Python for Data Analysis

Overview

This two-day training provides a practical introduction to Python and its core capabilities for data analysis.

Working with the project

1. Open the Codespace

1. Log in to Github - create one if you haven't already
2. Click the green ‘Code’ button on the GitHub repository page
3. 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.

2. Start working in the Codespace

Once the Codespace has launched:

1. Wait for the Codespace to fully initialise, this will take about 3 minutes on the first set up.

2. 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.

Agenda - Python for Data Analysis Training

Day 1: Python Essentials

• 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

Day 2: Data Analysis with pandas

• 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()