Powercourse Python Data Science

This repo contains a Python Jupyter notebook environment, datasets for data manipulation and notebooks explaining the basics of Jupyter notebook and Python data Science in general.

Setup guide

1. Clone this repository.
2. Install Docker.
   • Optional: Extend memory when working with large datasets.
3. Go to the project path and run make start.
4. Wait for the container to boot up and the following output to appear:

jupyter_1  |     To access the notebook, open this file in a browser:
jupyter_1  |         file:///home/jovyan/.local/share/jupyter/runtime/nbserver-7-open.html
jupyter_1  |     Or copy and paste one of these URLs:
jupyter_1  |         http://1cb200917588:8888/?token=2170cb82273a778165249bcaa12038fdbf14933e0ecb6523
jupyter_1  |      or http://127.0.0.1:8888/?token=2170cb82273a778165249bcaa12038fdbf14933e0ecb6523

5. Copy the localhost link into a browser to interact with the notebooks.

References

• https://colab.research.google.com/
• https://www.datacamp.com/community/tutorials/tutorial-jupyter-notebook
• https://github.com/jupyter/jupyter/wiki/A-gallery-of-interesting-Jupyter-Notebooks
• https://medium.com/analytics-vidhya/python-data-manipulation-fb86d0cdd028
• https://pandas.pydata.org/
• https://seaborn.pydata.org/
• https://matplotlib.org/stable/index.html
• https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf
• https://www.datacamp.com/community/blog/python-scientific-computing-case
• https://www.codecademy.com/learn/data-manipulation-in-python-dvp/modules/pandas-dvp/cheatsheet
• https://analyzingalpha.com/data-manipulation-with-python-and-pandas