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RSK World
housing-prices
RSK World
housing-prices
Housing Price Prediction Dataset - Real Estate ML + Price Prediction AI + Housing Price Deep Learning
housing-prices
  • __pycache__
  • .gitignore714 B
  • ADVANCED_FEATURES.md5.2 KB
  • LICENSE.txt1.5 KB
  • PROJECT_STRUCTURE.txt4.3 KB
  • README.md5.1 KB
  • advanced_models.py10.3 KB
  • data_analysis.py3.3 KB
  • data_visualization.py5.3 KB
  • dataset_info.txt3.5 KB
  • feature_engineering.py9.5 KB
  • housing_price_prediction.ipynb9.4 KB
  • housing_prices.csv4.8 KB
  • housing_prices.json23.7 KB
  • hyperparameter_tuning.py9.9 KB
  • index.html11.2 KB
  • model_comparison.py8.1 KB
  • predict_price.py4.6 KB
  • requirements.txt620 B
  • test_project.py6.8 KB
  • validate_data.py2.7 KB
dataset_info.txthousing_prices.json
dataset_info.txt
Raw Download
Find: Go to:
Housing Price Prediction Dataset - Dataset Information
RSK World - Free Programming Resources & Source Code
Website: https://rskworld.in
Contact: help@rskworld.in, support@rskworld.in
Phone: +91 93305 39277
Founder: Molla Samser
Designer & Tester: Rima Khatun
Created: 2026

================================================================================
DATASET INFORMATION
================================================================================

Dataset Name: Housing Price Prediction Dataset
Category: Tabular Data
Difficulty: Beginner
Total Records: 50 properties
Total Features: 20 columns

================================================================================
FEATURE DESCRIPTIONS
================================================================================

id              : Unique identifier for each property
price           : Sale price of the property (target variable)
bedrooms        : Number of bedrooms
bathrooms       : Number of bathrooms (can include half baths like 2.25)
sqft_living     : Square footage of interior living space
sqft_lot        : Square footage of land lot
floors          : Number of floors/levels in the house
waterfront      : Binary indicator (0=no, 1=yes) for waterfront view
view            : Quality of view rating (0-4 scale)
condition       : Overall condition rating (1-5 scale)
grade           : Overall grade/quality rating (1-13 scale)
sqft_above      : Square footage above ground level
sqft_basement   : Square footage of basement
yr_built        : Year the house was originally built
yr_renovated    : Year of last renovation (0 if never renovated)
zipcode         : ZIP code of property location
lat             : Latitude coordinate
long            : Longitude coordinate
sqft_living15   : Average sqft of interior living space of 15 nearest neighbors
sqft_lot15      : Average sqft of land lot of 15 nearest neighbors
neighborhood    : Name of the neighborhood

================================================================================
USE CASES
================================================================================

1. Regression Analysis: Predict house prices based on features
2. Feature Engineering: Create new features from existing ones
3. Exploratory Data Analysis: Understand relationships between variables
4. Machine Learning: Train and evaluate regression models
5. Data Visualization: Create charts and plots for insights

================================================================================
RECOMMENDED MODELS
================================================================================

- Linear Regression
- Random Forest Regressor
- Gradient Boosting Regressor
- Ridge/Lasso Regression
- Support Vector Regression

================================================================================
FILE FORMATS
================================================================================

- CSV: housing_prices.csv (comma-separated values)
- JSON: housing_prices.json (JavaScript Object Notation)

================================================================================
DEPENDENCIES
================================================================================

See requirements.txt for full list. Key libraries:
- pandas: Data manipulation and analysis
- numpy: Numerical computing
- scikit-learn: Machine learning algorithms
- matplotlib: Data visualization
- seaborn: Statistical visualization

