nicolaskruchten/pivottable

Features

• Pivot Table Visualizations - Provides a JavaScript library for creating interactive pivot tables with drag-and-drop grouping and aggregation.
• Dynamic Analysis Interfaces - Provides a drag-and-drop interface that lets users rearrange rows and columns to explore datasets dynamically.
• Derived Feature Generation - Creates new data dimensions using date derivers or custom logic to refine how data is grouped.
• Analytical Aggregation Schemas - Processes raw datasets through a dictionary of mathematical functions to produce summarized values.
• Client-Side Data Analysis - Enables loading CSV or JSON files directly in the browser to perform pivot analysis without a backend server.
• Client-Side Data Ingestors - Loads datasets from CSV files, object arrays, nested arrays, callback functions, or HTML tables.
• Drag-and-Drop Reorderers - Provides a drag-and-drop interface for rearranging rows and columns to explore data dynamically.
• Client-Side CSV Parsers - Imports CSV files and JSON arrays to perform local statistical summaries in the browser.
• Statistical Aggregators - Computes standard statistical summaries including sums, averages, medians, and unique value counts.
• Dataset Explorers - Offers a visual interface for transforming raw datasets into summarized tables and heatmaps.
• Custom Aggregators - Computes statistical summaries and custom mathematical operations to transform large datasets into summaries.
• Data Dimension Derivations - Provides the ability to create new data dimensions through date binning and custom categorization logic.
• Data Explorers - Provides an interface for dynamically exploring datasets by dragging and dropping fields to group and summarize information.
• Custom Calculation Logics - Supports user-defined functions to implement custom non-count logic for summarizing data values.
• Browser-Based Data Processing - Processes and visualizes pivoted data as charts using D3 and C3 directly within the browser.
• Report Generation - Converts raw data into formatted cross-tab tables and charts for customized reporting.
• External Chart Library Integration - Integrates with third-party graphing libraries like D3 and C3 to render pivot analysis as charts.
• Tabular Data Sorting - Provides the ability to order rows in the pivot table based on column values and totals.
• Aggregator Selection Interfaces - Provides an interface for users to select aggregation functions and target attributes from a defined dictionary.
• Chart Generators - Converts pivot results into integrated visual charts including bar, line, stacked, and pie charts.
• Custom Data-to-DOM Renderers - Supports custom visualization logic to connect a data model directly to the document object model.
• Table Visualizations - Renders datasets as interactive tables with heatmaps and embedded bar charts to highlight data patterns.
• Cell-Level Interaction Callbacks - Executes custom callback functions when clicking a cell to reveal the underlying raw records.
• Multi-Format Data Rendering - Transforms datasets into multiple visual interfaces, including HTML tables, charts, and TSV exports.
• HTML Tables - Generates the final pivot table as a semantic HTML table structure in the browser.
• JavaScript Charting Libraries - Uses JavaScript to create interactive tables, heatmaps, and charts that reveal patterns within raw datasets.

Istoric stele