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Supported Chart Types Supported Bar Chart Types Other Features Interactivity Rendering Technologies Databinding HTML 5 Canvas Line Timeline Scatter Area Pie Donut Bullet Radar Funnel Gantt Network Grouped Mind Mapping Stacked Negative Discrete Horizontal 3D Legends Animation Mouse Over onClick HTML5 Canvas SVG VML AxisXY WebGL rendering; AG ...
Python and Matplotlib are cross-platform, and are therefore available for Windows, OS X, and the Unix-like operating systems like Linux and FreeBSD. Matplotlib can create plots in a variety of output formats, such as PNG and SVG. Matplotlib mainly does 2-D plots (such as line, contour, bar, scatter, etc.), but 3-D functionality is also available.
Graph drawing is an area of mathematics and computer science combining methods from geometric graph theory and information visualization to derive two-dimensional depictions of graphs arising from applications such as social network analysis, cartography, linguistics, and bioinformatics.
If a chart plots 10 colors or fewer, then by default it uses every other one: The colors can be manually set in a graph by adding them to the 'colors' parameter. For example, for two pie charts, the first of which is default and the second of which omits some colors in the first, you would manually enter your selections from the default 20:
Matplotlib-animation [11] capabilities are intended for visualizing how certain data changes. However, one can use the functionality in any way required. These animations are defined as a function of frame number (or time). In other words, one defines a function that takes a frame number as input and defines/updates the matplotlib-figure based ...
A bar chart or bar graph is a chart or graph that presents categorical data with rectangular bars with heights or lengths proportional to the values that they represent. The bars can be plotted vertically or horizontally. A vertical bar chart is sometimes called a column chart and has been identified as the prototype of charts. [1]
In 2009, based on the experience of developing and utilizing Prefuse and Flare, Jeffrey Heer, Mike Bostock, and Vadim Ogievetsky of Stanford University's Stanford Visualization Group created Protovis, a JavaScript library to generate SVG graphics from data. The library was known to data visualization practitioners and academics.
AnyChart 8.x first released in 2017 has a modular system and supports more than 90 chart types, including variations of basic charts, Gantt charts, meteorological and environmental data graphs (such as air temperature and precipitation, depth measures [4]), and maps, along with custom drawing and diverse options to work with data.