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Data science in Python - course materials

Gitter

New course based on 'Working with Python: functions and modules' course

Materials for the course run by the Graduate School of Life Sciences, University of Cambridge.

  • Course website: http://pycam.github.io/
  • Booking website: http://www.training.cam.ac.uk/

If you wish to run the course on your personal computer, here are the steps to follow to get up and running.

Clone this github project

For Windows, you have to install GitBash https://gitforwindows.org/ to be able to execute the command. Note down the folder where you have downloaded the git repository.

git clone https://github.com/pycam/python-data-science.git
cd python-data-science

Dependencies

Mac OSX

Install Python 3 by downloading the latest version from https://www.python.org/. For Mac OSX, just run brew install python3.

Python 2.x is legacy, Python 3.x is the present and future of the language.

Create first a virtual environment using the venv library. Update pip if needed, install jupyter and RISE to get a slideshow extension into jupyter.

Note A virtual environment is a Python environment such that the Python interpreter, libraries and scripts installed into it are isolated from those installed in other virtual environments.

python3 -m venv venv
# activate your virtual environment
source venv/bin/activate
# update pip if needed
pip install --upgrade pip
# install package dependencies
pip install jupyter pandas matplotlib seaborn biopython

# slideshow extension
pip install rise
jupyter-nbextension install rise --py --sys-prefix
jupyter nbextension enable rise --py --sys-prefix

On mac OSX you may need to run this command to accept the XCode license, before installing biopython:

sudo xcodebuild -license

Windows

Install Python 3 by downloading the latest version of Anaconda https://www.anaconda.com/distribution/. Take the graphical installer or the command line installer.

Python 2.x is legacy, Python 3.x is the present and future of the language.

After installation, open an Anaconda prompt which is Windows command line configured for Anaconda.

(base) C:\Users\your_username>conda create --name python-course
(base) C:\Users\your_username>conda activate python-course
(python-course) C:\Users\your_username>conda install pandas matplotlib seaborn biopython
(python-course) C:\Users\your_username> conda install jupyter rise
(python-course) C:\Users\your_username>jupyter-nbextension install rise --py --sys-prefix
(python-course) C:\Users\your_usernamejupyter nbextension enable rise --py --sys-prefix

Usage

Mac OSX

Go to the directory where you've cloned this repository, activate your virtual environment and run jupyter.

Your web browser should automatically open with this url http://localhost:8888/tree where you see the directory tree of the course with all the jupyter notebooks.

cd python-data-science
source venv/bin/activate
jupyter notebook

To shutdown jupyter, type ctrl-C into the terminal you've ran jupyter notebook, answer y and press enter.

You may wish to deactivate the virtual environment, by entering into the terminal:

deactivate

Windows

Launch the Anaconda prompt.

Go to the directory where you've cloned this repository (here: C:\Users\your_username\python-data-science), activate your Anaconda environment and run jupyter.

Your web browser should automatically open with this url http://localhost:8888/tree where you see the directory tree of the course with all the jupyter notebooks.

(base) C:\Users\your_username>cd python-data-science
(base) C:\Users\your_username\python-data-science>conda activate python-course
(python-course) C:\Users\your_username\python-data-science>jupyter notebook

To shutdown jupyter, type ctrl-C into the terminal you've ran jupyter notebook, answer y and press enter.

You may wish to deactivate the virtual environment, by entering into the terminal:

conda deactivate

Resources used

  • Data Carpentry lesson
  • Software Carpentry lesson
  • Biopython tutorial on sickle cell
  • Python tutorial
  • Pandas tutorials
  • Matplotlib tutorials
  • Biopython tutorial

Contributing

  • See contributing.md

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