Python lectures Notebooks

This is the repository of my Python lectures give at Instituto de Astronomia - UNAM since 2012

The available lectures are the following:

1. Introduction to python (PDF version)

• Using python as a calculator
• assignments
• comments
• types
• complex numbers
• booleans
• printing strings
• strings
• Tuples, lists and dictionaries
• Blocks
• List and dictionary comprehension
• Functions, procedures
• Scripting
• Importing libraries

2. Introduction to Numpy (PDF version)

• The Array class
• create an array
• 1D, 2D 3D arrays
• creating array from scratch
• arrays share memory (views)
• random generator
• timing a command
• slicing arrays
• assignments
• using masks
• the where function
• some operations with arrays
• broadcasting
• calling scripts
• structured arrays and record arrays
• NaN other ANSI values.

3. Interacting with files (PDF version)

• Reading a simple ASCII file
• How to treat special rows (comments, header)
• classical way
• using numpy.loadtxt
• using numpy.genfromtxt
• Dealing with missing data
• Data in a fixed size format
• Writing files
• simple method
• Pickle files (python format)
• FITS files

4. How to make plots, images, 3D, etc, using Matplotlib (PDF version)

• Simple plot
• Controlling colors and symbols
• Overplot
• Fixing axes limits
• Labels, titles
• Legends
• The object oriented way to use Matplotlib
• Scatter
• log plots
• Multiple plots
• Everything is object
• Error bars
• Sharing axes
• Histograms
• Boxplots
• Ticks, axes and spines
• A plot inside a plot
• Play with all the objects of a plot
• Filled regions
• 2D-histograms
• 2D data sets and images
• Contour
• 3D scatter plots
• Saving plots
• Access and clear the current figure and axe
• What's happen when not in a Notebook? plt.show() and plt.ion() commands

5. Introduction to Scipy (PDF version)

• Some useful methods
• nanmean
• constants
• Integrations
• Interpolations
• 2D-interpolations
• data fitting
• multivariate estimation

6. Usefull libraries (PDF version)

• time and datetime
• timeit
• os
• sys
• subprocess
• glob
• re
• urllib2

7. The astropy library (PDF version)

• constants and units
• data table
• Downloading from CDS
• Coordinates
• Modeling

8. Object Oriented programing (PDF version)

• use functions to do simple jobs
• but use objects when things start to be more complex
• define classes, objects, attributes, methods, etc...
• use *args and **kwargs in functions calls
• use the class variables
• add functionalities to classes and objects
• use class inheritance
• use attributes properties

9. Optimization (PDF version)
10. Calling Fortran (PDF version)
11. Sending requests to MySQL and receiving the result from python, using SQLalchemy (PDF version)

• See MySQL.pdf
• connect to database
• using pandas to easy access

12. Using astroquery (PDF version)

• querying Vizier
• querying MAST
• catalogs

13. Machine Learning

• See Machine Learning.pdf
• One Notebook comparing Artificial Neural Network to Polynomial fit
• Notebook from Miguel Angel Aragon lecture on redshift determination
• Notebook from Miguel Angel Aragon lecture on Galaxy classification