# Documentation Update Summary - Multi-Timeframe Aggregation (Issue #9)

## Overview
Documentation has been successfully updated to reflect the new multi-timeframe OHLCV aggregation feature.

## Files Updated

### 1. CHANGELOG.md
Location: /Users/andrewkaszubski/Dev/Spektiv/CHANGELOG.md

Added comprehensive entry under "[Unreleased] Added" section:
- Multi-timeframe OHLCV aggregation functions (Issue #9)
- 19 sub-entries documenting:
  - Module location and size (320 lines)
  - Core validation and resampling functions
  - OHLCV aggregation rules (Open=first, High=max, Low=min, Close=last, Volume=sum)
  - Weekly aggregation with Sunday/Monday anchors
  - Monthly aggregation with period-end/start options
  - Timezone preservation
  - Test coverage: 29 unit tests + 13 integration tests = 42 total tests

Format: Follows Keep a Changelog standard with file:line references for code locations

### 2. docs/api/dataflows.md
Location: /Users/andrewkaszubski/Dev/Spektiv/docs/api/dataflows.md

Added new "Multi-Timeframe Aggregation" section with:
- Module location: spektiv/dataflows/multi_timeframe.py
- Capabilities (weekly/monthly conversion, timezone preservation, partial periods)
- Setup requirements (pandas only, no external dependencies)
- Feature summary (OHLCV rules, week anchors, error handling)
- Practical code example with:
  - Sample data creation
  - Weekly aggregation (Sunday and Monday anchors)
  - Monthly aggregation (period-end and period-start)
- Available functions documentation:
  - aggregate_to_weekly(data, anchor='SUN')
  - aggregate_to_monthly(data, period_end=True)
- Return format details (DataFrame on success, error string on failure)
- Error handling examples
- Validation requirements
- Timezone handling notes

Location in file: Inserted between FRED API integration and Local Cache sections (maintains logical grouping of data sources/utilities)

## Test Coverage Verified
- Unit tests: 29 tests in tests/unit/dataflows/test_multi_timeframe.py
- Integration tests: 13 tests in tests/integration/dataflows/test_multi_timeframe_integration.py
- Total: 42 tests passing

## Implementation Verified
- Module: spektiv/dataflows/multi_timeframe.py (320 lines)
- Public functions: aggregate_to_weekly(), aggregate_to_monthly()
- Private functions: _validate_ohlcv_dataframe(), _resample_ohlcv()
- All functions have comprehensive docstrings with examples

## Cross-References Validated
- File links in CHANGELOG verified against actual file locations
- Code line ranges accurate for all referenced functions
- API documentation examples are executable and follow module API
- No broken links or missing references

## Documentation Quality
- Concise and actionable (best practices applied)
- Consistent formatting with existing documentation
- Complete API coverage (parameters, return types, errors)
- Real-world usage examples provided
- Clear error handling patterns demonstrated

## Key Features Documented
1. OHLCV Aggregation Rules
   - Open: first value
   - High: maximum value
   - Low: minimum value
   - Close: last value
   - Volume: sum of volumes

2. Weekly Aggregation (aggregate_to_weekly)
   - Sunday anchor (default)
   - Monday anchor
   - Automatic day-of-week mapping
   - Partial week handling

3. Monthly Aggregation (aggregate_to_monthly)
   - Month-end labeling
   - Month-start labeling
   - Partial month handling

4. Input Validation
   - Non-empty DataFrame check
   - DatetimeIndex requirement
   - OHLCV column presence

5. Timezone Support
   - UTC timezone preservation
   - Localized timezone support (e.g., America/New_York)
   - Transparent handling in aggregation

## Notes
- No changes required to README.md (dataflows are internal API)
- Multi-timeframe functions are part of spektiv.dataflows module
- All documentation uses consistent formatting and structure
- Examples follow project code style conventions
- Error handling patterns documented for developers