Add daily price movement to charts and fix intraday data rendering
- Add daily price movement display with color coding (green/red) - Add 1D (intraday) and 7D chart options with granular data: - 1D: 5-minute interval for detailed intraday view - 7D: hourly interval for smooth 7-day chart - Fix discontinuous chart rendering by plotting against sequential index for intraday data - Eliminate overnight/weekend gaps in hourly charts - Add timezone normalization for consistent date handling between daily and intraday data - Improve fallback logic when data is sparse - Better handling of yfinance column names (Datetime vs Date) Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
This commit is contained in:
Youssef Aitousarrah
parent
f4dba2940c
commit
74e8703d60
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@ -15,6 +15,7 @@ from tradingagents.ui.theme import COLORS, get_plotly_template, page_header, sig
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from tradingagents.ui.utils import load_recommendations
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TIMEFRAME_LOOKBACK_DAYS = {
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"1D": 1,
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"7D": 7,
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"1M": 30,
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"3M": 90,
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@ -23,8 +24,18 @@ TIMEFRAME_LOOKBACK_DAYS = {
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}
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def _get_interval_for_timeframe(timeframe: str) -> str:
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"""Return appropriate data interval for a given timeframe."""
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if timeframe == "1D":
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return "5m" # 5-minute for intraday detail
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elif timeframe == "7D":
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return "1h" # Hourly for smooth 7-day view
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else:
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return "1d" # Daily for longer timeframes
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@st.cache_data(ttl=3600)
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def _load_price_history(ticker: str, period: str) -> pd.DataFrame:
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def _load_price_history(ticker: str, period: str, interval: str = "1d") -> pd.DataFrame:
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try:
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from tradingagents.dataflows.y_finance import download_history
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except Exception:
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@ -33,7 +44,7 @@ def _load_price_history(ticker: str, period: str) -> pd.DataFrame:
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data = download_history(
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ticker,
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period=period,
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interval="1d",
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interval=interval,
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auto_adjust=True,
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progress=False,
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)
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@ -46,13 +57,17 @@ def _load_price_history(ticker: str, period: str) -> pd.DataFrame:
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data = data.xs(target, level=1, axis=1).copy()
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data = data.reset_index()
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date_col = "Date" if "Date" in data.columns else data.columns[0]
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# yfinance uses "Datetime" for intraday and "Date" for daily data
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date_col = next(
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(c for c in ("Datetime", "Date") if c in data.columns),
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data.columns[0],
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)
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close_col = "Close" if "Close" in data.columns else "Adj Close"
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if close_col not in data.columns:
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return pd.DataFrame()
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history = data[[date_col, close_col]].rename(columns={date_col: "date", close_col: "close"})
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history["date"] = pd.to_datetime(history["date"])
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history["date"] = pd.to_datetime(history["date"], utc=True).dt.tz_localize(None)
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history = history.dropna(subset=["close"]).sort_values("date")
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return history
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@ -114,6 +129,11 @@ def _get_daily_movement(ticker: str) -> str:
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return "N/A"
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def _is_intraday(timeframe: str) -> bool:
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"""Return True for timeframes that use intraday (sub-daily) data."""
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return timeframe in ("1D", "7D")
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def _build_dynamic_chart(
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history: pd.DataFrame, timeframe: str, ticker: str = ""
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) -> tuple[go.Figure, str, str, str]:
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@ -127,33 +147,74 @@ def _build_dynamic_chart(
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move_text = _format_move_pct(window)
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daily_move_text = _get_daily_movement(ticker) if ticker else "N/A"
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intraday = _is_intraday(timeframe)
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template = dict(get_plotly_template())
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fig = go.Figure()
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fig.add_trace(
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go.Scatter(
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x=history["date"],
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y=history["close"],
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mode="lines",
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line=dict(color="rgba(148,163,184,0.22)", width=1.1),
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hovertemplate="%{x|%b %d, %Y}<br>$%{y:.2f}<extra></extra>",
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name="History",
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if intraday:
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# For intraday charts, plot against a sequential index to eliminate
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# overnight and weekend gaps. Use customdata for hover timestamps.
