Name: igraph
Author: Open Source

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igraph is a collection of network analysis tools developed by the igraph core team. According to the vendor, the product aims to provide efficient, portable, and user-friendly solutions for various industries. The vendor states that igraph is suitable for companies of all sizes, from small startups to large enterprises. Professionals in fields such as data science, network analysis, social science, bioinformatics, computational biology, network research, and computer science rely on igraph to create, manipulate, analyze, and visualize networks. The following key features are highlighted by the vendor:

**Network Analysis Tools**: igraph offers a comprehensive set of network analysis tools, including algorithms for calculating centrality measures, community detection, network motifs, shortest paths, graph isomorphism, and more. These tools are designed to help users gain insights into the structure and properties of networks, identify important nodes and communities, and analyze various network characteristics.

**Graph Manipulation**: igraph provides functions for creating, manipulating, and modifying graphs. According to the vendor, users can easily add and remove nodes and edges, merge and split graphs, and subset graphs based on node or edge attributes. These capabilities allow users to customize and transform graphs according to their specific needs, update node and edge attributes, and modify graph structures.

**Network Visualization**: igraph offers various visualization options to represent networks in a visually appealing and informative manner. The vendor states that users can customize the appearance of nodes and edges, apply different layout algorithms to arrange the network layout, and create interactive visualizations to explore and present network data effectively.

**Graph Conversion**: According to the vendor, igraph provides functions for converting graphs between different formats, facilitating interoperability and collaboration in the network science community. Users can seamlessly exchange graph data with other network analysis libraries and tools, including networkx, graph-tool, and various file formats (e.g., GraphML, Pajek, GML).

**Language Support**: igraph supports multiple programming languages, including R, Python, Mathematica, and C/C++. The vendor claims that this flexibility allows users to leverage igraph's functionality in their preferred language and integrate it into their existing data analysis workflows.

**Portability and Efficiency**: The vendor emphasizes that igraph is designed with a focus on portability and efficiency. Implemented in C and offering bindings for different programming languages, igraph is optimized for analyzing large-scale networks and handling computationally intensive tasks.

**Active Development**: igraph is actively developed and maintained by the igraph core team. The vendor states that regular updates and bug fixes are released to improve the functionality, stability, and performance of the library. The development team is responsive to user feedback and actively engages with the community to ensure that igraph remains a reliable and up-to-date tool for network analysis.


igraph is a collection of network analysis tools. igraph can be programmed in R, Python, C/C++, and Mathematica.

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Demo de spots, cortinillas, rubricas de entrada, animaciones 2D y 3D de logotipos, intros y backgrounds de iGraph animacion. www.igraph.es msn: alberto_torres@igraph.es

iGraph demo reel

A demo of the ont-app IGraph protocol in a Clojure REPL

iGraph demo 3D

demo tv branding iGraph

iGraph demo Produccion de video

demo vfx iGraph

Graph Math Equations with iGraph - Demo

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Data Discovery and Visualization is the analysis of multiple data sources in a search for patterns and outliers and the ability to represent the data visually.

Pre-built visualization formats (heatmaps, scatter plots etc.)

Pre-built visualization formats are canned visualization types that can be selected to visualize different kinds of data.

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Location analytics is the visualization of geographical or spatial data.

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Predictive Analytics is the ability to build forecasting models based on existing data sets.

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Machine learning refers to computer programs that can learn when exposed to new data.

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Pattern recognition and data mining mean the ability to recognize hidden patterns in large quantities of data.

Integration with R or other statistical packages

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Standard reporting means pre-built or canned reports available to users without having to create them.

Customizable dashboards

Customizable dashboards are dashboards providing the builder some degree of control over the look and feel and display options.

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Pixel Perfect reports are highly-formatted reports with graphics and ability to preview the report before printing.

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Ad-Hoc Reports are reports built by the user to meet highly specific requirements.

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Drill down analysis is the ability to get to a further level of detail by going deeper into the hierarchy.

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Ability to format output e.g. conditional formatting, lines, headers, footers.

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Predictive modeling is the ability to build future forecasting models.

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igraph

Overview

What is igraph?