drdwitte/DS-python-data-analysis

Data manipulation, analysis and visualisation in Python - specialist course Doctoral schools of Ghent University

Data manipulation, analysis and visualisation in Python

Specialist course Doctoral schools of Ghent University

For how to set up a working environment, fetch the course materials and start the notebooks, see the slides: https://jorisvandenbossche.github.io/DS-python-data-analysis/

Requirements to run this tutorial

Look at the environment.yml file for all packages that need to be installed.

Setting up a working environment

• Working on a PC from the computer room [1]:

  • Ensure you have a helios account: http://helpdesk.ugent.be/account/helios.php
  • Log in at https://snake.ugent.be
  • Start a Terminal: New (upper right) > Terminal

• Working on your own laptop [2]

Getting the course materials

• With using git ([1] and recommended for [2])

  First time (inside a terminal or cmd):

$ git clone https://github.com/jorisvandenbossche/DS-python-data-analysis.git $ cd DS-python-data-analysis

Updating (on second or third day):

$ git pull

* Without git for [2]: download ZIP from https://github.com/jorisvandenbossche/DS-python-data-analysis (green button "Clone or download")


### Create an environment with Anaconda (for [2])

(*make sure you have a working internet connection*)

Use our [environment.yml](https://github.com/jorisvandenbossche/DS-python-data-analysis/blob/master/environment.yml) file inside the course folder to set up your Python working environment

In a terminal or cmd, navigate to the `DS-python-data-analysis` folder and use the following command:

$ conda env create -f environment.yml

When the environment is installed, activate the environment inside the terminal/cmd:

* Windows-users

$ activate DS-python-data-analysis

* Linux/Mac-users

$ source activate DS-python-data-analysis

### Starting a Jupyter Notebook (for [2])

* In the terminal, navigate to the `DS-python-data-analysis` directory if not there already

* Ensure that the correct environment is activated.

* Start a jupyter notebook server with

$ jupyter notebook

 This will open a browser window automatically. Use the `notebooks` folder to access the notebooks containing the course material. If you require some rehearsel of python itself (and numpy), check the [python_recap](https://github.com/jorisvandenbossche/DS-python-data-analysis/tree/master/notebooks/python_recap) folder first, otherwise you can directly jump into the `pandas_0x_` notebooks.


Authors: Joris Van den Bossche, Stijn Van Hoey