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  2. Graph Modelling Language - Wikipedia

    en.wikipedia.org/wiki/Graph_Modelling_Language

    Graph-tool, a free Python module for manipulation and statistical analysis of graphs. NetworkX, an open source Python library for studying complex graphs. Tulip (software) is a free software in the domain of information visualisation capable of manipulating huge graphs (with more than 1.000.000 elements).

  3. Cypher (query language) - Wikipedia

    en.wikipedia.org/wiki/Cypher_(query_language)

    Using graph as a fundamental representation for data modeling is an emerging approach in data management. In this approach, the data set is modeled as a graph, representing each data entity as a vertex (also called a node) of the graph and each relationship between two entities as an edge between corresponding vertices.

  4. List of information graphics software - Wikipedia

    en.wikipedia.org/wiki/List_of_information...

    This is a list of software to create any kind of information graphics: either includes the ability to create one or more infographics from a provided data set; either it is provided specifically for information visualization

  5. Social network analysis software - Wikipedia

    en.wikipedia.org/wiki/Social_network_analysis...

    Python will read in almost any format data file Python has write capability for most data formats Windows, Linux, Mac Open source: Python contains several packages relevant for social network analysis: igraph is a library collection for creating and manipulating graphs and analyzing networks. It is written in C and also exists as Python and R ...

  6. Datasaurus dozen - Wikipedia

    en.wikipedia.org/wiki/Datasaurus_dozen

    The dinosaur data set created by Alberto Cairo that inspired the creation of the Datasaurus Dozen. The first data set, in the shape of a Tyrannosaurus, that inspired the rest of the "datasaurus" data set was constructed in 2016 by Alberto Cairo. [7] [8] It was proposed by Maarten Lambrechts that this data set also be called "Anscombosaurus". [7]

  7. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  8. NetworkX - Wikipedia

    en.wikipedia.org/wiki/NetworkX

    The nodes in a NetworkX graph can be specialized to hold any data, and the data stored in edges is arbitrary, further making it widely applicable to different fields. It is able to read in networks from data and randomly generate networks with specified qualities. This allows it to be used to explore changes across wide amounts of networks. [4]

  9. Gramps (software) - Wikipedia

    en.wikipedia.org/wiki/Gramps_(software)

    Gramps, formerly GRAMPS (an acronym for Genealogical Research and Analysis Management Programming System), [2] is a free and open-source genealogy software. [9] It is developed in Python using PyGObject and utilizes Graphviz to create relationship graphs.