[huuan26]

Resolves #32.

Summary

This PR adds support for On-Balance Volume (OBV) as a first-class technical indicator in StockDataFrame.

Features

1. On-Balance Volume (OBV):

   • Exposes df['obv'] as a first-class indicator column.
   • Vectorized computation using NumPy (np.diff, np.sign, np.cumsum):
     • OBV[0] = 0.0
     • OBV[t] = OBV[t-1] + sign(Close[t] - Close[t-1]) * Volume[t]
   • Adds class method StockDataFrame.obv(close, volume).
   • Naturally supports moving averages and crossovers on OBV (e.g. df['obv_10_sma'], df['obv_20_ema'], df['obv_xu_obv_20_ema']).
   • Cleanly handles edge cases (empty series, single-element series, flat price periods).

2. Handler Registration:

   • Registered as ("obv",): self._get_obv in self.handler for exact membership lookup and zero substring collision.

Verification & Documentation

• Added unit tests in test.py:
  • test_obv: Verified against 30-day stock data step-by-step benchmark and moving average calculation (obv_5_sma).
  • test_obv_edge_cases: Verified edge cases (empty series, single-element, flat prices, hand-crafted benchmark verification).
• Updated README.md Summary table, Introduction list, and Volume section with formula and usage examples.
• Code style: flake8 stockstats.py test.py passed with 0 errors.
• Test suite: 137/137 tests passed (96% coverage).

[jealous]

Please help to resolve the conflict.

[huuan26]

Conflicts fixed! Rebased onto latest master, all tests & lint pass cleanly. Plz lmk if any changes are needed

[jealous]

Thanks for the contribution.