Overview

Welcome
Testing Welcome


Accessing Jupyter Notebook
Instructions on accessing jupyterhub


Introduction to Notebook and beyond
Introduction to features of Notebooks and python syntax


Introduction to Python
Description of Module 1


Python-Variables
Python variables and assigning values to variables


Python-Strings
Strings and string manipulations


Python-Numeric types
int, float and complex in python


Python-Operators
Manipulating inputs


Python-Loops
Run X times.


Python-in-practice
Advancing with python datastructures, functions and Exception handling


Python-Lists
Most commonly used sequence


Python-Tuples
Immutable list


Python-Dictionaries
Container of Key-Value pairs


Python-Functions
A block of organized and reusable code


Python-Exception-Handling
Representation of an error


Python-File-IO
I/O operations on files and standard I/O


Numpy
An introduction to one of the most fundamental packages in scientific computing


Numpy-Array-basics
Basics of Numpy’s homogenous, multidimensional arrays


Numpy-Ufuncs
Numpy universal funcs


Numpy-broadcasting-and-computation
Applying the ufuncs to multi-dimensional arrays and other generic numpy functions


Python-Matplotlib
Introduction to plotting and visualizing using python’s Matplotlib package


Matplotlib-Interactive-plotting
Plotting the plots for interactive use inside jupyter notebook


Matplotlib-types-of-plots
Introduction to some of the different types of plots in Matplotlib packages


Matplotlib-subplots-and-annotations
Plotting multiple plots in same figure and annotating them


Python-Pandas
Working with relational and labeled datasets made easy


Pandas-Series-and-Dataframe
Introduction to the two powerful workhorse datastructures of Pandas


Pandas-Exploratory-data-analysis
Example of using pandas for performing exploratory data analysis