Data statistics. Crude integral approximations. Mandelbrot set. Markov chain. Full code examples. Full code examples for the numpy chapter 1.4. Matplotlib: plotting. Introduction. IPython, Jupyter, and matplotlib modes. pyplot. Simple plot. Advanced operations. Polynomials More polynomials (with more bases). Loading data files Text files Images NumPys own format Well-known ( more obscure) file formats. Some exercises. Array manipulations. Picture manipulation: Framing a Face. Plotting with default settings. Instantiating defaults. Changing colors and line widths. Setting limits. Setting ticks. Setting tick labels. Moving spines. Adding a legend. Annotate some points. Devil is in the details. Grids. Multi Plots. Polar Axis. 3D Plots. Text. Beyond this tutorial. Tutorials. Matplotlib documentation. Code documentation. Galleries. Mailing lists. Quick references. Line properties. Line styles. Markers. Colormaps. Full code examples. Code samples for Matplotlib. Solutions of the exercises for scipy 1.6. Getting help and finding documentation Copyright 2012,2013,2015,2016,2017. Created using Sphinx.
Python. The Scientific Python ecosystem. Before starting: Installing a working environment. The workflow: interactive environments and text editors. Interactive work. Elaboration of the work in an editor. IPython and Jupyter Tips and Tricks 1.2.