================================================================================

86 lines•3.5 KB
text
housing_prices.json
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[
  {
    "id": 1,
    "price": 221900,
    "bedrooms": 3,
    "bathrooms": 1.0,
    "sqft_living": 1180,
    "sqft_lot": 5650,
    "floors": 1,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 7,
    "sqft_above": 1180,
    "sqft_basement": 0,
    "yr_built": 1955,
    "yr_renovated": 0,
    "zipcode": 98178,
    "lat": 47.5112,
    "long": -122.257,
    "sqft_living15": 1340,
    "sqft_lot15": 5650,
    "neighborhood": "Greenwood"
  },
  {
    "id": 2,
    "price": 538000,
    "bedrooms": 3,
    "bathrooms": 2.25,
    "sqft_living": 2570,
    "sqft_lot": 7242,
    "floors": 2,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 7,
    "sqft_above": 2170,
    "sqft_basement": 400,
    "yr_built": 1951,
    "yr_renovated": 1991,
    "zipcode": 98125,
    "lat": 47.721,
    "long": -122.319,
    "sqft_living15": 1690,
    "sqft_lot15": 7639,
    "neighborhood": "Northgate"
  },
  {
    "id": 3,
    "price": 180000,
    "bedrooms": 2,
    "bathrooms": 1.0,
    "sqft_living": 770,
    "sqft_lot": 10000,
    "floors": 1,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 6,
    "sqft_above": 770,
    "sqft_basement": 0,
    "yr_built": 1933,
    "yr_renovated": 0,
    "zipcode": 98028,
    "lat": 47.7379,
    "long": -122.233,
    "sqft_living15": 2720,
    "sqft_lot15": 8062,
    "neighborhood": "Kenmore"
  },
  {
    "id": 4,
    "price": 604000,
    "bedrooms": 4,
    "bathrooms": 3.0,
    "sqft_living": 1960,
    "sqft_lot": 5000,
    "floors": 1,
    "waterfront": 0,
    "view": 0,
    "condition": 5,
    "grade": 7,
    "sqft_above": 1050,
    "sqft_basement": 910,
    "yr_built": 1965,
    "yr_renovated": 0,
    "zipcode": 98136,
    "lat": 47.5208,
    "long": -122.393,
    "sqft_living15": 1360,
    "sqft_lot15": 5000,
    "neighborhood": "West Seattle"
  },
  {
    "id": 5,
    "price": 510000,
    "bedrooms": 3,
    "bathrooms": 2.0,
    "sqft_living": 1680,
    "sqft_lot": 8080,
    "floors": 1,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 8,
    "sqft_above": 1680,
    "sqft_basement": 0,
    "yr_built": 1987,
    "yr_renovated": 0,
    "zipcode": 98074,
    "lat": 47.6168,
    "long": -122.045,
    "sqft_living15": 1800,
    "sqft_lot15": 7503,
    "neighborhood": "Sammamish"
  },
  {
    "id": 6,
    "price": 1225000,
    "bedrooms": 4,
    "bathrooms": 4.5,
    "sqft_living": 5420,
    "sqft_lot": 101930,
    "floors": 1,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 11,
    "sqft_above": 3890,
    "sqft_basement": 1530,
    "yr_built": 2001,
    "yr_renovated": 0,
    "zipcode": 98053,
    "lat": 47.6561,
    "long": -122.005,
    "sqft_living15": 4760,
    "sqft_lot15": 101930,
    "neighborhood": "Issaquah"
  },
  {
    "id": 7,
    "price": 257500,
    "bedrooms": 3,
    "bathrooms": 2.25,
    "sqft_living": 1715,
    "sqft_lot": 6819,
    "floors": 2,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 7,
    "sqft_above": 1715,
    "sqft_basement": 0,
    "yr_built": 1995,
    "yr_renovated": 0,
    "zipcode": 98003,
    "lat": 47.3097,
    "long": -122.327,
    "sqft_living15": 2238,
    "sqft_lot15": 6819,
    "neighborhood": "Federal Way"
  },
  {
    "id": 8,
    "price": 291850,
    "bedrooms": 3,
    "bathrooms": 1.5,
    "sqft_living": 1060,
    "sqft_lot": 9711,
    "floors": 1,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 7,
