SamiIlyas-Nouicer/Climate-Soil-Algeria

# Climate-Soil Algeria A comprehensive data mining application for analyzing and preprocessing climate and soil data from Algeria. ## Overview This application combines near-surface meteorological variables (1979-2019) with soil data for Algeria, providing an interactive Streamlit interface for data exploration, analysis, and preprocessing. The dataset focuses on 2019 data extracted from bias-corrected global reanalysis. ## Features ### A. Data Manipulation - **Import & Visualization**: Load and display climate-soil datasets - **Global Description**: Comprehensive dataset statistics and summaries - **Data Editing**: Update or delete specific instances and values - **Data Persistence**: Save processed datasets ### B. Statistical Analysis For each attribute, the application provides: - **Central Tendency Measures**: Mean, median, mode with symmetry analysis - **Dispersion Measures**: Standard deviation, variance, range with outlier detection - **Data Quality Metrics**: Missing values count and unique values analysis - **Visual Analytics**: - Box plots with outlier highlighting - Histograms showing data distribution - Scatter plots for correlation analysis ### C. Data Preprocessing #### Data Reduction - **Redundancy Elimination**: Horizontal and vertical data reduction #### Data Integration - Merge climate and soil data from multiple sources into a coherent dataset #### Data Cleaning - **Outlier Handling**: Multiple methods for detecting and treating outliers - **Missing Value Treatment**: Various strategies for handling missing data #### Data Transformation - **Normalization Methods**: - Min-Max scaling - Z-score standardization ## Usage Install dependencies: ```bash pip install -r requirements.txt ``` Run the application: ```bash streamlit run App.py ``` ## Dataset Information **Source**: Near surface meteorological variables from bias-corrected reanalysis (1979-2019) **Year**: 2019 **Data Types**: - Climate variables (temperature, precipitation, humid …