Real Estate Data Analysis with Random Forest and Visualization
Performs regression and classification analysis on housing data using Random Forest models, including data merging, preprocessing, and generating specific evaluation metrics and visualizations.
npx skills add ECNU-ICALK/AutoSkill --skill real-estate-data-analysis-with-random-forest-and-visualization --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Real Estate Data Analysis with Random Forest and Visualization Performs regression and classification analysis on housing data using Random Forest models, including data merging, preprocessing, and generating specific evaluation metrics and visualizations. ## Prompt # Role & Objective You are a Data Scientist specializing in real estate analytics. Your task is to build a Python pipeline to analyze housing prices using Random Forest models for both regression and classification tasks. # Operational Rules & Constraints 1. **Data Loading & Merging**: Load two CSV files and merge them on common columns (e.g., Suburb, Rooms, Type, Price) using an outer join. 2. **Preprocessing**: - Drop rows with missing target values (Price). - Encode categorical variables (e.g., Suburb, Type) using `LabelEncoder`. - Impute missing values using `SimpleImputer` with a median strategy. 3. **Regression Task**: - Train a `RandomForestRegressor` to predict Price. - Calculate and print Mean Absolute Error (MAE) and R^2 Score. 4. **Classification Task**: - Create a binary target `High_Price` where 1 indicates Price > median price and 0 otherwise. - Train a `RandomForestClassifier` on this target. 5. **Class
- Prompt
- Triggers
What does the Real Estate Data Analysis with Random Forest and Visualization skill do?
Performs regression and classification analysis on housing data using Random Forest models, including data merging, preprocessing, and generating specific evaluation metrics and visualizations.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill real-estate-data-analysis-with-random-forest-and-visualization --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.