Introduction to Python for Data Science

An introductory lesson centered around data science tasks in Python.

This lesson contains three episodes that focus on:

Manipulating tabular data with Pandas
Visualizing data with Pandas and altair
Common tasks in machine learning

Prerequisites

We assume that you have participated in the previous lessons for day 1 and 2 of the workshop Getting Started with Python for Data Science and Automation in Biotechnology. That means, we expect you to be familiar with file paths on the shell and that you have a basic understanding of Python.

Schedule

	Setup	Download files required for the lesson
00:00	1. Reading and Working with Tabular Data	What is a Pandas data frame? How do I get an overview on my tabular data? How do I read tabular data in different formats? How do I access subsets of a data frame? How do I calculate simple statistics like the mean?
01:30	2. Morning Break	Break
01:45	3. Visualize Your Data	What tools exist to plot data in Python? How do I make a basic plot? What visuals are available? How can I best visualize groups of data?
03:00	4. Lunch Break	Break
04:00	5. Machine Learning	What is machine learning? What kind of tasks can I apply machine learning to? How do I perform machine learning with scikit-learn? How do I interpret my results?
05:30	6. Afternoon Break	Break
05:45	7. Machine Learning (continued)	Break
06:30	8. Wrap-up and Outlook	Break
07:00	Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.