Plotting and Visualization in Julia

Introductory examples to plotting in Julia using varios libraries

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Last Used:

• July 20, 2018 - CEBI 0971 Summer@Brown: Biomedical Informatics and Data Science Skills for Biomedicine and Health Care
• June 20, 2018 - BIOL6535 Preclinical Elective Summer 2018 at Brown University.

Materials:

• Introductory Notebook: Intro Slides
• PlotlyJS Notebook Viewer
• Plots Notebook Viewer
• Seaborn Notebook Viewer
• Gadfly Notebook Viewer
• PyPlot Notebook Viewer
• (For instructors) To locally view the notebooks as slide you can install the notebook extension RISE

Files in this directory:

• Intro.ipynb -- Intro notebook
• Intro.ipynb -- Julia script matching the corresponding notebook
• plots_basics.ipynb - Jupyter notebook introducing Plots.jl
• plots_basics.jl - Julia script matching the corresponding notebook
• plotlyjs_basics.ipynb - Jupyter notebook introducing PlotlyJS.jl
• plotlyjs_basics.jl - Julia script matching the corresponding notebook
• seaborn_basics.ipynb - Jupyter notebook introducing Seaborn.jl
• seaborn_basics.jl - Julia script matching the corresponding notebook

Dependencies:

See install_dependencies.jl if you need to troubleshoot.

# Packages to add - you may already have some of them
Pkg.add("PyPlot")
Pkg.add("Plots")
Pkg.add("StatPlots")
Pkg.add("PlotlyJS")
Pkg.add("Gadfly")
Pkg.add("Seaborn")
Pkg.add("Pandas")


# Test all used packages
using Plots
using StatPlots
using DataFrames, RDatasets
using PlotlyJS
using Gadfly

using Seaborn
using Pandas
using PyPlot
using PyCall