Jupyter notebooks for PhD class on data languages.
Installing python
The easiest way to install python on any OS is to use anaconda python. This will install a local version of python on your system so you don't need to worry about needing admin to install new packages. Most of the packages listed above are installed by default with anaconda. For this class we will be using python 3, and I recommend you use this version for you research (unless you have a very good reason to use python 2).
Packages to install (in addition to anaconda's defaults)
emcee
reproject
wcsaxes
pip install emcee reproject wcsaxes
Class 1
Git.ipynb
: Git and Git-HubGeneral_Python.ipynb
: General python information
Class 2
General_plotting.ipynb
: How to make publication ready plotsmpl_style.py
: How to make amatplotlib
styleUncertainty_plotting.ipynb
: Making plots with errorbarsFits_images.ipynb
: Plotting image contained in FITS files
Class 3
Stats_with_Scipy.ipynb
: usingscipy
for stats distributionsAstropy_fitting.ipynb
: usingastropy
to model and fit datamcmc_fit_with_outliers.ipynb
: fitting a line to data while rejecting outliers using MCMCGaussian_process_regression
: fitting data without defining a functional form