Pygal is a Python Library designed with the purpose of creating high resolution and interactive graphs. Pygal specializes in the creation of SVG’s (Scalable Vector Graphics). Not only are these very scalable and high quality, you can easily integrate them with other frameworks and applications. ...
plotly.py is an interactive, open-source, and browser-based graphing library for Python ✨Built on top of plotly.js, plotly.py is a high-level, declarative charting library. plotly.js ships with over 30 chart types, including scientific charts, 3D graphs, statistical charts, SVG maps, ...
xdot.pyis an interactive viewer for graphs written inGraphviz'sdot language. It uses internally the GraphViz'sxdot output formatas an intermediate format,Python GTK bindings, andCairofor rendering. xdot.pycan be used either as a standalone application from command line, or as a library embedde...
Additionally, Bokeh has some built-in functionality for building things like stacked bar charts and plenty of examples for creating more advanced visualizations like network graphs and maps. Organize the Layout If you need more than one figure to express your data, Bokeh’s got you covered. Not...
Discover the power of data visualization with Plotly in Python. Learn to transform raw data into interactive, insightful visuals and create dynamic dashboard
Graphviz can output graphs in DOT format, which contains detailed information about nodes, edges, and their positions. Python 6 1 importpygraphviz 2 3 defconvert_gviz_image(gviz): 4 graph_dot=pygraphviz.AGraph(str(gviz)) 5 image_str=graph_dot.to_string() ...
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Data from emerging applications, such as cybersecurity and social networking, can be abstracted as graphs whose edges are updated sequentially in the form of a stream. The challenging problem of interactive graph stream analytics is the quick response of the queries on terabyte and beyond graph ...
This article provides several examples of histograms inplotlyusing thePython programming language. The table of contents is shown below: 1)Modules and Example Data 2)Basic Histogram 3)Plotting Multiple Groups 4)Bin Sizes and Alternative Graphs ...
The only problem is, that if I want to modify graphs that I made with `matplotlib`, that doesn't seem to be possible. I can generate the desired object, e.g. `ax.scatter([1,2,3],[1,2,3])` which print this output: `<matplotlib.collections.PathCollection at ...