This two-day training provides a practical introduction to Python and its core capabilities for data analysis.
- Log in to Github - create one if you haven't already
- Click the green ‘Code’ button on the GitHub repository page
- Select ‘Codespaces’ → ‘Create codespace on main’
This will launch a new Codespace, a cloud-based development environment pre-configured with all necessary packages and files for the training.
Once the Codespace has launched:
-
Wait for the Codespace to fully initialise, this will take about 3 minutes on the first set up.
-
Close the Terminal and open the notebook(s) listed in the training agenda and start working through the exercises.
All necessary libraries should already be installed. If you encounter a missing package, use
pip install package_name
.
- Understand the different data types, including integers, floats, strings, booleans, and lists
- Use conditionals to execute code only under certain conditions
- Write
for
loops to repeat code segments - Create reusable functions with parameters to apply logic flexibly
- Gather descriptive summary statistics of your data with simple operations
- Effectively select and filter parts of your dataset
- Retrieve advanced statistics with
groupby
aggregations - Create new columns using
.assign()