This is the Python Project
Short: Exploratory Data Analysis and basic predictive modeling on a building assets dataset using Python (Pandas, NumPy, Matplotlib, Seaborn, scikit-learn).
- Objective: Clean dataset, explore key features, detect outliers, visualize relationships, and train a simple linear regression to understand drivers of the target variable.
- Dataset: Public/private Excel file containing building-related features (location, square footage, construction date, lat/long, etc.).
- Data loading and inspection (
df.info(),df.describe()) - Missing value handling and justification for chosen strategy
- Outlier detection using Z-score and rationale
- Visualizations (heatmap, boxplots, pairplots, scatter plots)
- Simple Linear Regression to study relationships between selected features and the target
- Summary, key findings and recommendations
pip install -r requirements.txt
python analysis_notebook.ipynb # or open in Jupyter / Colab