226 lines
8.2 KiB
Python
226 lines
8.2 KiB
Python
"""Page 2: Executive Compensation."""
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import dash
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import duckdb
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from dash import html, dcc, Input, Output, dash_table
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import plotly.express as px
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import plotly.graph_objects as go
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from admin_analytics.dashboard.queries import (
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query_top_earners,
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query_comp_by_role,
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query_comp_vs_cpi,
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query_comp_cagr,
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query_aggregate_comp,
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query_aggregate_comp_cagr,
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)
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_NO_DATA = html.Div(
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"No IRS 990 data loaded. Run: admin-analytics ingest irs990",
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style={"textAlign": "center", "padding": "40px", "color": "#888"},
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)
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# Roles to highlight in trend chart
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_KEY_ROLES = ["PRESIDENT", "PROVOST", "VP_FINANCE", "VP_RESEARCH", "VP_ADVANCEMENT", "CFO"]
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def _kpi_card(title: str, value: str, subtitle: str = "") -> html.Div:
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return html.Div(
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[
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html.H4(title, style={"margin": "0", "color": "#666", "fontSize": "14px"}),
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html.H2(value, style={"margin": "5px 0", "color": "#00539F"}),
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html.P(subtitle, style={"margin": "0", "color": "#999", "fontSize": "12px"}),
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],
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style={
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"flex": "1",
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"padding": "20px",
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"backgroundColor": "#f8f9fa",
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"borderRadius": "8px",
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"textAlign": "center",
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"margin": "0 8px",
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},
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)
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def layout(conn: duckdb.DuckDBPyConnection):
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all_earners = query_top_earners(conn)
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if all_earners.height == 0:
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return _NO_DATA
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years = sorted(all_earners["tax_year"].unique().to_list())
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year_options = [{"label": "All Years", "value": "all"}] + [
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{"label": str(y), "value": y} for y in years
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]
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# KPI cards
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cagr = query_comp_cagr(conn)
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agg_cagr = query_aggregate_comp_cagr(conn)
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kpi_cards = []
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if cagr:
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kpi_cards.append(_kpi_card(
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"President Compensation",
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f"${cagr['end_comp']:,}",
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f"Tax year {cagr['end_year']}",
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))
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kpi_cards.append(_kpi_card(
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"President CAGR",
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f"{cagr['cagr_pct']}%",
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f"Annualized growth, {cagr['start_year']}-{cagr['end_year']}",
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))
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if agg_cagr:
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kpi_cards.append(_kpi_card(
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"Top-10 Total Compensation",
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f"${agg_cagr['end_comp']:,}",
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f"Tax year {agg_cagr['end_year']}",
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))
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kpi_cards.append(_kpi_card(
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"Top-10 CAGR",
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f"{agg_cagr['cagr_pct']}%",
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f"Annualized growth, {agg_cagr['start_year']}-{agg_cagr['end_year']}",
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))
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kpi_row = html.Div(kpi_cards, style={"display": "flex", "marginBottom": "24px"}) if kpi_cards else html.Div()
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# Compensation by role trend
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role_df = query_comp_by_role(conn)
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role_fig = go.Figure()
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if role_df.height > 0:
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role_pd = role_df.to_pandas()
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for role in _KEY_ROLES:
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subset = role_pd[role_pd["canonical_role"] == role]
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if len(subset) > 0:
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role_fig.add_trace(go.Scatter(
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x=subset["tax_year"],
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y=subset["total_compensation"],
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mode="lines+markers",
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name=role.replace("_", " ").title(),
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))
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role_fig.update_layout(
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title="Compensation Trends by Role",
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xaxis_title="Tax Year", yaxis_title="Total Compensation ($)",
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template="plotly_white", height=420,
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)
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# Comp vs CPI indexed
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cpi_df = query_comp_vs_cpi(conn)
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cpi_fig = go.Figure()
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if cpi_df.height > 0:
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cpi_pd = cpi_df.to_pandas()
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cpi_fig.add_trace(go.Scatter(
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x=cpi_pd["year"], y=cpi_pd["comp_index"],
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mode="lines+markers", name="Top Compensation",
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line={"color": "#00539F"},
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))
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cpi_fig.add_trace(go.Scatter(
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x=cpi_pd["year"], y=cpi_pd["agg_index"],
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mode="lines+markers", name="Top-10 Aggregate",
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line={"color": "#E07A5F"},
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))
