Data Visualisation

COSC3000: Data Visualisation examples

All course files and examples available on GitHub: github.com/benroberts999/COSC3000

  • 00-Basic
    • Some very basic introductory python versions of the introductory matlab scripts from the course blackboard

Week 1 - reading data files

  • wk1 lecture slides

  • read-files
    • A number of basic examples showing reading in text files + plotting
    • Examples in: python, C++, gnuplot, matlab, Mathematica, C
    • See README-read_files.md for details
  • binary-files
  • GPS-example
    • A more complicated “real world” example, using skills from above
      • (This will probably be more accessible after a few weeks of the course, but I give it to you now for your interest)
    • Plots public atomic clock data from GPS (provided by JPL/NASA)
    • See README_GPS-example.md for details
  • waveform
    • Python and C++ versions of the matlab script to read the binary waveform data from week 1 tutorial

proj1-example

  • A bare-bones python example similar to provided matlab example for first project
  • You’ll need to download the data from the blackboard site

Week 2 - univariate data

  • Example “height” data plots from the lecture
  • Solutions to week 2 workshop (flu data)
  • wk2 lecture slides

Week 3 - bivariate data

Week 4 - time series data

  • Time-series data examples, including Fourier transforms, autocorrelation, heatmaps, seasonal trends etc.
  • interative plot example with ipywidgets
  • wk4 lecture slides

Week 5 - multivariate data

  • Multi-variate data: 3D data plotting, multi-regression, heatmaps, spatial statistics (correlation)
  • wk5 lecture slides

Week 6 - principle component analysis

  • PCA: Principle component analysis examples
  • wk6 lecture slides
  • (week 7 was covered by other lecturer)

Week 8 - clustering

  • k-means clustering and extensions
  • 4D+ plotting: contours, colour-maps, quiver plots, stream plots, meshgrid
  • wk8 lecture slides

Week 9 - 3+D plots, and styles

  • Interactive plotting and animations, python ‘magics’
  • Interpolation
  • Wire frames, surface plots, 3D contours and projections (galaxy-surface)
  • Plotting styles, colors, fonts, style sheets
  • dealing with large output file sizes + scalable graphics