This repository contains all of the code and data related to the Spring 2021 module Visual Analytics as part of the bachelor's tilvalg in Cultural Data Science at Aarhus University.
This repository is in active development, with new material being pushed on a weekly basis.
To run and use the Python files located in the src/ folder, I recommend installing Anaconda and using conda to administrate your environments.
To create an environment capable of running the .pyfiles in this repo create run the following code in a terminal:
# Clone the GitHub
git clone https://github.com/MalteHB/visual_analytics_cds.git
cd visual_analytics_cds
# Create conda env:
conda create -n cds python=3.8
# Activate conda env:
conda activate cds
# Install requirements
pip install -r requirements.txt
# Conda install packages
conda install opencv -y
conda install ipykernel -yThis repository has the following directory structure:
| Column | Description |
|---|---|
data |
A folder to be used for sample datasets that we use in class. |
notebooks |
This is where you should save all exploratory and experimental notebooks. |
src |
For Python scripts developed in class and as part of assignments. |
utils |
Utility functions that are written by me, and which we'll use in class. |
A detailed breakdown of the course structure and the associated readings can be found in the syllabus, while the studieordning can be found here.
All the credits for the content, the syllabus, the teaching and this Git repository goes to Ross Deans Kristensen-McLachlan.
For help or further information feel free to connect with me, Malte, on [email protected] or any of the following platforms:
