mohit637840/algerian-forest-fire-eda

# Algerian Forest Fire Data Analysis ## Overview This project performs data cleaning and exploratory data analysis (EDA) on the Algerian Forest Fires dataset. The dataset contains weather observations and fire indices from two regions: Bejaia and Sidi Bel-Abbes. ## Dataset Description The dataset includes: - Weather data: Temperature, Humidity, Wind Speed, Rain - Fire Weather Index (FWI) components - Target variable indicating fire occurrence ## Data Preprocessing - Handled missing values and removed invalid rows - Created a new feature "Region" to distinguish between two locations - Cleaned column names and fixed formatting issues - Converted string-based numerical columns into numeric format - Processed target variable into binary form: - 0 → Not Fire - 1 → Fire ## Exploratory Data Analysis - Distribution of fire vs non-fire cases - Relationship between temperature and fire occurrence - Analysis of Fire Weather Index (FWI) - Correlation analysis between features ## Key Insights - Higher temperature and FWI values are associated with fire occurrences - Weather conditions play a significant role in fire prediction - Data cleaning was essential due to inconsistencies in the raw dataset ## Tools Used - Python - pandas - NumPy - Matplotlib - Seaborn ## Future Work - Apply machine learning models for fire prediction - Perform feature selection and model evaluation