Data Analysis

Data Analysis Skill

Description

This skill helps analyze datasets and create meaningful visualizations. It can handle CSV files, perform statistical analysis, and generate various types of plots.

Usage Instructions

When a user requests data analysis:

1. Load the dataset: Use pandas to read the data file
2. Inspect the data: Check shape, columns, data types, and basic statistics
3. Clean the data: Handle missing values and outliers if necessary
4. Perform analysis: Calculate relevant statistics based on user's question
5. Create visualizations: Generate appropriate plots (line, bar, scatter, etc.)
6. Save results: Export results and visualizations

Available Resources

Scripts

• scripts/analyze.py: Core analysis functions

  • load_dataset(filepath): Load data from various formats
  • basic_statistics(df): Calculate descriptive statistics
  • detect_outliers(df, column): Identify outliers
  • correlation_analysis(df): Compute correlations

• scripts/visualize.py: Visualization utilities

  • plot_distribution(df, column): Create distribution plots
  • plot_correlation_matrix(df): Visualize correlation heatmap
  • plot_time_series(df, date_col, value_col): Time series plots
  • save_plot(fig, filename): Save figure to file

References

• references/examples.md: Usage examples and common patterns
• references/best_practices.md: Data analysis best practices

Example Prompts

• "Analyze this CSV file and show me the trends"
• "Create a visualization of the sales data by month"
• "Find correlations in this dataset"
• "Identify outliers in the price column"
• "Generate a statistical summary of the data"

Output Format

Analysis results should include:

1. Data overview (shape, columns, types)
2. Statistical summary
3. Key insights and findings
4. Visualizations (saved as PNG files)
5. Recommendations or next steps

Notes

• Always inspect data before analysis
• Handle missing values appropriately
• Choose visualizations that match the data type
• Provide clear explanations of findings
• Save all outputs for user reference

Source: femto/minion — distributed by TomeVault.