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mayor124/Nigerian-Car-Analytics-Dashboard-Market-Trends-Buyer-Behavior-using-excel

Domaine:

socioeconomic

Type de record:

dataset
Créateur:
may
Hôte:
An interactive dashboard analyzing over 2,800 Nigerian car listings to reveal market trends, popular brands, price averages, color choices, and buyer preferences. Toyota leads the market, with most cars being foreign used and automatic, reflecting Nigeria’s shift toward convenience and reliability. # Project Objective: The objective of this project is to analyze and visualize trends in the Nigerian automotive market using car listing data. It aims to uncover insights into vehicle pricing, brand popularity, regional distribution, fuel and transmission preferences, and overall buyer behavior. By transforming raw data into actionable insights, the project helps car dealers, analysts, and investors make informed business decisions and understand key market dynamics. ## dataset used - Nigerian Car Market dataset ## questions answerded What is the average price and mileage of cars sold in Nigeria? Which brands and models are most popular among Nigerian buyers? Do Nigerians prefer brand-new or used cars? Which regions have the highest car listings and purchases? What are the most common car colors in Nigeria? Which transmission type do Nigerian drivers prefer — manual or automatic? How does engine size or horsepower vary by car brand or model? What is the distribution of car types (SUVs, sedans, etc.) across regions? ## dashbaord interaction - dashboard ## Project Process Data Collection: The dataset was obtained from Car45, containing over 2,800 vehicle listings across Nigeria with features such as price, brand, model, color, mileage, engine size, transmission, and region. Data Cleaning & Preparation: Removed duplicates and irrelevant columns. Handled missing values in columns like mileage, engine size, and horse_power. Standardized categorical data (e.g., “Foreign Used”, “Nigerian Used”). Converted data types (e.g., year, amount, mileage) for accurate analysis. Data Transformation: Created calculated fields such as average price, average mileage, and average horsepower. Grouped data by region, car brand, and condition to identify trends. Extracted useful metrics for KPI visuals. Exploratory Data Analysis (EDA): Conducted descriptive analysis to understand data distribution. Identified top-selling brands, common fuel types, and popula …

Visit

github.com

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