ngusadeep/Tourism-EDA

EDA and predictive modeling for Tanzania’s tourism sector to uncover insights and forecast visitor trends. ### **📊 Exploratory Data Analysis and Prediction: Tourism Sector in Tanzania** ## 📌 Project Overview Tourism is one of Tanzania’s largest economic drivers, known for its rich wildlife, cultural heritage, and world-class destinations. This project performs **Exploratory Data Analysis (EDA)** on tourism data to extract insights about visitor trends and develops a **classification model** to predict tourism outcomes such as visitor flow categories and market segments. The results aim to empower policymakers, stakeholders, and tourism boards to make **evidence-based decisions** for sustainable growth of the sector. --- ## 🎯 Objectives 1. **Exploratory Data Analysis (EDA):** - Study **visitor demographics**, **spending patterns**, and **seasonal trends**. - Analyze **tour package preferences** and **popular activities**. - Identify **top source countries** for tourists. 2. **Predictive Modeling:** - Build a **classification model** to predict: - Tourist flow categories (e.g., **"High"**, **"Medium"**, **"Low"**). - Tourist segmentation based on origin or package selection. - Provide data-driven insights for strategic planning. --- ## 📂 Dataset Description | Column Name | Description | | ------------------ | ----------------------------------------------------------------------- | | `id` | Unique identifier for each tourist | | `country` | Country of origin of the tourist | | `age_group` | Age group category of the tourist | | `travel_with` | Relation of people the tourist traveled with | | `total_female` | Total number of females in the travel group | | `total_male` | Total number of males in the travel group | | `purpose` | Purpose of visitin …