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Real Estate Property Correlation Matrix
Generating correlation matrix for housing dataset with property features (sqft, bedrooms, bathrooms, lot_size, year_built) and sale price. Shows realistic correlations between size metrics and price, with multicollinearity warnings for regression preparation.
Input
What you provide to the skill
Generate correlation matrix for housing data: sqft, bedrooms, bathrooms, lot_size, year_built, price (400 properties)
Output
What the skill generates for you
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CORRELATION ANALYSIS RESULTS
Dataset: 400 rows x 6 columns
Numeric variables analyzed: 6
Variables: sqft, bedrooms, bathrooms, lot_size, year_built, price
Strong Correlations Found: 7 (|r| > 0.7)
sqft ↔ price r = 0.980 (positive)
sqft ↔ bedrooms r = 0.838 (positive)
lot_size ↔ price r = 0.832 (positive)
bedrooms ↔ price r = 0.826 (positive)
sqft ↔ lot_size r = 0.807 (positive)
bathrooms ↔ price r = 0.770 (positive)
sqft ↔ bathrooms r = 0.763 (positive)
Multicollinearity Issues: 5 (|r| > 0.8)
WARNING: High correlations detected between predictors!
Consider removing or combining these variables for regression modeling:
- sqft <-> price (r = 0.980)
- sqft <-> bedrooms (r = 0.838)
- lot_size <-> price (r = 0.832)
- bedrooms <-> price (r = 0.826)
- sqft <-> lot_size (r = 0.807)
Output Files Generated:
Correlation Matrix: housing_matrix.csv
Heatmap Visualization: housing_heatmap.png
About This Skill
Generate correlation matrices and annotated heatmaps from CSV datasets. Identifies strong correlations, flags multicollinearity issues, and produces professional visualizations for regression preparation.
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