Course setup

To get started, you should have the following three elements setup:

Install Python and the required Python packages
Download the course material to your computer
Test your configuration and installation
Start Jupyter lab

In the following sections, more details are provided for each of these steps. When all three are done, you are ready to start coding!

1. (before the course) Install Python and the required Python packages

For scientific and data analysis, we recommend to use Anaconda (or Miniconda) (https://www.anaconda.com/download/), which provides a Python distribution that includes the scientific libraries (this recommendation applies to all platforms, so for both Windows, Linux and Mac), instead of installing Python as such. After installation, proceed with the setup.

Install Anaconda

Option 1: I do not have Anaconda installed

For first time users and people not fully confident with using the command line, we advise to install Anaconda, by downloading and installing the Python 3.x version from https://www.anaconda.com/download/. Recent computers will require the 64-Bit installer.

For more detailed instructions to install Anaconda, check the Windows, Mac or linux installation tutorial.

Note: When you are already familiar with the command line and Python environments you could opt to use Miniconda instead of Anaconda and download it from https://conda.io/miniconda.html. The main difference is that Anaconda provides a graphical user interface (Anaconda navigator) and a whole lot of scientific packages (e.g https://docs.anaconda.com/anaconda/packages/py3.9_win-64/) when installing, whereas for Miniconda the user needs to install all packages using the command line. On the other hand, Miniconda requires less disk space.

Option 2: I have installed Anaconda earlier

When you already have an installation of Anaconda, you have to make sure you are working with the most recent versions. As the course is developed for Python 3, make sure you have Anaconda3 (on Windows, check Start > Programs > Anaconda3). If not, reinstall Anaconda according to the previous section.

Start the Anaconda Navigator program (for Windows users: Start > Anaconda Navigator) and go to the Environments tab. You should see the base (root) environment, click the arrow next to it and click Open terminal, as shown in the following figure:

Navigator terminal

Type following command + ENTER-button (make sure you have an internet connection):

conda update -n base conda

and respond with Yes by typing y. Packages should be updated after the completion of the command.

Setup after Anaconda installation

As not all packages we will use in the course are provided by default as part of Anaconda, we have to add the package to Anaconda to get started. As a good practice, we will create a new conda environment to work with. This environment will contain the required packages on which this course depends.

The packages used in the course are enlisted in an environment.yml file. The file looks as follows:

name: DS-python
channels:
- defaults
- conda-forge
dependencies:
- python=3.11
- ipython
- jupyter
- ...

The file contains information on:

name is the name used for the environment
channels to define where to download the packages from
dependencies contains each of the packages

To download the environment file, click to go to the environment.yml online. Once opened in the browser, right-click and save the file/page on your computer. The specific text depends on your browser (Save page as..., Save as...).

WARNING ! Make sure you save the file as environment.yml instead of environment.yml.txt which, specifically on Windows operating system, might be the default option. To do so, choose for ‘save as type’ All Files instead of ‘Text Document’.

You will need the folder/directory containing the environment.yml file in the next step. Make sure you know where you stored the file on your computer, e.g. when stored in the folder C:/Users/yourusername/Documents you should see the file environment.yml in File Explorer in that directory.

Next, start the Anaconda Navigator program (for windows users: Start > Anaconda Navigator) and go to the Environments tab. You should see the base (root) environment, click the arrow next to it and click Open terminal, as shown in the following figure:

Navigator terminal

Type following commands line by line + ENTER-button (make sure you have an internet connection):

conda install -n base conda-libmamba-solver
conda config --set solver libmamba
conda config --add channels conda-forge
conda config --set channel_priority strict
cd FOLDER_PATH_TO_ENVIRONMENT_FILE
conda env create -f environment.yml

! FOLDER_PATH_TO_ENVIRONMENT_FILE should be replaced by the path to the folder containing the downloaded environment file. In the example earlier, this was C:/Users/yourusername/Documents, but make sure you use your specific folder (as seen in File Explorer).

Respond with Yes by typing y when asked. Output will be printed and if no error occurs, you should have the environment configured with all packages installed.

Note: If you did use Miniconda instead, create the environment using the same commands/instructions in the terminal (make sure to do the conda config ... steps.).

When finished, keep the terminal window open (or reopen it). Execute the following commands to check your installation:

conda activate DS-python
ipython

Within the terminal, a Python session will be started in which you can start writing Python! Type the following command:

import pandas
import matplotlib

If no message is returned, you’re all set! If a message (probably an error) returned, contact the instructors. Copy paste the message returned.

2. (first day of the course) Getting the course materials

Option 1: You are a git user?

As the course has been setup as a git repository managed on Github, you can clone the entire course to your local machine. Use the command line to clone the repository and go into the course folder:

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

In case you would prefer using Github Desktop, see this tutorial.

Option 2: You are not a git user?

To download the repository to your local machine as a zip-file, click the download ZIP on the repository page https://github.com/jorisvandenbossche/DS-python-data-analysis (green button “Code”):

After the download, unzip on the location you prefer within your user account (e.g. My Documents, not C:\).

Note: Make sure you know where you stored the course material, e.g. C:/Users/yourusername/Documents/DS-python-data-analysis

3. (first day of the course) Test your configuration

To check if your packages are properly installed, open the Conda Terminal again (see above) and navigate to the course directory:

cd FOLDER_PATH_TO_COURSE_MATERIAL

With FOLDER_PATH_TO_COURSE_MATERIAL replaced by the path to the folder with the downloaded course material (e.g. in the example it is C:/Users/yourusername/Documents/DS-python-data-analysis).

Activate the newly created conda environment:

conda activate DS-python

Then, run the check_environment.py script:

python check_environment.py

When all checkmarks are ok, you’re ready to go!

4.(start of day during course) Starting Jupyter Notebook with Jupyter Lab

Each of the course modules is set up as a Jupyter notebook, an interactive environment to write and run code. It is no problem if you never used jupyter notebooks before as an introduction to notebooks is part of the course.

Option 1: Using the command line

In the terminal, navigate to the DS-python-data-analysis directory (downloaded or cloned in the previous section)
Ensure that the correct environment is activated.
```
conda activate DS-python
```
Start a jupyter notebook server by typing
```
jupyter lab
```

Option 2: Using Anaconda Navigator

In the Anaconda Navigator Home tab, first switch to the course environment, called DS-python in the selection bar. Next, select the Launch button under the Jupyter Lab icon:

Navigator terminal

Next?

This will open a browser window automatically. Navigate to the course directory (if not already there) and choose the notebooks folder to access the individual notebooks containing the course material.