Fix _json_value crashing on array-valued yfinance info fields

pd.isna() on a numpy array returns an array, not a scalar, causing
ValueError in the boolean context. Wrapping in try/except restores
get_company_info() for tickers like NFLX whose .info includes array
fields. Also suppress FutureWarning in compute_beta pct_change calls.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

1 files changed, 12 insertions, 5 deletions

diff --git a/backend/app/services/data_service.py b/backend/app/services/data_service.py
index 31bdb05..95650ad 100644
--- a/backend/app/services/data_service.py
+++ b/backend/app/services/data_service.py
@@ -58,7 +58,10 @@ def _json_value(value: Any) -> Any:
         return None
     if isinstance(value, pd.Timestamp):
         return value.isoformat()
-    if pd.isna(value):
+    try:
+        if pd.isna(value):
+            return None
+    except (TypeError, ValueError):
         return None
     if hasattr(value, "item"):
         return _json_value(value.item())
@@ -653,10 +656,14 @@ def compute_beta(symbol: str) -> float | None:
     try:
         ticker_closes = {row["date"]: row["close"] for row in ticker_history if row.get("close") is not None}
         spy_closes = {row["date"]: row["close"] for row in spy_history if row.get("close") is not None}
-        ticker_series = pd.Series(ticker_closes).sort_index()
-        spy_series = pd.Series(spy_closes).sort_index()
-        ticker_weekly = ticker_series.resample("W").last().pct_change().dropna()
-        spy_weekly = spy_series.resample("W").last().pct_change().dropna()
+        ticker_series = pd.Series(ticker_closes, dtype=float)
+        ticker_series.index = pd.to_datetime(ticker_series.index)
+        ticker_series = ticker_series.sort_index()
+        spy_series = pd.Series(spy_closes, dtype=float)
+        spy_series.index = pd.to_datetime(spy_series.index)
+        spy_series = spy_series.sort_index()
+        ticker_weekly = ticker_series.resample("W").last().pct_change(fill_method=None).dropna()
+        spy_weekly = spy_series.resample("W").last().pct_change(fill_method=None).dropna()
         aligned = pd.concat([ticker_weekly, spy_weekly], axis=1, join="inner").dropna()
         aligned.columns = ["ticker", "spy"]
         if len(aligned) < 52: