Python Learning Paths

Why Python

Python is a general purpose language that is easy and intuitive. This gives it a relatively flat learning curve, and it increases the speed at which you can write a program. In short,  you need less time to code and you have more time to play around with it. In this article here are some good python learning paths.

 

Why IPython
The IPython Notebook makes it easier to work with Python and data. You can easily share notebooks with colleagues, without having them to install anything.  This drastically reduces the overhead of organizing code, output and notes files. This will allow you to spend more time doing real work.
They are fast, becoming the go to for reproducible research and are a great learning resource.
I’ve been using IPython Notebooks and I really love how flexible they are and how quickly I’m able to try out new ideas.

 

The easiest way to proceed is to just download Anaconda from Continuum.io. It comes packaged with most of the things you will need ever.

 

Best resources for learning Python

If you are a beginner and want to go through the syntax of Python with some good examples,
refer – http://www.codecademy.com/tracks… 

Here is a brief introduction to various libraries.

  • Practice the NumPy tutorial thoroughly, especially NumPy arrays. This will form a good foundation for things to come.
  • Next, look at the SciPy tutorials. Go through the introduction and the basics and do the remaining one’s basis your needs.
  • If you guessed Matplotlib tutorials next, you are wrong! They are too comprehensive for our need here. Instead look at this ipython notebook till Line 68 (i.e. till animations)
  • Finally, let us look at Pandas. Pandas provide DataFrame functionality (like R) for Python. This is also where you should spend a good time practising. Pandas would become the most effective tool for all mid-size data analysis. Start with a short introduction, 10 minutes to pandas. Then move on to a more detailed tutorial on pandas.
  • We have discussed on these libraries in detail in our post Click Here

You can also look at Exploratory Data Analysis with Pandas and Data munging with Pandas

Also, check out these free online resources.

 

Happy Learning !!
Team StepUpAnalytics.

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