Visual Analytics - Spring 2021

<<<<<<< HEAD This repository contains all of the assignments and code-along sessions of the Visual Analytics course.

Running my scripts

For running my scripts I'd recommend doing the following from your terminal (and remembering to use the new environment that it creates):

MAC/LINUX/WORKER02

git clone https://github.com/emiltj/cds-visual.git
cd cds-visual
bash ./create_lang_venv.sh

WINDOWS:

git clone https://github.com/emiltj/cds-visual.git
cd cds-visual
bash ./create_lang_venv_win.sh

Repo structure and files

======= 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.

Technicalities

For the sake of convenience, I recommend using our own JupyterHub server for development purposes. The first time you use the server, you'll need to create your own version of the repo and install relevant dependencies in a virtual environment:

git clone https://github.com/CDS-AU-DK/cds-visual.git
cd cds-visual
bash create_vision_venv.sh

From then on, every time you use the server, make sure you update the repo and install any new dependencies:

cd lang101
git pull origin main
bash create_vision_venv.sh

Repo structure

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This repository has the following directory structure:

Column	Description
<<<<<<< HEAD
`data`	Contains the data used in both the scripts and the notebooks
`notebooks`	Contains the notebooks (code along sessions)
`src`	Contains the assignments
`utils`	Utility functions written by Ross which are utilised in some of the scripts

Furthermore it contains the files:

./create_lang_venv.sh -> A bash script which automatically generates a new virtual environment, and install all the packages contained within requirements.txt
requirements.txt -> A list of packages along with the versions that are certain to work
README.md -> This very readme file

Contact

Feel free to write me, Emil Jessen for any questions (also regarding the reviews). You can do so on Slack or on Facebook.

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 | Python scripts to be used in class. utils | Utility functions that are written by me, and which we'll use in class.

Class times

This class takes place on Thursday afternoons from 14-18. Teaching will take place on Zoom, the link for which will be posted on Slack and Blackboard.

Course overview and readings

A detailed breakdown of the course structure and the associated readings can be found in the syllabus. Also, be sure to familiarise yourself with the studieordning for the course, especially in relation to examination and academic regulations.

Contact details

The instructor is me! That is to say, Ross.

All communication to you will be sent both on Slack and via Blackboard. If you need to get in touch with me, Slack should be your first port-of-call!