🏠 House Price Data Cleaning Script 🧹

A simple and efficient Python script to clean the House Price Prediction dataset. It prepares your data by removing invalid and missing entries, making it ready for analysis or modeling.

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✨ Features

• 📥 Load data from Excel (.xlsx)

• 🔍 Initial data inspection and summary statistics

• 🚫 Remove rows with zero or negative values in critical columns:

  • LotArea, YearBuilt, YearRemodAdd, TotalBsmtSF, SalePrice

• 🧽 Drop rows with missing values

• 🔢 Keep only numeric columns

• 💾 Save cleaned data to a new Excel file

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🚀 Usage

1. Place your dataset here:

   c:\Ds\HousePricePrediction.xlsx
   

2. Run the cleaning script:

   python data_cleaning.py

3. Find the cleaned dataset here:

   Cleaned_HousePricePrediction.xlsx
   

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📊 Output

• Cleaned Excel file with only valid records
• Console printout with the count of remaining records

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⚙️ Requirements

• Python 3.x
• pandas
• openpyxl

Install dependencies:

pip install pandas openpyxl

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📝 Notes

• Adjust zero_check_columns in the script if your dataset has different column names.
• Ideal for preprocessing before machine learning or statistical analysis.