17 रिपॉजिटरी
Frameworks that automatically generate statistical summaries and visual insights from raw datasets.
Distinct from Data Analysis: Distinct from general data analysis: focuses on the automation of the exploratory phase rather than strategic or manual analysis.
Explore 17 awesome GitHub repositories matching data & databases · Automated Exploratory Analysis. Refine with filters or upvote what's useful.
Chat2DB is an AI-powered SQL client and multi-database GUI manager designed for managing various relational and NoSQL database systems. It serves as a visual database management tool and a natural language to SQL interface, allowing users to convert plain text descriptions into executable and optimized queries. The platform distinguishes itself through automated business intelligence capabilities, which include the generation of real-time data visualization dashboards and AI-driven data analysis from spreadsheets. To ensure data privacy, it supports secure local AI deployment, enabling large
Provides AI-driven analysis of spreadsheet files to extract patterns and insights using natural language processing.
This library provides a diagnostic toolkit for automated data profiling and exploratory analysis. It generates comprehensive statistical summaries and visual reports for tabular datasets, enabling users to identify distribution patterns, missing values, and quality anomalies through a unified interface. The project distinguishes itself by offering differential analysis, which allows for the comparison of two dataset versions to track structural and statistical changes over time. It supports large-scale data processing through lazy evaluation and provides interactive widgets that embed directl
Automates the statistical summary and visualization of tabular datasets to identify patterns and quality issues.
This project is an exploratory data analysis framework and profiling tool designed to generate comprehensive statistical reports from Pandas and Spark DataFrames. It functions as a data quality profiler that identifies missing values, duplicates, and high correlations within tabular datasets. The tool distinguishes itself through specialized capabilities for time-series analysis, extracting temporal statistics, seasonality, and auto-correlation plots. It also includes a dataset comparison utility to identify structural or content changes between different versions of a dataset. The analysis
Provides a framework that automatically generates statistical summaries and visual insights from tabular datasets.
This project is an exploratory data analysis library and profiling tool for Pandas and Spark DataFrames. It automates the initial investigation of datasets by generating comprehensive descriptive analysis reports, statistical summaries, and data quality warnings. The system functions as a data quality profiler to detect missing values, duplicate rows, and type inconsistencies. It includes a dataset comparison tool for identifying structural and content shifts between different versions of the same data, as well as specialized tools for time-series analysis to calculate auto-correlation and se
Automatically generates statistical summaries and visual insights to facilitate the initial investigation of datasets.
This project is a data profiling and exploratory data analysis tool designed to generate automated quality reports for Pandas and Spark dataframes. It serves as a system for computing descriptive statistics, identifying correlations, and analyzing univariate and multivariate data patterns. The tool provides specialized capabilities for comparing different versions of datasets to identify changes in data quality and distributions. It includes a dedicated profiler for time-dependent data to extract statistical information such as seasonality and auto-correlation. The software covers a broad an
Automatically generates statistical summaries and visual insights to discover patterns and anomalies in new datasets.
Ydata-profiling is an automated exploratory data analysis framework designed to generate comprehensive statistical reports and visual summaries from dataframes. It functions as a diagnostic tool for assessing data quality, identifying missing values, duplicates, and outliers, while providing a scalable engine for profiling massive datasets across distributed enterprise environments. The project distinguishes itself through its ability to handle large-scale data through distributed task orchestration and lazy stream processing, which minimizes memory overhead during complex computations. It in
Provides an automated framework for discovering data distributions, correlations, and quality issues within large datasets.
This project is an AI-powered IDE extension and LLM coding assistant that provides a conversational interface for generating, refactoring, and debugging code. It functions as an AI agent framework and a Model Context Protocol client, connecting AI models to external data sources and tools to automate complex development tasks. The system is distinguished by its use of autonomous AI agents capable of multi-step task execution, including the ability to read files, modify code, and run terminal commands iteratively. It supports recursive agent orchestration through subagent delegation and employ
Automatically generates a complete data analysis workflow, including notebook scaffolding and visualization code.
GrowthBook is a feature flagging and experimentation platform that utilizes a warehouse-native approach to data analysis. It serves as a system for managing feature rollouts and conducting A/B tests by executing SQL queries directly against existing data warehouses to calculate experiment results. The platform is distinguished by its integration of a Model Context Protocol server, which allows AI coding assistants and IDEs to manage flags and query analytics using natural language. It also provides specialized capabilities for AI model optimization, enabling the testing of prompts and models
Generates automated drill-down analyses for a single metric across multiple dimensions.
