Plotting Intro

Visualising Data

The purpose of scientific computation is insight not numbers: To understand the meaning of the (many) numbers we compute, we often need postprocessing, statistical analysis and graphical visualisation of our data. The ensuing sections will outline the use of plotting tools within Python, mainly Matplotlib, Pandas and Plotly.

Matplotlib

The Python library Matplotlib is a python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments. Matplotlib tries to make easy things easy and hard things possible. You can generate plots, histograms, power spectra, bar charts, errorcharts, scatterplots, etc, with just a few lines of code.

For more detailed information, check these links:

Greydon Gilmore
Greydon Gilmore
Ph.D. Candidate in Biomedical Engineering

My research interests include deep brain stimulation, machine learning and signal processing.

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