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.
- Clone this repository.
- Install Docker.
- Optional: Extend memory when working with large datasets.
- Go to the project path and run
make start. - 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
- Copy the localhost link into a browser to interact with the notebooks.
- 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