Osmedeus is a security workflow orchestration engine that coordinates AI agents, shell commands, and scanning tools through declarative YAML pipelines. It functions as a distributed security scanner, a declarative workflow automator, and an AI agent framework for security, enabling automated multi-step security analysis with conditional branching, parallel execution, and distributed workers. The engine distinguishes itself through a hybrid runner model that executes workflow steps on the local host, inside Docker containers, or over SSH to remote machines, selected per step or module. It supp
Sends prompts to language models and exports generated analysis for use in subsequent workflow steps.
Lux is an automated exploratory data analysis tool designed to generate intelligent visual representations of pandas dataframes. It identifies patterns and trends by recommending optimal chart types and axis mappings based on the statistical attributes of a dataset. The tool functions as an interactive data profiling layer that allows users to browse and query collections of charts using filters and wildcards. It also serves as a visualization code generator, translating automatically produced charts into programmatic code or HTML for manual refinement in external libraries. The system cover
Automates the exploratory data analysis process by recommending optimal chart types and axis mappings based on dataset attributes.
Visual Insights is an automated exploratory data analysis platform and causal inference tool designed to discover patterns and cause-and-effect relationships within datasets. It functions as an interactive data visualization library using a grammar-of-graphics approach to generate multi-dimensional charts and dashboards. The project distinguishes itself through a natural language interface that translates plain-text questions into data answers and visualizations via a language model. It provides a specialized framework for causal discovery and inference, allowing users to identify variable li
Discovers patterns and trends in unfamiliar datasets using automated agents to generate multi-dimensional visualizations.
EQGRP is a remote access trojan framework and post-exploitation toolkit. It provides a centralized command and control infrastructure for deploying persistent implants and managing remote agents across diverse operating systems. The project includes tools for digital forensic evasion, such as modifying system logs and filesystem timestamps to remove execution traces. It features a network interception system for capturing and reconstructing data streams by hooking into the system root, as well as exploits designed for kernel privilege escalation to elevate process permissions to administrativ
Parses telecommunications call detail records to extract structured data for analysis.
This project is a curated library of Python code examples, educational resources, and programming tutorials. It functions as an educational repository designed to teach Python language fundamentals through practical implementation tasks, real-world exercises, and functional code snippets. The collection covers a diverse range of implementation examples, including the development of interactive websites and message boards using web frameworks. It also features scripts for audio speech processing, automated media processing for images, and the extraction of data from web content. Additional ca
Parses call detail records from spreadsheets and computes total talk time per month.
Positron is a data science integrated development environment and AI-powered code editor designed for polyglot development, specifically supporting Python and R. It functions as a remote compute workspace that separates the user interface from the execution kernel via SSH or container integration. The environment features a deep integration of large language models that provide context-aware suggestions and automated data analysis by accessing real-time interpreter state, in-memory objects, and plot outputs. It distinguishes itself through a polyglot runtime bridge that enables cross-language
Automatically generates and executes statistical summaries and visualizations to uncover insights from datasets.
This project provides a programmatic interface and framework for integrating large language models with secure, stateful, and multimodal code execution environments. It functions as a code interpreter API that enables the execution of arbitrary Python scripts within isolated sandboxed runtimes. The system supports multimodal data analysis by processing combined text and file inputs to generate visualizations and computational results. It manages stateful workflows by maintaining conversation memory and session history, allowing language models to complete multi-step technical tasks. The fram
Automates the generation of statistical summaries and visual reports by dynamically executing analysis scripts.
IronCalc is an XLSX spreadsheet engine and formula evaluator designed to compute numerical expressions and manage workbook structures. It utilizes a logic engine compatible with industry standards to evaluate formulas and manage cell dependencies. The project provides a comprehensive suite of specialized toolkits, including a financial calculation library for bond pricing and net present value, and an engineering math toolkit for complex number arithmetic and Bessel functions. It also features a web-based spreadsheet interface for creating and formatting workbooks. The engine covers a broad
Enables the creation of automated workflows to filter, sort, and aggregate large datasets using database-style criteria.
PromptX is an LLM agent orchestration framework designed to execute multi-step workflows using autonomous agents. It features a sandboxed tool execution environment for secure filesystem operations and external API integrations, alongside a persona management system that defines professional roles and domain expertise to control agent behavior. The system implements a semantic memory network for persistent knowledge storage, utilizing graph-based memory and engrams to retain information across sessions. This cognitive memory includes specialized tools for knowledge graph visualization, allowi
Processes Excel files to generate insights, automate reports, and create data visualizations.