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This repository is a submission for the code competition BIG DATA Predictions by IT-Talents and Materna.
Learn more about the competition here: https://it-talents.de/veranstaltung/code-competition-12-2021-big-data-predictions/ (German)
The task is to clean, understand and create useful insights from a messy dataset of 166,000 records from an online racing game.
The submission file is the notebook Report.ipynb.
I have beautified my notebook using jupyter-themes. If you want it to look as ✨stylish✨ as intended, execute the following commands before starting Jupyter (this is totally optional):
pip install jupyterthemes
jt -t grade3 -fs 10 -altp -nfs 115 -nf georgiaserif -tfs 115 -tf opensans -m 200 -cellw 70%
This will mainly make the cells wider – great for looking at horizontal plots – and remove UI clutter. Please note that it will permanently change your notebook style. Revert to the defaults with jt -r if you don't like it. A clean Jupyter interface does feel great though!
Finally, open the notebook:
jupyter notebook Report.ipynb
This assumes you have Python 3 and Jupyter (Jupyter Notebook) already installed, of course.
If you don't just want to read the notebook, but execute its cells yourself, all requirements in requirements.txt have to be installed. You don't have to do this externally! Just execute the installation cell at the top of the notebook after starting it – you should execute the notebook from top to bottom anyway.
These images are a preview of what to expect from the notebook:
This repository has been published under the MIT license (see the file LICENSE.txt).
The photo of the race car has been shot by Wes Tindel and was published under the Unsplash license.
The logos of IT-Talents and Materna are property of their respective owners.