RSK World - Weather Forecasting Dataset | Time Series | ML Models | Anomaly Detection | RSK World

Weather Data Time Series ML Ready Air Quality Forecasting CSV/JSON

This project features a comprehensive Weather Forecasting dataset designed for professional weather analysis, climate research, and machine learning. The dataset includes historical weather data for 5 major Indian cities (New Delhi, Mumbai, Bangalore, Kolkata, Chennai) with 35+ weather parameters including temperature, humidity, atmospheric pressure, wind speed/direction, precipitation, cloud cover, visibility, UV index, air quality (AQI, PM2.5, PM10, Ozone, NO2, SO2, CO), solar radiation, soil temperature/moisture, heat index, wind chill, and dew point. The package includes 5 advanced Python scripts: weather_analysis.py, data_preprocessing.py, ml_models.py (Linear Regression, Ridge, Lasso, Random Forest, Gradient Boosting, XGBoost, SVR, LSTM), and anomaly_detection.py (Z-score, IQR, Isolation Forest, LOF). Features include LSTM neural networks with TensorFlow/Keras, Flask Weather API simulation with REST endpoints, interactive Chart.js dashboards with real-time analytics, and comprehensive Jupyter notebook tutorials. Includes 9 data files: weather_data.csv (120+ records), weather_advanced.csv (35+ parameters), weather_alerts.csv, weather_forecast_comparison.csv, seasonal_statistics.csv, locations.csv, weather_hourly_extended.csv, weather_data.json, and dataset_info.json. Complete with professional documentation and demo webpage. Perfect for data scientists, researchers, students, and developers working on weather prediction, climate analysis, time series forecasting, and environmental monitoring.

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Dataset Overview

Complete weather data with 35+ parameters including temperature, humidity, pressure, wind, air quality, and more for 5 major Indian cities.

Temperature (Celsius, Fahrenheit, Feels-like)
Humidity, Pressure, Dew Point
Wind Speed, Direction, Gust
Precipitation, Cloud Cover, Visibility
5 Cities: Delhi, Mumbai, Bangalore, Kolkata, Chennai
Air Quality Index (AQI, PM2.5, PM10)
Solar Radiation, UV Index
Soil Temperature & Moisture
9 Data Files (CSV + JSON)
120+ Weather Records
Perfect for ML & Time Series Forecasting

Data Quality & Files

Clean, validated weather data with comprehensive data files and preprocessing utilities.

weather_data.csv - Main dataset (120+ records)
weather_advanced.csv - 35+ parameters
weather_alerts.csv - Alert & warning data
weather_forecast_comparison.csv - Model evaluation
seasonal_statistics.csv - Monthly aggregates
locations.csv - City information
weather_hourly_extended.csv - Hourly data
weather_data.json - JSON format
dataset_info.json - Metadata
No missing values - Clean dataset
Date parsing with indexing support

Weather Analysis

Comprehensive analysis tools with statistical analysis, visualization, and pattern detection.

Summary statistics for all parameters
Temperature trend visualization
Humidity & pressure analysis
Wind pattern analysis
Precipitation tracking
Seasonal pattern detection
Location comparison tools
Correlation matrix analysis
Air quality trend analysis
Beautiful Matplotlib/Seaborn visualizations
Export capabilities

Weather Forecasting

Advanced forecasting capabilities with multiple prediction models and evaluation metrics.

Multi-day weather forecasting
Temperature prediction models
Humidity & pressure forecasting
Precipitation probability
Walk-forward validation
Forecast comparison tools
Performance metrics (RMSE, MAE, MAPE)
Confidence interval calculation
Residual analysis
Trend and seasonality detection
Visualization of predictions vs actuals

Machine Learning Models

Advanced ML models including LSTM neural networks, Random Forest, XGBoost, and more.

Linear Regression - Baseline
Ridge/Lasso Regression - Regularized
Random Forest Regressor
Gradient Boosting Regressor
XGBoost - Optimized boosting
Support Vector Regression (SVR)
LSTM Neural Network (TensorFlow/Keras)
Automatic feature engineering
Cross-validation support
Hyperparameter tuning
Feature importance analysis
Model comparison framework

Anomaly Detection

Multiple anomaly detection algorithms to identify unusual weather patterns and extreme events.

Z-score anomaly detection
IQR (Interquartile Range) method
Isolation Forest algorithm
Local Outlier Factor (LOF)
Moving average deviation
Extreme weather event detection
Multi-parameter anomaly analysis
Automated report generation
Configurable thresholds
Visualization of anomalies
Historical pattern comparison

What You Get

Complete package with 20+ files for professional weather analysis and forecasting.

9 Data files (CSV + JSON)
5 Python scripts (2,500+ lines of code)
Jupyter notebook for analysis
Flask Weather API simulation
Interactive Chart.js dashboard
Professional demo webpage (index.html)
Comprehensive README.md
CHANGELOG.md version history
Requirements.txt for easy setup
Educational License included
preview-generator.html tool

Weather API Simulation

Flask-based Weather API with REST endpoints for testing and development.

Flask-based REST API
/api/weather/current - Current weather
/api/weather/forecast - Multi-day forecast
/api/alerts - Weather alerts
/api/locations - Available locations
Realistic data generation
JSON response format
Query parameter support
CORS enabled
Easy to extend and customize
Perfect for frontend development

Interactive Dashboard

Advanced analytics dashboard with Chart.js visualizations and real-time stats.

Real-time stat cards
Temperature trend line charts
Weather distribution (doughnut chart)
Humidity vs Temperature scatter plot
Location comparison bar charts
Data table with export capability
Active weather alerts panel
Dark theme modern design
Fully responsive layout
Interactive tooltips
Range selectors and filters

Air Quality & Environment

Comprehensive air quality and environmental data for pollution analysis and health studies.

Air Quality Index (AQI)
PM2.5 - Fine particulate matter
PM10 - Coarse particulate matter
Ozone (O3) - Ground-level ozone
NO2 - Nitrogen dioxide
SO2 - Sulfur dioxide
CO - Carbon monoxide
Solar radiation (W/m²)
Soil temperature & moisture
UV Index measurements
Environmental impact analysis

Credits & Acknowledgments

This dataset is provided for educational and research purposes. Core technologies and libraries are credited below.

Python 3.8+ - Programming language (PSF License)
Pandas - Data manipulation (BSD License)
NumPy - Numerical computing (BSD License)
Scikit-learn - Machine learning (BSD License)
TensorFlow/Keras - LSTM models (Apache 2.0)
Matplotlib - Visualization (PSF License)
Flask - API development (BSD License)
RSK World - Dataset creator and provider
GitHub Repository - Source code and releases
Author: Molla Samser | Designer: Rima Khatun
Educational License - Free for learning & research

Support & Contact

For commercial use, custom datasets, or integration help, please contact us.

Email: help@rskworld.in
Phone: +91 93305 39277
Website: RSKWORLD.in
Location: Nutanhat, Mongolkote, West Bengal, India
Author: Molla Samser
Designer & Tester: Rima Khatun
GitHub: Coming Soon
Weather Forecasting Dataset Documentation
Technical Support Available
Custom Dataset Requests Welcome

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Weather Forecasting Dataset

Dataset Overview

Data Quality & Files

Weather Analysis

Weather Forecasting

Machine Learning Models

Anomaly Detection

What You Get

Weather API Simulation

Interactive Dashboard

Air Quality & Environment

Credits & Acknowledgments

Support & Contact

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Additional Sponsored Content

Download Free Source Code

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