BazelaR/youth-unemployment-analysis

Exploratory Data Analysis of youth unemployment in South Africa # Youth Unemployment Analysis – South Africa (Stats SA QLFS) This project is a simple exploratory data analysis (EDA) of **youth unemployment in South Africa by province**, using data from the Quarterly Labour Force Survey (QLFS). The goal of this project is to practice Python-based data analysis while exploring a real social and economic issue that affects young people. ## Project Goals - Load and explore a real-world dataset (Stats SA QLFS youth unemployment by province and sex) - Filter the data by **year** and **total youth** - Summarise youth unemployment by province - Create a clear visualisation (bar chart) - Practice writing insights and communicating findings ## Data The dataset used is: - `ZA110,DF_UNE_SEX_PROV,1.0+all.csv` Key columns: - `REF_AREA` – Province code (e.g. GP, KZN, WC) - `SEX` – Sex category (`_T` = total, `M` = male, `F` = female) - `TIME_PERIOD` – Quarter & year (e.g. `2023-Q1`) - `OBS_VALUE` – Number of unemployed youth (in thousands) - `UNIT_MEASURE` – Unit of measure (`PS` = persons) - `UNIT_MULT` – Multiplier (`3` = thousands) In this first version of the project, the analysis focuses on: - **Total youth unemployment (`SEX = "_T"`)** - **Year 2023** - **Average number of unemployed youth per province in 2023** ## Tools & Technologies - Python - Pandas - Matplotlib - Jupyter Notebook / Google Colab - GitHub (for version control and portfolio) ## Notebook Main analysis notebook: - `youth_unemployment_eda.ipynb` This notebook includes: 1. Loading the dataset 2. Filtering to total youth (`SEX = "_T"`) 3. Filtering to a specific year (`2023`) 4. Mapping province codes to province names 5. Calculating average youth unemployment per province 6. Visualising the results using a bar chart 7. Writing short insights based on the chart ## Example Visualisation - **Bar chart:** Average youth unemployment (thousands) by province for 2023 This gives a quick view of which provinces have the highest and lowest numbers of unempl …