vamseeachanta Distribution Analysis (+3)
Distribution Analysis
For numeric columns, characterize the distribution:
- Normal: Mean and median are close, bell-shaped
- Skewed right: Long tail of high values (common for revenue, session duration)
- Skewed left: Long tail of low values (less common)
- Bimodal: Two peaks (suggests two distinct populations)
- Power law: Few very large values, many small ones (common for user activity)
- Uniform: Roughly equal frequency across range (often synthetic or random)
Temporal Patterns
For time series data, look for:
- Trend: Sustained upward or downward movement
- Seasonality: Repeating patterns (weekly, monthly, quarterly, annual)
- Day-of-week effects: Weekday vs. weekend differences
- Holiday effects: Drops or spikes around known holidays
- Change points: Sudden shifts in level or trend
- Anomalies: Individual data points that break the pattern
Segmentation Discovery
Identify natural segments by:
- Finding categorical columns with 3-20 distinct values
- Comparing metric distributions across segment values
- Looking for segments with significantly different behavior
- Testing whether segments are homogeneous or contain sub-segments
Correlation Exploration
Between numeric columns:
- Compute correlation matrix for all metric pairs
- Flag strong correlations (|r| > 0.7) for investigation
- Note: Correlation does not imply causation -- flag this explicitly
- Check for non-linear relationships (e.g., quadratic, logarithmic)