How do things become more beautiful and interesting?

An essential part of solving computational problems is the presentation of the results. In most cases, this means a properly styled figure. In the next few notebooks, we are going to have a look at two of Python's popular plotting libraries, matplotlib and plotly. Additionally, we are going to create interactive figures with the help of the slides and dropdown menus of the ipywidgets package. This is the outline of the topic:

  • 2D figures

    • simple function and data plotting
    • plotting measurement data with errorbars
    • histograms
    • plotting bivariate functions, contour plots, heatmaps
    • plotting vector fields, arrows and field lines
    • figure legends, labels, arrows, figure arrays
  • Interactivity

    • interactive opjects in IPython (dropdown menus, slides, buttons etc.)
    • interactive figures
  • 3D figures

    • curves in 3D
    • viewing angle
    • bivariate functions
    • general surfaces
    • vector fields in 3D
  • plotly

    • basics of plotly, most common structures
    • simple plots
    • 3D plots