Data Visualization
This unit provides comprehensive training in using the Matplotlib and Seaborn libraries for visualizing data in Science. You will learn how to generate and visualize various signal types (sinusoids, square waves, chirps) using SciPy, work with image data and colormaps, and create raster plots and peri-stimulus time histograms for spike time analysis. This unit will help you develop skills needed both for customize plots in Matplotlib to create publication-ready figures and quickly generate advanced visualizations with Seaborn to reveal patterns in complex neuroscience datasets.
Tools
Sessions
Generating Signals with Scipy and Plotting with Matplotlib
How to generate sinusoids, boxcar, chirp, and sawtooth signals and visualize them
Image Data with Numpy and Matplotlib
Accessing and visualizing image data
Spike Time Analysis with Pandas and Matplotlib
Create raster and firing rate plots, use pandas methods to select data
ERP Analysis With Pandas And Seaborn
Visualize and analyze LFP data across brain regions using Seaborn