khajuriakrishna18-maker/Algerian-Forest-Fires-Dataset-Analysis-and-Fire-Classification-EDA-Data-Preprocessing-

A data analysis project that cleans, preprocesses, and explores the Algerian Forest Fires dataset. The project performs data cleaning, feature type conversion, exploratory data analysis (EDA), correlation analysis, and visualization to identify patterns associated with forest fire occurrences in different Algerian regions. README.md Algerian Forest Fires Dataset Analysis Overview This project focuses on preprocessing and exploratory data analysis (EDA) of the Algerian Forest Fires Dataset. The objective is to clean the dataset, analyze fire-related patterns, and understand the relationships between meteorological features and fire occurrence. Dataset Information The dataset contains weather and fire weather indices collected from two regions in Algeria: Bejaia Region Sidi Bel-Abbes Region Features include: Temperature Relative Humidity (RH) Wind Speed (Ws) Rain FFMC (Fine Fuel Moisture Code) DMC (Duff Moisture Code) DC (Drought Code) ISI (Initial Spread Index) BUI (Build-Up Index) FWI (Fire Weather Index) Fire Class (Fire / Not Fire) Project Workflow 1. Data Cleaning Loaded the raw dataset Handled missing values Removed invalid records Assigned region labels Renamed and cleaned column names Converted columns to appropriate data types 2. Data Preprocessing Converted categorical labels into numerical values Created a cleaned dataset for analysis Saved the processed dataset for future use 3. Exploratory Data Analysis (EDA) Distribution analysis using histograms Fire vs Non-Fire class distribution Correlation analysis Heatmap visualization Outlier detection using boxplots Regional fire occurrence analysis 4. Visualization The project includes: Histograms Pie Charts Correlation Heatmaps Boxplots Countplots for monthly fire occurrences Technologies Used Python Pandas NumPy Matplotlib Seaborn Jupyter Notebook Key Insights Explores relationships between weather conditions and forest fire occurrences. Identifies highly correlated fire weather indices. Compares fire trends across Algerian regions. Visualizes class imbalance between fire and non-fire events.