CoLAB Data Science Workshop 2019

Requirements

Python >= 3.6

Installation

Download python from https://www.python.org/downloads/. Examples of how to install python are here https://realpython.com/installing-python/.

• An alternative is a data science platform e.g. Anaconda https://www.anaconda.com/distribution/ that comes with many preinstalled packages
• An Integrated Development Environments e.g. PyCharm community edition https://www.jetbrains.com/pycharm/ Can be used to install packages

Setup

Two methods are provided: 1 Install a Python virtual environment https://docs.python.org/3/library/venv.html

python3 -m venv colab-venv

• Start the python virtual environment

source colab-venv/bin/activate

• Install packages with pip and requirements.txt

pip install -r requirements.txt

2 Install with conda:

conda env create -f environment.yml

Run

Start the jupyter notebook server in the python virtual environemnt then go to the src folder. The steps are:

1. Start the python virtual environment

• For example on GNU/Linux

source PATH_TO_MY_VIRTUAL_ENVIRONMENT/bin/activate;

• or with conda

conda activate colab-2019

2. Start the jupyter notebook

jupyter-notebook

Docker

There is also a Dockerfile e.g Build

docker build -t colab .

Run

docker run -p 8888:8888 -t colab

The docker file can be improved to handle e.g. data mounting and run name tagging

Documentation

Documentation is in the docs folder

Data

Data can be put in the data folder. A .gitignore file ignores data/*.csv files. The data from https://analyse.kmi.open.ac.uk/open_dataset#data is used.

Use download_data.sh for help downloading the data files to the data folder

bash ./download_data.sh

Packages used

jupyter
matplotlib
numpy
pandas
scikit-learn
scipy
seaborn