watutwelydiah-byte/kenya_road_accidents_analysis

Kenya road accidents analysis using Python, Pandas, Matplotlib, and real-world accident data. # Kenya Road Accident Analysis A Python data analysis project that explores road accident data in Kenya for the years **2016** and **2017**. The project focuses on cleaning, combining, profiling, and visualizing accident records to uncover patterns that could support road safety awareness and data-driven decision-making. ## Project Objectives The main objectives of this project are to: - Clean and preprocess raw accident data. - Merge datasets from multiple years into a single dataset. - Standardize inconsistent column names. - Handle missing values and duplicate records. - Perform exploratory data analysis (EDA). - Visualize accident trends across counties and victim categories. - Export a cleaned dataset for future analysis. ## Dataset The dataset contains road accident records reported in Kenya for the years **2016** and **2017**. ### Features include: - Date of accident - County - Road - Place - Victim type - Gender - Age - Accident description - Other accident-related information ## Technologies Used - Python - Pandas - NumPy - Matplotlib ## Data Cleaning Process The following preprocessing steps were performed: - Loaded accident records from two Excel worksheets (2016 and 2017) - Removed unnecessary columns - Standardized column names - Matched columns between both datasets - Combined the datasets into one DataFrame - Removed duplicate records - Converted the date column to datetime format - Extracted additional features: - Year - Month - Day of the week - Exported the cleaned dataset as a CSV file ## Exploratory Data Analysis The analysis includes: ### 1. County Analysis Identified the counties with the highest number of recorded accidents. ### 2. Victim Type Analysis Examined the most common categories of accident victims. ### 3. Data Profiling Generated descriptive statistics for numerical variables such as age and assessed missing values across the dataset. ## Visualizations #### Top 10 Counties by Number of Accidents #### Most Comm …