This talk:

• What is Python
• Scientific Python

• Research with Jupyter

Python:

Python is:

• Python is a high-level / all-purpose programming language
• It has an established ‘stack’ of libraries for science

• Python is clear, powerful and popular

# Set up the matplotlib figure
f, axes = plt.subplots(3, 3, figsize=(9, 9), sharex=True, sharey=True)

# Rotate the starting point around the cubehelix hue circle
for ax, s in zip(axes.flat, np.linspace(0, 3, 10)):

    # Create a cubehelix colormap to use with kdeplot
    cmap = sns.cubehelix_palette(start=s, light=1, as_cmap=True)

    # Generate and plot a random bivariate dataset
    x, y = rs.randn(2, 50)
    sns.kdeplot(x, y, cmap=cmap, shade=True, cut=5, ax=ax)
    ax.set(xlim=(-3, 3), ylim=(-3, 3))

The Scipy Stack

Unlike more specialised computational languages like R, Matlab, Julia, and others, Python does not have numerical and statistical tools built-in to the language.

The Scipy stack provides a standalone, versatile and powerful scientific working environment, including: NumPy, SciPy, IPython (Jupyter), Matplotlib, Pandas, and many others...

The Jupyter notebook

• try jupyter: https://tmpnb.org/
• nb gallery: http://nb.bianp.net/
• join us on fb: research with jupyter