Analyses I
Contents
Analyses I¶
With this session, we have reached the final chapter of our endeavor. After spending quite a good while on important prerequisites concerning scientific computing and the basics of the python programming language and a short excurse to running experiments using PsychoPy, we will now spend a look at data analyses using python. This includes a brief showcase of several distinct aspects/steps in a “classic” data analyses workflow: basic data handling (reading, wrangling, writing), data visualization and statistical analyses. As usual the aim is to provide folks a respective overview that allows them to dig further into details and start using python for their data analyses after the course ends.
Topics 💡👨🏻🏫¶
In the following you’ll find the objectives and materials for each of the topics we’ll discuss during this session.
Introduction to Data analyses - I¶
Sure, most of us already conducted some analyses here and there but did you already make use of the fantastic world of data analyzes using python with its tremendously powerful go-to modules and basically unlimited amount of highly specifialized libraries? No matter what you’re looking for and want to work on, python’s got your back! Given the short amount of time we have, this session will focus on one of the central modules concerning working with data: pandas. In more detail, we will check the data we obtained during the PsychoPy sessions via going through several core steps of data analyes using pandas.
Objectives 📍¶
learn basic and efficient usage of python for data analyzes & visualization
working with data:
reading, working, writing
preprocessing, filtering, wrangling
visualizing data:
basic plots
advanced & fancy stuff
statistical analyses
Ask and answer questions
Have a great time
Materials 📓¶
Please see the rendered version of the jupyter notebook Data analyzes I - basics in data handling in the ToC on the left.
tasks for subsequent meeting 🖥️✍🏽📖¶
Your eight homework assignment will entail working through a few tasks covering the contents discussed in this session within of a jupyter notebook. You can download it here. In order to open it, put the homework assignment notebook within the folder you stored the course materials, start a jupyter notebook as during the sessions, navigate to the homework assignment notebook, open it and have fun!
Deadline: 02/02/2022, 11:59 PM EST
optional/reading/further materials¶
Here are some cool add-ons to further familiarize yourself with pandas and its capabilities.
Make sure to check the amazing 10 minutes to pandas tutorial that covers a lot of important functionality!