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 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 folder first, otherwise you can directly jump into the pandas_0x_ notebooks.

Authors: Joris Van den Bossche, Stijn Van Hoey