gradampl / introduction-to-python

Python introduction for Data Science in Practice course.

Introduction to Python

To learn about the workshop go to the university USOS information page.

Grades, how do they work?

• The student is working with the prepared Jupyter Notebook files (fork),
• All work is done individually by the student,
• All work should be stored in a public GitHub repository for preview,
• What is taken into consideration while grading:
  • Regularity of commits to the repository,
  • Keeping Python standards in code,
  • End exam (you can only repeat it once).
  • Code quality.

Workspace setup

You can use two python distributions for the workshops:

• Anaconda 3.7 (prefered),
• Python 3.7.

Anaconda installation

1. Install Anaconda from the official website,
2. Open terminal / command prompt,
3. Create a new environment (approve all pending questions):

   conda create -n introduction-to-python python=3.7

4. Start using the created environment:

   conda activate introduction-to-python

5. Install packages to be used in our workshops:

   conda install notebook pandas numpy matplotlib seaborn

6. To start the Jupyter server navigate to your repository folder and run:

   jupyter notebook

Python installation

1. Install Python 3.7 from the official website,
2. Open terminal / command prompt,
3. Navigate to your repository folder,
4. Install virtualenv:

   pip install virtualenv

5. Create virtual environment:

   virtualenv introduction-to-python

6. Activate the virtual environment:

   # MacOS / Linux
   source introduction-to-python/bin/activate
   
   # Windows
   introduction-to-python\Scripts\activate

7. Install packages to be used in our workshops:

   pip install notebook pandas numpy matplotlib seaborn

8. To start the Jupyter server run:

   jupyter notebook