Getting started with Python data processing

Python data processing: environment and main anatomy.

· 1. Run Anaconda
· 2. Create a Jupyter Notebook 
· 3. Begin Python data analysis
· 4. Anatomy of Python data analysis scripts
· 5. Your turn..

In this post, I want to walk you through the essential steps to be quickly up and running with Python, for data analysis and processing.

We will use the Python distribution available in Anaconda, a platform with a lot of free Data Science tools and libraries, of which I am a big fan. In case you haven’t installed it yet, you can just download it from here, and install it in a few clicks.

Once installed, let’s go and see how you can quickly start using Python and its best library for data analysis.

1. Run Anaconda

You will see the Anaconda interface with a full stack of Data Science tools. Let’s launch Jupyter Notebook.

2. Create a Jupyter Notebook

The Jupyter Notebook is an open-source web application that allows you to create documents that contain live code, equations, visualizations and narrative text.