Jupyter notebooks for a python data visualisation tutorial

The pdfs slides are in the repository for future look up of the references and links therein. To run the notebooks, you will need to install the necessary packages. I recommend setting up a new conda environment to contain your visualization packages:

conda create -n scivis python=3.9
conda activate scivis
conda install numpy pandas matplotlib seaborn bokeh
conda install -c plotly plotly=5.7.0
conda install -c pyviz holoviews
conda install -c conda-forge cmocean
conda install "jupyterlab>=3" "ipywidgets>=7.6"
conda install -c conda-forge -c plotly jupyter-dash

then, launch your JupyterLab with

jupyter-lab

There are three main notebooks:

1. scatterPlots.ipynb: Creates some example data spread randomly along some trend line split into different subsets. Shows some different options and problems for visualizations.
2. colorMapNotebook.ipynb: Makes several types of artifical images and compares different color maps and how specific colormaps may induce artifacts.
3. plottingLibraries.ipynb: A simple notebook which reproduces some plots using different packages to highlight how they are different and what they can include.
4. hypatiaPlot.ipynb: This notebook reads in the data from the Hypatia catalog and gives an example plot. It is meant for people to have access to astronomical data to play around with different plotting styles, etc.