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In Python using matplotlib ; The R programming language can be used for creating Wikipedia graphs. The Google Chart API allows a variety of graphs to be created. Livegap Charts creates line, bar, spider, polar-area and pie charts, and can export them as images without needing to download any tools.
Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy.It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.
Chart Studio Cloud is a free, online tool for creating interactive graphs. It has a point-and-click graphical user interface for importing and analyzing data into a grid and using stats tools. [ 13 ] Graphs can be embedded or downloaded.
A SVG plot with Wikimedia SVG Chart. Wikimedia SVG Chart is a graph generator using the templates functionality of Wikimedia Commons. This template generates line and point charts in a structured and readable svg format. The original values are provided unmodified for the SVG file.
Line chart showing the population of the town of Pushkin, Saint Petersburg from 1800 to 2010, measured at various intervals. A line chart or line graph, also known as curve chart, [1] is a type of chart that displays information as a series of data points called 'markers' connected by straight line segments. [2]
The first version was released August 25, 1999. [3] Ploticus is a mature product with activity, where the last major release (2.42) occurred in May 2013. [4] Bruce Byfield in Linux.com described Ploticus as, "...a throwback to the days when Unix programs did one thing, and did it well, using a minimum of system resources."
Pie chart of populations of English native speakers. A pie chart (or a circle chart) is a circular statistical graphic which is divided into slices to illustrate numerical proportion. In a pie chart, the arc length of each slice (and consequently its central angle and area) is proportional to the quantity it represents.
NetworkX is suitable for operation on large real-world graphs: e.g., graphs in excess of 10 million nodes and 100 million edges. [ clarification needed ] [ 19 ] Due to its dependence on a pure-Python "dictionary of dictionary" data structure, NetworkX is a reasonably efficient, very scalable , highly portable framework for network and social ...