<commit_before>### How to Use this Guide
All of the code for this workshop is contained in [Jupyter Notebooks](http://jupyter.org/).

Each of the *Sections* in the *Table of Contents* maps to one of the folders above. Click on the folder to open it, and then click on the file you want to view.

If you're looking to install Python the recommended (and supported) method is [here](http://nbviewer.jupyter.org/github/vbarua/PythonWorkshop/blob/master/Code/Meta/3%20-%20Running%20Python%20in%20a%20Virtual%20Machine.ipynb) and alternatives are [here](http://nbviewer.jupyter.org/github/vbarua/PythonWorkshop/blob/master/Code/Meta/2%20-%20Python%20Setup.ipynb)

### Extra Resources
* The official [Python Style Guide](https://www.python.org/dev/peps/pep-0008/#version-bookkeeping).
* The official [Python Tutorial](https://docs.python.org/3/tutorial/). Start at Section 3. Goes into more detail than this workshop.
* [Learn Python The Hard Way](http://learnpythonthehardway.org/book/) - An online book. Very detailed, great for beginners.
* [Dive Into Python](http://www.diveintopython3.net/your-first-python-program.html) - Another online book. Covers a bit more advance material.

# Table of Contents
## Meta
 1. [Terminals and You](http://nbviewer.jupyter.org/github/vbarua/PythonWorkshop/blob/master/Code/Meta/1%20-%20Terminals%20and%20You.ipynb)
 2. [Python Setup](http://nbviewer.jupyter.org/github/vbarua/PythonWorkshop/blob/master/Code/Meta/2%20-%20Python%20Setup.ipynb)
 3. [Running Python in a Virtual Machine](http://nbviewer.jupyter.org/github/vbarua/PythonWorkshop/blob/master/Code/Meta/3%20-%20Running%20Python%20in%20a%20Virtual%20Machine.ipynb)

## Introduction to Python
 1. Strings, Numbers and Booleans
 2. Tuples and Lists
 3. Dictionaries
 4. Conditionals and Looping
 5. Functions
 6. Classes
 7. Imports

## Numerical Computing with NumPy
 1. Introduction to NumPy
 2. Linear Algebra with NumPy

## An Interlude on Input and Output
 1. Reading and Writing Data

## Plotting
 1. Plotting with Matplotlib
 2. Plotting Matrices

## Useful SciPy Functionalities
 1. Curve Fitting with SciPy

<commit_msg>Updating README to emphasize installation options<commit_after>### How to Use this Guide
All of the code for this workshop is contained in [Jupyter Notebooks](http://jupyter.org/).

If you're looking to install Python the recommended (and supported) method is [here](http://nbviewer.jupyter.org/github/vbarua/PythonWorkshop/blob/master/Code/Meta/3%20-%20Running%20Python%20in%20a%20Virtual%20Machine.ipynb) and alternatives are [here](http://nbviewer.jupyter.org/github/vbarua/PythonWorkshop/blob/master/Code/Meta/2%20-%20Python%20Setup.ipynb)

# Table of Contents
## [Meta](http://nbviewer.jupyter.org/github/vbarua/PythonWorkshop/tree/master/Code/Meta/)
(Information around installing and using Python)

 1. Terminals and You
 2. Python Setup
 3. Running Python in a Virtual Machine
 4. Running Python Code

## [Introduction to Python](http://nbviewer.jupyter.org/github/vbarua/PythonWorkshop/tree/master/Code/Introduction%20To%20Python/)
 1. Strings, Numbers and Booleans
 2. Tuples and Lists
 3. Dictionaries
 4. Conditionals and Looping
 5. Functions
 6. Classes
 7. Imports

## [Numerical Computing with NumPy](http://nbviewer.jupyter.org/github/vbarua/PythonWorkshop/tree/master/Code/Numerical%20Computing%20with%20Numpy/)
 1. Introduction to NumPy
 2. Linear Algebra with NumPy

## [An Interlude on Input and Output](http://nbviewer.jupyter.org/github/vbarua/PythonWorkshop/tree/master/Code/An%20Interlude%20on%20Input%20and%20Output/)
 1. Reading and Writing Data

## [Plotting](http://nbviewer.jupyter.org/github/vbarua/PythonWorkshop/tree/master/Code/Plotting/)
 1. Plotting with Matplotlib
 2. Plotting Matrices

## [Useful SciPy Functionalities](http://nbviewer.jupyter.org/github/vbarua/PythonWorkshop/tree/master/Code/Useful%20SciPy%20Functionalities/)
 1. Curve Fitting with SciPy


# Extra Resources
* The official [Python Style Guide](https://www.python.org/dev/peps/pep-0008/#version-bookkeeping).
* The official [Python Tutorial](https://docs.python.org/3/tutorial/). Start at Section 3. Goes into more detail than this workshop.
* [Learn Python The Hard Way](http://learnpythonthehardway.org/book/) - An online book. Very detailed, great for beginners.
* [Dive Into Python](http://www.diveintopython3.net/your-first-python-program.html) - Another online book. Covers a bit more advance material.

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