Introduction to Data Wrangling

Overview

In this tutorial, we’ll be taking an exploratory look at how to perform data wrangling using Python. It’s assumed the audience has a working understanding of Python and some basic data analysis exposure. Participants will leave the class with a better understanding of useful Python libraries for data analysis, as well as some hands-on scripts built throughout the tutorial. With these initial first steps, they should feel comfortable integrating data analysis into their current Python projects.

Outline

• Introduction to Data Wrangling with Python * How to ask questions * Where to find data ** Why Python?

• Initial setup * IPython Notebook * Getting the data

• Importing data * Working with easy formats * Working with hard formats ** APIs

• Exploring data * Using pandas * Asking simple questions ** Joining datasets

• Analysing data * What is the data saying * Standardization and normalization ** Making conlusion

• Reporting your findings * Who is your audience * Charting data ** Interactive charts and graphs

• Next steps * Where to go from here * Q&A ** “Homework”

Please download: https://github.com/kjam/data-wrangling-pycon