    "sqft_above": 1060,
    "sqft_basement": 0,
    "yr_built": 1963,
    "yr_renovated": 0,
    "zipcode": 98198,
    "lat": 47.4095,
    "long": -122.315,
    "sqft_living15": 1650,
    "sqft_lot15": 9711,
    "neighborhood": "Des Moines"
  },
  {
    "id": 9,
    "price": 229500,
    "bedrooms": 3,
    "bathrooms": 1.0,
    "sqft_living": 1780,
    "sqft_lot": 7470,
    "floors": 1,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 7,
    "sqft_above": 1050,
    "sqft_basement": 730,
    "yr_built": 1960,
    "yr_renovated": 0,
    "zipcode": 98146,
    "lat": 47.5123,
    "long": -122.337,
    "sqft_living15": 1780,
    "sqft_lot15": 8113,
    "neighborhood": "White Center"
  },
  {
    "id": 10,
    "price": 323000,
    "bedrooms": 3,
    "bathrooms": 2.5,
    "sqft_living": 1890,
    "sqft_lot": 6560,
    "floors": 2,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 7,
    "sqft_above": 1890,
    "sqft_basement": 0,
    "yr_built": 2003,
    "yr_renovated": 0,
    "zipcode": 98038,
    "lat": 47.3684,
    "long": -122.031,
    "sqft_living15": 2390,
    "sqft_lot15": 7570,
    "neighborhood": "Maple Valley"
  },
  {
    "id": 11,
    "price": 662500,
    "bedrooms": 3,
    "bathrooms": 2.5,
    "sqft_living": 3560,
    "sqft_lot": 9796,
    "floors": 1,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 8,
    "sqft_above": 1860,
    "sqft_basement": 1700,
    "yr_built": 1965,
    "yr_renovated": 0,
    "zipcode": 98052,
    "lat": 47.6311,
    "long": -122.031,
    "sqft_living15": 2440,
    "sqft_lot15": 9796,
    "neighborhood": "Redmond"
  },
  {
    "id": 12,
    "price": 468000,
    "bedrooms": 2,
    "bathrooms": 1.0,
    "sqft_living": 1160,
    "sqft_lot": 6000,
    "floors": 1,
    "waterfront": 0,
    "view": 0,
    "condition": 4,
    "grade": 7,
    "sqft_above": 860,
    "sqft_basement": 300,
    "yr_built": 1942,
    "yr_renovated": 0,
    "zipcode": 98115,
    "lat": 47.6822,
    "long": -122.286,
    "sqft_living15": 1330,
    "sqft_lot15": 6000,
    "neighborhood": "Maple Leaf"
  },
  {
    "id": 13,
    "price": 310000,
    "bedrooms": 3,
    "bathrooms": 2.0,
    "sqft_living": 1430,
    "sqft_lot": 19900,
    "floors": 1,
    "waterfront": 0,
    "view": 0,
    "condition": 4,
    "grade": 7,
    "sqft_above": 1430,
    "sqft_basement": 0,
    "yr_built": 1927,
    "yr_renovated": 0,
    "zipcode": 98107,
    "lat": 47.6769,
    "long": -122.377,
    "sqft_living15": 1430,
    "sqft_lot15": 20000,
    "neighborhood": "Ballard"
  },
  {
    "id": 14,
    "price": 400000,
    "bedrooms": 3,
    "bathrooms": 2.5,
    "sqft_living": 2030,
    "sqft_lot": 8220,
    "floors": 2,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 7,
    "sqft_above": 2030,
    "sqft_basement": 0,
    "yr_built": 2000,
    "yr_renovated": 0,
    "zipcode": 98103,
    "lat": 47.6904,
    "long": -122.356,
    "sqft_living15": 2070,
    "sqft_lot15": 8500,
    "neighborhood": "Fremont"
  },
  {
    "id": 15,
    "price": 530000,
    "bedrooms": 4,
    "bathrooms": 2.5,
    "sqft_living": 2560,
    "sqft_lot": 9000,
    "floors": 2,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 8,
    "sqft_above": 2560,
    "sqft_basement": 0,
    "yr_built": 1993,
    "yr_renovated": 0,
    "zipcode": 98006,
    "lat": 47.5668,
    "long": -122.153,
    "sqft_living15": 2560,
    "sqft_lot15": 9000,
    "neighborhood": "Bellevue"
  },
  {
    "id": 16,
    "price": 650000,
    "bedrooms": 4,
