Data Analysis with Python - Complete Module

A comprehensive 11-week course covering data analysis fundamentals using Python and pandas. No previous knowledge of Python is assumed.

Course Overview

This repository contains all workshop materials for the Level 4 Data Analysis with Python module, developed as part of the University of Salford's DipHE Data Science programme. It progresses from Python basics to the use of Pandas, Seaborn, NumPy and SciPy.

Weekly Topics

• Week 1: Python fundamentals
• Week 2: Python data structures (lists, tuples, dictionaries, sets)
• Week 3: Control flow
• Week 4: Functions, modules and libraries
• Week 5: Pandas basics & EDA
• Week 6: Pandas apply, using regex and data visualisation using Seaborn
• Week 7: Data aggregation and pivoting
• Week 8: Joining data in pandas
• Week 9: Data cleaning and preparation
• Week 10: Using GitHub
• Week 11: NumPy and SciPy

Getting Started

Each week's folder contains:

• Workshop notebooks with exercises
• Sample datasets
• Practice materials

For Students

1. Fork this repository to create your own copy
2. Work through each week's materials in order
3. Complete the exercises and save your work
4. Build your portfolio using the GitHub skills from Week 10

For Instructors

• Each folder contains Python notebooks for workshops, along with a version including exercise answers
• All datasets are included and ready to use

Prerequisites

• Basic computer literacy
• No prior programming experience required

Tools Required

• Python 3.11+
• Jupyter Notebook or Google Colab
• GitHub account (Week 11)

Note on Datasets

All datasets, apart from the Palmer Penguins dataset (penguins_size.csv, used for data visualisation in Week 6) are simulated datasets and do not contain real data. They are intended to emulate the kind of datasets students are likely to encounter in the real world and are deliberately designed to include data quality issues.