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cpi_fig.add_trace(go.Scatter(
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x=cpi_pd["year"], y=cpi_pd["cpi_index"],
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mode="lines+markers", name="CPI-U",
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line={"color": "#FFD200", "dash": "dash"},
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))
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cpi_fig.update_layout(
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title="Compensation vs CPI-U (Indexed, Base Year = 100)",
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xaxis_title="Year", yaxis_title="Index",
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template="plotly_white", height=380,
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)
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return html.Div([
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kpi_row,
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html.Div(
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[
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html.Label("Filter by Tax Year: ", style={"fontWeight": "bold"}),
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dcc.Dropdown(
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id="comp-year-dropdown",
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options=year_options,
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value="all",
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style={"width": "200px", "display": "inline-block"},
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),
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],
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style={"marginBottom": "16px"},
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),
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dash_table.DataTable(
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id="comp-table",
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columns=[
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{"name": "Year", "id": "tax_year"},
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{"name": "Name", "id": "person_name"},
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{"name": "Title", "id": "title"},
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{"name": "Role", "id": "canonical_role"},
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{"name": "Base", "id": "base_compensation", "type": "numeric",
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"format": dash_table.Format.Format().group(True)},
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{"name": "Bonus", "id": "bonus_compensation", "type": "numeric",
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"format": dash_table.Format.Format().group(True)},
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{"name": "Total", "id": "total_compensation", "type": "numeric",
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"format": dash_table.Format.Format().group(True)},
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],
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data=all_earners.to_pandas().to_dict("records"),
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page_size=15,
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sort_action="native",
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filter_action="native",
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style_table={"overflowX": "auto"},
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style_cell={"textAlign": "left", "padding": "8px", "fontSize": "13px"},
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style_header={"fontWeight": "bold", "backgroundColor": "#f0f0f0"},
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),
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html.Div(
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[
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html.Div(dcc.Graph(id="comp-breakdown-chart"), style={"flex": "1"}),
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html.Div(dcc.Graph(figure=cpi_fig), style={"flex": "1"}),
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],
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style={"display": "flex", "gap": "16px", "marginTop": "16px"},
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),
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dcc.Graph(figure=role_fig),
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])
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def register_callbacks(app: dash.Dash, conn: duckdb.DuckDBPyConnection) -> None:
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"""Register interactive callbacks for the compensation page."""
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@app.callback(
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[Output("comp-table", "data"), Output("comp-breakdown-chart", "figure")],
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Input("comp-year-dropdown", "value"),
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)
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def update_compensation(year_value):
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year = None if year_value == "all" else int(year_value)
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earners = query_top_earners(conn, year=year)
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# Table data
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table_data = earners.to_pandas().to_dict("records") if earners.height > 0 else []
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# Breakdown chart — stacked bar of comp components
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breakdown_fig = go.Figure()
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if earners.height > 0:
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ep = earners.to_pandas().head(10) # top 10 by total comp
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_SUFFIXES = {"JR", "SR", "II", "III", "IV", "JR.", "SR."}
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def _short_name(n):
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if "," in n:
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return n.split(",")[0][:20]
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parts = n.split()
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while len(parts) > 1 and parts[-1].upper().rstrip(".") in _SUFFIXES:
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parts.pop()
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return parts[-1][:20] if parts else n[:20]
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short_names = [_short_name(n) for n in ep["person_name"]]
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for comp_type, label, color in [
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("base_compensation", "Base", "#00539F"),
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("bonus_compensation", "Bonus", "#FFD200"),
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("deferred_compensation", "Deferred", "#7FB069"),
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("nontaxable_benefits", "Benefits", "#E07A5F"),
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("other_compensation", "Other", "#999"),
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]:
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if comp_type in ep.columns:
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breakdown_fig.add_trace(go.Bar(
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x=short_names, y=ep[comp_type],
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name=label, marker_color=color,
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))
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breakdown_fig.update_layout(barmode="stack")
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title_suffix = f" ({year})" if year else " (All Years)"
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breakdown_fig.update_layout(
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title=f"Compensation Breakdown — Top 10{title_suffix}",
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xaxis_title="", yaxis_title="$",
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template="plotly_white", height=380,
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)
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return table_data, breakdown_fig
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