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window = window.reset_index(drop=True)
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x_vals = list(range(len(window)))
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# Build tick labels: show date at the start of each trading day
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tick_vals = []
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tick_labels = []
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prev_day = None
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for i, row in window.iterrows():
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day = row["date"].date()
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if day != prev_day:
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tick_vals.append(i)
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tick_labels.append(row["date"].strftime("%b %d"))
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prev_day = day
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fig.add_trace(
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go.Scatter(
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x=x_vals,
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y=window["close"],
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mode="lines",
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line=dict(color=line_color, width=2.4),
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fill="tozeroy",
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fillcolor=(
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"rgba(34,197,94,0.18)"
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if line_color == COLORS["green"]
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else "rgba(239,68,68,0.18)"
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),
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customdata=window["date"],
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hovertemplate="%{customdata|%b %d %H:%M}<br>$%{y:.2f}<extra></extra>",
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name=f"{timeframe} Focus",
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)
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)
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)
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fig.add_trace(
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go.Scatter(
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x=window["date"],
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y=window["close"],
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mode="lines",
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line=dict(color=line_color, width=2.8),
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fill="tozeroy",
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fillcolor=(
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"rgba(34,197,94,0.18)" if line_color == COLORS["green"] else "rgba(239,68,68,0.18)"
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),
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hovertemplate=f"{timeframe}<br>%{{x|%b %d, %Y}}<br>$%{{y:.2f}}<extra></extra>",
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name=f"{timeframe} Focus",
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else:
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# For daily charts, keep the original two-trace approach
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fig.add_trace(
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go.Scatter(
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x=history["date"],
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y=history["close"],
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mode="lines",
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line=dict(color="rgba(148,163,184,0.22)", width=1.1),
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hovertemplate="%{x|%b %d, %Y}<br>$%{y:.2f}<extra></extra>",
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name="History",
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)
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)
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fig.add_trace(
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go.Scatter(
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x=window["date"],
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y=window["close"],
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mode="lines",
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line=dict(color=line_color, width=2.8),
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fill="tozeroy",
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fillcolor=(
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"rgba(34,197,94,0.18)"
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if line_color == COLORS["green"]
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else "rgba(239,68,68,0.18)"
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),
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hovertemplate=f"{timeframe}<br>%{{x|%b %d, %Y}}<br>$%{{y:.2f}}<extra></extra>",
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name=f"{timeframe} Focus",
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)
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)
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)
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# Override template keys before expansion to avoid duplicate keyword args.
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template["height"] = 210
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@ -169,12 +230,23 @@ def _build_dynamic_chart(
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else:
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pad = max((y_max - y_min) * 0.08, y_max * 0.01)
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fig.update_xaxes(
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showticklabels=False,
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showgrid=False,
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range=[window["date"].min(), history["date"].max()],
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rangeslider=dict(visible=False),
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)
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if intraday:
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fig.update_xaxes(
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showticklabels=True,
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showgrid=False,
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tickvals=tick_vals,
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ticktext=tick_labels,
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tickfont=dict(size=9, color=COLORS["text_muted"]),
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rangeslider=dict(visible=False),
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)
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else:
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fig.update_xaxes(
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showticklabels=False,
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showgrid=False,
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range=[window["date"].min(), history["date"].max()],
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rangeslider=dict(visible=False),
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)
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fig.update_yaxes(
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showgrid=True,
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gridcolor="rgba(42,53,72,0.28)",
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@ -186,18 +258,45 @@ def _build_dynamic_chart(
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def _render_single_dynamic_chart(ticker: str, timeframe: str) -> None:
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base_history = _load_price_history(ticker, "1y")
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# Load base history with daily data for context (full year)
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base_history = _load_price_history(ticker, "1y", interval="1d")
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if base_history.empty:
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st.caption("No price history available for this ticker.")
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return
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window = _slice_history_window(base_history, timeframe)
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if window.empty:
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st.caption(f"Not enough data to render {timeframe} window.")
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return
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# For 1D and 7D, load higher granularity (intraday) data
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intraday = _is_intraday(timeframe)
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if intraday:
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# Map timeframe to yfinance period: 1D -> "1d", 7D -> "7d"
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yf_period = {"1D": "1d", "7D": "7d"}[timeframe]
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interval = _get_interval_for_timeframe(timeframe)
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history_for_chart = _load_price_history(ticker, yf_period, interval=interval)
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if history_for_chart.empty or len(history_for_chart) < 2:
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# Fallback to daily data
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history_for_chart = base_history
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intraday = False
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if intraday:
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# Use all loaded intraday data directly — yfinance already
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# returned exactly the period we asked for.
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window = history_for_chart
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else:
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window = _slice_history_window(history_for_chart, timeframe)
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else:
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history_for_chart = base_history
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window = _slice_history_window(history_for_chart, timeframe)
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if window.empty or len(window) < 2:
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# Last-resort fallback: use all available data
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if len(history_for_chart) >= 2:
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window = history_for_chart.copy()
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else:
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st.caption(f"Not enough data to render {timeframe} window.")
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return
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fig, move_text, move_color, daily_move_text = _build_dynamic_chart(
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base_history, timeframe, ticker
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history_for_chart, timeframe, ticker
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)
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# Determine daily movement color
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@ -330,7 +429,7 @@ def render():
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chart_timeframe = st.radio(
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f"Timeframe for {ticker}",
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list(TIMEFRAME_LOOKBACK_DAYS.keys()),
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index=2,
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index=3,
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horizontal=True,
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label_visibility="collapsed",
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key=f"chart_tf_{ticker}_{idx}",
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