3 रिपॉजिटरी
Generates automated statistical reports and visual summaries specifically for tabular dataframes.
Distinct from Profiling Reports: Distinct from Profiling Reports: focuses on the specific integration with the pandas ecosystem for tabular data profiling.
Explore 3 awesome GitHub repositories matching data & databases · Pandas Profiling Tools. Refine with filters or upvote what's useful.
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
Generates automated statistical reports and visual summaries for tabular data to identify quality issues.
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
Integrates with pandas to inject interactive visualization components directly into notebook outputs.
dtale is a web-based interactive grid and visualizer for pandas dataframes, designed as an exploratory data analysis tool. It provides a browser-based interface for analyzing tabular data structures, allowing users to calculate statistics, detect outliers, and compute correlations without writing manual code. The project functions as an embedded data viewer that can be integrated into web applications via iframes or custom routes, with specific support for Django, Flask, and Streamlit. It enables the exploration of datasets through a combination of an interactive data grid and a data visualiz
Provides a web-based interactive grid specifically for exploring, filtering, and analyzing pandas data structures.