Search Results for "statistical graphs"

plotly.py is a browser-based, open source graphing library for Python that lets you create beautiful, interactive, publication-quality graphs. Built on top of plotly.js, it is a high-level, declarative charting library that ships with more than 30 chart types. Everything from statistical charts and scientific charts, through to maps, 3D graphs and animations, plotly.py lets you create them all. Graphs made with plotly.py can be viewed in Jupyter notebooks, standalone HTML files, or hosted online using Chart Studio Cloud.

TAVIA is a desktop application for structured data analysis, visualization, reporting, and reproducible research workflows. It combines spreadsheet-style data handling with statistical tools, publication-ready graphs, confidence intervals, project files, encrypted storage, audit trails, workflow automation, and extensible plugins. The application includes CSV, TSV, XLSX, and SQLite import and export, customizable chart styles, confidence bands, error bars, report generation, generated analysis scripts, parameter sweeps, and a documented plugin API with a starter template. ...

...By automating the visualization process, AutoViz allows users to rapidly explore datasets before applying machine learning models or statistical analysis.

...FuzzBench integrates with the OSS-Fuzz infrastructure, allowing it to run experiments on authentic open source projects and collect meaningful data on crash discovery rates, code coverage, and bug-finding efficiency. The service includes an easy-to-use API for integrating custom fuzzers and an automated reporting system that generates detailed statistical analyses, comparative graphs, and significance testing. By running experiments at Google scale, FuzzBench ensures consistent, unbiased, and data-driven evaluations that support academic and industrial fuzzing research.