From bfd130578a2896d74fb80e451f8c118fdcdc678a Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jos=C3=A9=20Manuel=20G=C3=B3mez?= <jmgomez@roiandco.com>
Date: Thu, 2 Jul 2026 17:43:55 +0200
Subject: [PATCH] =?UTF-8?q?Improve=20SEM=20dashboard:=20split=20Hist=C3=B3?=
 =?UTF-8?q?rico=20tabs,=20shrink=20KPI=20metrics,=20add=20daily=20P&L=20ch?=
 =?UTF-8?q?art?=
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- Separate campaign-level daily metrics from the global portfolio view in
  the Histórico tab using nested sub-tabs instead of a single stacked section.
- Shrink st.metric font sizes globally so large KPI values render correctly.
- Add a daily evolution chart in Resumen showing Inversión, Ingreso,
  Margen (sumatorio) and Margen (PPL) aggregated across filtered campaigns.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
---
 dashboard.py | 90 +++++++++++++++++++++++++++++++++++++++++++++++++++-
 1 file changed, 89 insertions(+), 1 deletion(-)

diff --git a/dashboard.py b/dashboard.py
index 835b665..7b0fc52 100644
--- a/dashboard.py
+++ b/dashboard.py
@@ -1,6 +1,7 @@
 """Dashboard interactivo para leads-optimizer — Streamlit."""
 import streamlit as st
 import pandas as pd
+import altair as alt
 import json
 import subprocess
 import sys
@@ -20,6 +21,19 @@ st.set_page_config(
     initial_sidebar_state="expanded",
 )
 
+# Los KPI (st.metric) por defecto son demasiado grandes y se cortan en pantallas
+# más estrechas o cuando el valor es largo (p.ej. "1.234,56€"). Los reducimos.
+st.markdown(
+    """
+    <style>
+    [data-testid="stMetricValue"] { font-size: 1.5rem; }
+    [data-testid="stMetricLabel"] { font-size: 0.8rem; }
+    [data-testid="stMetricDelta"] { font-size: 0.8rem; }
+    </style>
+    """,
+    unsafe_allow_html=True,
+)
+
 # ── Helpers ───────────────────────────────────────────────────────────────────
 
 URGENCIA_ICON = {
@@ -183,6 +197,48 @@ def _compute_analysis(row: dict, dia_actual: int, dias_mes: int) -> dict:
     }
 
 
+def _daily_summary(rows: list[dict]) -> pd.DataFrame:
+    """Agrega Inversión/Ingreso/Margen día a día sumando las MetricasDiarias
+    de todas las campañas dadas, más un margen alternativo calculado con el
+    PPL fijo de cada campaña en lugar del ingreso reportado."""
+    daily = {}
+    for r in rows:
+        metricas = r.get("metricas")
+        if not metricas:
+            continue
+        items = metricas.items() if isinstance(metricas, dict) else [
+            (m.get("fecha"), m) for m in metricas
+        ]
+        for fecha, m in items:
+            if not fecha or not isinstance(m, dict):
+                continue
+            gasto = revenue = leads = None
+            for k, v in m.items():
+                kl = k.lower()
+                if gasto is None and ("coste" in kl or "cost" in kl):
+                    gasto = float(v or 0)
+                elif revenue is None and ("ingres" in kl or "revenue" in kl):
+                    revenue = float(v or 0)
+                elif leads is None and "lead" in kl:
+                    leads = float(v or 0)
+            entry = daily.setdefault(fecha, {"gasto": 0.0, "revenue": 0.0, "revenue_ppl": 0.0})
+            entry["gasto"] += gasto or 0.0
+            entry["revenue"] += revenue or 0.0
+            entry["revenue_ppl"] += (leads or 0.0) * r["ppl"]
+
+    if not daily:
+        return pd.DataFrame()
+
+    df = pd.DataFrame([{"Fecha": f, **v} for f, v in sorted(daily.items())])
+    return pd.DataFrame({
+        "Fecha": df["Fecha"],
+        "Inversión": df["gasto"],
+        "Ingreso": df["revenue"],
+        "Margen (sumatorio)": df["revenue"] - df["gasto"],
+        "Margen (PPL)": df["revenue_ppl"] - df["gasto"],
+    })
+
+
 # ── Sidebar ───────────────────────────────────────────────────────────────────
 
 st.sidebar.title("Leads Optimizer")
@@ -277,6 +333,35 @@ with tab_resumen:
 
     st.divider()
 
+    # ── Evolución diaria del mes (inversión / ingreso / margen) ──────────────────
+    st.subheader("Evolución diaria del mes")
+
+    df_summary = _daily_summary(filtered)
+    if df_summary.empty:
+        st.info("Sin métricas diarias disponibles para las campañas filtradas.")
+    else:
+        df_long = df_summary.melt("Fecha", var_name="Serie", value_name="Valor")
+        serie_order = ["Inversión", "Ingreso", "Margen (sumatorio)", "Margen (PPL)"]
+        color_scale = alt.Scale(
+            domain=serie_order,
+            range=["#2a78d6", "#1baf7a", "#4a3aa7", "#eb6834"],
+        )
+        chart = (
+            alt.Chart(df_long)
+            .mark_line(point=True, strokeWidth=2)
+            .encode(
+                x=alt.X("Fecha:O", title=None),
+                y=alt.Y("Valor:Q", title="€"),
+                color=alt.Color("Serie:N", scale=color_scale, sort=serie_order, legend=alt.Legend(title=None)),
+                tooltip=["Fecha", "Serie", alt.Tooltip("Valor:Q", format=",.2f")],
+            )
+            .properties(height=320)
+        )
+        st.altair_chart(chart, use_container_width=True)
+        st.caption("Margen (sumatorio) = Ingreso reportado − Gasto · Margen (PPL) = Leads del día × PPL de campaña − Gasto")
+
+    st.divider()
+
     # ── Alertas activas ───────────────────────────────────────────────────────
     alerts = []
     for r in filtered:
@@ -454,6 +539,9 @@ with tab_campanas:
 # ════════════════════════════════════════════════════════════════════════════ #
 
 with tab_historico:
+    hist_camp_tab, hist_portfolio_tab = st.tabs(["📋 Campañas", "🌐 Portfolio global"])
+
+with hist_camp_tab:
     st.subheader("Métricas diarias por campaña")
 
     camp_names = [r["nombre"] for r in filtered if r["metricas"]]
@@ -540,7 +628,7 @@ with tab_historico:
         else:
             st.info("Sin métricas diarias para esta campaña.")
 
-    st.divider()
+with hist_portfolio_tab:
     st.subheader("Portfolio agregado (GAMes)")
 
     @st.cache_data(ttl=300, show_spinner="Cargando portfolio...")