"Here at Plotly, we are on a mission to build a platform where data scientists can analyze data, create beautiful graphs and collaborate: like a GitHub for data, where you can share and find plots, data, and code." - Matt Sundquist Plotly's Co-Founder.
Plotly is a browser-based data analysis and visualization tool that creates interactive, customizable, publication quality figures. This API allows MATLAB users to generate Plotly graphs from their desktop MATLAB environment. All graphs can be styled and shared through Plotly's interactive web application.
This User Guide is designed to provide a documentation of The Plotly MATLAB API functionality. Whereas the documentation provided ONLINE serves as a nice reference for begginner/intermediate users, these notebooks provide a richer learning experience, enabling beginer/intermediate users to quickly become Plotly Gurus!
These user guide notebooks are inteded to be read online and are rendered using the nbviewer website. However, if you want to get your hands dirty and use these notebooks more interactively, the source code lives HERE on github. Feel free to download the code or cloan the repository to your local machine!
Found below is a list of the various plot types handled by Plotly, covering many standard data representations. Please LET US KNOW if there are any plot types not covered that you want us to handle! We are constantly updating and expanding to new plot types.
[0] GETTING STARTED / API DOCUMENTATION
[1] OVERVIEW
[2] LINE AND SCATTER PLOTS (coming soon)
[3] BAR CHARTS (coming soon)
[4] SUBPLOTS (coming soon)
[5] ERROR BARS (coming soon)
[6] HISTROGRAMS (coming soon)
[7] BOX PLOTS (coming soon)
[8] HEAT MAPS AND COLOUR SCALES (coming soon)
[9] BUBBLE CHARTS (coming soon)
[10] 2D HISTROGRAMS (coming soon)
[11] CONTOUR PLOTS (coming soon)
[12] STREAMING AND REAL TIME DATA (coming soon)
[13] RETRIEVING DATA (coming soon)
[14] 3D SURFACE PLOTS (coming soon)
[15] MAPS (coming soon)
# CSS styling within IPython notebook
from IPython.core.display import HTML
def css_styling():
styles = open("./css/style_notebook.css", "r").read()
return HTML(styles)
css_styling()