update dynamically.

Local‑First Architecture

Runs entirely on the Mac (Apple Silicon optimized), with no cloud upload, ensuring full data privacy and offline capability.

Use Cases

Use CaseDescriptionFor

Student CourseworkCreate publication‑quality plots and PDFs from lab CSV files without building a pipeline, enabling quick turnaround for assignments.Students

Scientific ResearchFit heavy‑tail distributions, inspect diagnostics, and generate reproducible Python code for peer review and journal submission.Scientists

R&D Data AnalysisAnalyze confidential datasets locally, using the full toolkit and AI assistant without any data upload to the cloud.R&D Teams

Update History

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