    "bathrooms": 3.0,
    "sqft_living": 2910,
    "sqft_lot": 12000,
    "floors": 2,
    "waterfront": 0,
    "view": 0,
    "condition": 4,
    "grade": 9,
    "sqft_above": 2910,
    "sqft_basement": 0,
    "yr_built": 1997,
    "yr_renovated": 0,
    "zipcode": 98004,
    "lat": 47.6063,
    "long": -122.214,
    "sqft_living15": 2910,
    "sqft_lot15": 12000,
    "neighborhood": "Bellevue"
  },
  {
    "id": 17,
    "price": 395000,
    "bedrooms": 3,
    "bathrooms": 2.5,
    "sqft_living": 1920,
    "sqft_lot": 8000,
    "floors": 2,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 7,
    "sqft_above": 1920,
    "sqft_basement": 0,
    "yr_built": 1989,
    "yr_renovated": 0,
    "zipcode": 98033,
    "lat": 47.6091,
    "long": -122.222,
    "sqft_living15": 1920,
    "sqft_lot15": 8000,
    "neighborhood": "Kirkland"
  },
  {
    "id": 18,
    "price": 485000,
    "bedrooms": 3,
    "bathrooms": 2.0,
    "sqft_living": 2040,
    "sqft_lot": 9850,
    "floors": 2,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 7,
    "sqft_above": 2040,
    "sqft_basement": 0,
    "yr_built": 1995,
    "yr_renovated": 0,
    "zipcode": 98034,
    "lat": 47.7018,
    "long": -122.2,
    "sqft_living15": 2040,
    "sqft_lot15": 9850,
    "neighborhood": "North Kirkland"
  },
  {
    "id": 19,
    "price": 189900,
    "bedrooms": 2,
    "bathrooms": 1.0,
    "sqft_living": 840,
    "sqft_lot": 4000,
    "floors": 1,
    "waterfront": 0,
    "view": 0,
    "condition": 4,
    "grade": 6,
    "sqft_above": 840,
    "sqft_basement": 0,
    "yr_built": 1955,
    "yr_renovated": 0,
    "zipcode": 98023,
    "lat": 47.3028,
    "long": -122.356,
    "sqft_living15": 840,
    "sqft_lot15": 4000,
    "neighborhood": "Federal Way"
  },
  {
    "id": 20,
    "price": 230000,
    "bedrooms": 3,
    "bathrooms": 1.0,
    "sqft_living": 1170,
    "sqft_lot": 5500,
    "floors": 1,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 7,
    "sqft_above": 1170,
    "sqft_basement": 0,
    "yr_built": 1968,
    "yr_renovated": 0,
    "zipcode": 98042,
    "lat": 47.3639,
    "long": -122.14,
    "sqft_living15": 1170,
    "sqft_lot15": 5500,
    "neighborhood": "Renton"
  },
  {
    "id": 21,
    "price": 385000,
    "bedrooms": 4,
    "bathrooms": 2.5,
    "sqft_living": 2360,
    "sqft_lot": 7200,
    "floors": 2,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 8,
    "sqft_above": 2360,
    "sqft_basement": 0,
    "yr_built": 2001,
    "yr_renovated": 0,
    "zipcode": 98027,
    "lat": 47.5261,
    "long": -122.058,
    "sqft_living15": 2360,
    "sqft_lot15": 7200,
    "neighborhood": "Issaquah"
  },
  {
    "id": 22,
    "price": 1180000,
    "bedrooms": 5,
    "bathrooms": 4.5,
    "sqft_living": 4680,
    "sqft_lot": 29000,
    "floors": 2,
    "waterfront": 1,
    "view": 4,
    "condition": 5,
    "grade": 11,
    "sqft_above": 3040,
    "sqft_basement": 1640,
    "yr_built": 2002,
    "yr_renovated": 0,
    "zipcode": 98039,
    "lat": 47.6311,
    "long": -122.241,
    "sqft_living15": 4680,
    "sqft_lot15": 29000,
    "neighborhood": "Medina"
  },
  {
    "id": 23,
    "price": 475000,
    "bedrooms": 3,
    "bathrooms": 2.0,
    "sqft_living": 1620,
    "sqft_lot": 6800,
    "floors": 1,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 7,
    "sqft_above": 820,
    "sqft_basement": 800,
    "yr_built": 1920,
    "yr_renovated": 2002,
    "zipcode": 98117,
    "lat": 47.6975,
    "long": -122.383,
    "sqft_living15": 1620,
    "sqft_lot15": 6800,
    "neighborhood": "Phinney Ridge"
  },
  {
    "id": 24,
    "price": 399950,
    "bedrooms": 3,
    "bathrooms": 2.5,
    "sqft_living": 2100,
    "sqft_lot": 7600,
    "floors": 2,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 8,
    "sqft_above": 2100,
    "sqft_basement": 0,
    "yr_built": 1999,
    "yr_renovated": 0,
    "zipcode": 98056,
    "lat": 47.4969,
    "long": -122.151,
    "sqft_living15": 2100,
    "sqft_lot15": 7600,
    "neighborhood": "Renton"
  },
  {
    "id": 25,
    "price": 365000,
    "bedrooms": 4,
    "bathrooms": 2.0,
    "sqft_living": 2140,
    "sqft_lot": 9600,
    "floors": 1,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 7,
    "sqft_above": 2140,
    "sqft_basement": 0,
    "yr_built": 1987,
    "yr_renovated": 0,
    "zipcode": 98108,
    "lat": 47.5452,
    "long": -122.31,
    "sqft_living15": 2140,
    "sqft_lot15": 9600,
    "neighborhood": "Georgetown"
  },
  {
    "id": 26,
    "price": 289000,
    "bedrooms": 3,
    "bathrooms": 2.0,
    "sqft_living": 1840,
    "sqft_lot": 9100,
    "floors": 1,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 7,
    "sqft_above": 1840,
    "sqft_basement": 0,
    "yr_built": 1991,
    "yr_renovated": 0,
    "zipcode": 98002,
    "lat": 47.3075,
    "long": -122.321,
    "sqft_living15": 1840,
    "sqft_lot15": 9100,
    "neighborhood": "Auburn"
  },
  {
    "id": 27,
    "price": 385000,
    "bedrooms": 3,
    "bathrooms": 2.0,
    "sqft_living": 2360,
    "sqft_lot": 10000,
    "floors": 2,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 7,
    "sqft_above": 2360,
    "sqft_basement": 0,
    "yr_built": 1982,
    "yr_renovated": 0,
    "zipcode": 98031,
    "lat": 47.4788,
    "long": -122.198,
    "sqft_living15": 2360,
    "sqft_lot15": 10000,
    "neighborhood": "Renton"
  },
  {
    "id": 28,
    "price": 549000,
    "bedrooms": 4,
    "bathrooms": 3.0,
    "sqft_living": 2650,
    "sqft_lot": 8500,
    "floors": 2,
    "waterfront": 0,
    "view": 0,
    "condition": 4,
    "grade": 8,
    "sqft_above": 2650,
    "sqft_basement": 0,
    "yr_built": 1998,
    "yr_renovated": 0,
    "zipcode": 98029,
    "lat": 47.5415,
    "long": -122.054,
    "sqft_living15": 2650,
    "sqft_lot15": 8500,
    "neighborhood": "Issaquah"
  },
  {
    "id": 29,
    "price": 445000,
    "bedrooms": 3,
    "bathrooms": 2.5,
    "sqft_living": 2380,
    "sqft_lot": 9200,
    "floors": 2,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 8,
    "sqft_above": 2380,
    "sqft_basement": 0,
    "yr_built": 1994,
    "yr_renovated": 0,
    "zipcode": 98052,
    "lat": 47.6384,
    "long": -122.055,
    "sqft_living15": 2380,
    "sqft_lot15": 9200,
    "neighborhood": "Redmond"
  },
  {
    "id": 30,
    "price": 250000,
    "bedrooms": 3,
    "bathrooms": 2.0,
    "sqft_living": 1800,
    "sqft_lot": 7500,
    "floors": 1,
    "waterfront": 0,
    "view": 0,
    "condition": 3,
    "grade": 7,
    "sqft_above": 1800,
    "sqft_basement": 0,
    "yr_built": 1970,
    "yr_renovated": 0,
    "zipcode": 98055,
    "lat": 47.5694,
    "long": -122.169,
    "sqft_living15": 1800,
    "sqft_lot15": 7500,
    "neighborhood": "Renton"
  },
  {
    "id": 31,
    "price": 549900,
    "bedrooms": 4,
    "bathrooms": 3.5,
    "sqft_living": 2750,
    "sqft_lot": 11000,
    "floors": 2,
    "waterfront": 0,
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1,152 lines•23.7 KB
json

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