fn-registry agent
245 lines
8.2 KiB
Plaintext
245 lines
8.2 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "36ae91c9",
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"metadata": {},
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"source": [
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"# 02 — 3 KPI principales\n",
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"\n",
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"Por **centro real de facturación** (`tpv_terminals.center_id` del invoice) y ventana temporal:\n",
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"\n",
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"1. **A — Valor facturado de quotes call_center que CONVIRTIERON** \n",
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" Quote creado por usuario call_center + existe `tpv_orders_invoice` con el mismo `order_id`. Sumamos `tpv_orders_order.total_cost` o líneas. Centro = centro del invoice.\n",
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"\n",
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"2. **B — Valor facturado total a esos mismos clientes en centros** \n",
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" Misma identidad cliente (`customer_id` y/o `vehicle_id` y/o `tlf`+`matricula` normalizados). Todas las facturas del cliente en ese centro en la misma ventana. Debe ser ≥ A.\n",
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"\n",
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"3. **C — Facturación total del centro** \n",
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" Suma de invoices del centro en la ventana, todos los clientes."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7938921f",
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"metadata": {},
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"outputs": [],
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"source": [
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"from google.cloud import bigquery\n",
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"import pandas as pd\n",
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"\n",
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"PROJECT = \"autingo-159109\"\n",
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"DATASET = \"psql_dcpublic\"\n",
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"bq = bigquery.Client(project=PROJECT)\n",
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"\n",
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"WINDOW_DAYS = 90\n",
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"\n",
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"def q(sql):\n",
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" return bq.query(sql).to_dataframe()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "c7cfa785",
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"metadata": {},
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"source": [
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"## Setup: CTEs base reutilizables\n",
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"\n",
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"Construimos una query maestra con CTEs para A, B, C juntos por centro."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "3e06df33",
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"metadata": {},
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"outputs": [],
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"source": [
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"SQL_KPI = f\"\"\"\n",
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"DECLARE window_days INT64 DEFAULT {WINDOW_DAYS};\n",
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"DECLARE t_start TIMESTAMP DEFAULT TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL window_days DAY);\n",
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"\n",
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"WITH\n",
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"cc_users AS (\n",
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" SELECT DISTINCT tpvuser_id AS user_id\n",
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" FROM `{PROJECT}.{DATASET}.tpv_authorization_tpvuser_centers`\n",
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" WHERE dccenter_id IN (159, 162)\n",
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"),\n",
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"-- Quotes creados por call_center que TIENEN invoice (convertidos)\n",
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"cc_converted AS (\n",
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" SELECT\n",
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" q.id AS quote_id,\n",
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" q.order_id,\n",
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" q.created_at AS quote_ts,\n",
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" o.customer_id,\n",
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" o.vehicle_id,\n",
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" o.terminal_id,\n",
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" t.center_id,\n",
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" o.total_cost,\n",
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" i.id AS invoice_id,\n",
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" i.created_at AS invoice_ts\n",
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" FROM `{PROJECT}.{DATASET}.tpv_orders_quote` q\n",
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" JOIN cc_users cc ON q.created_by_id = cc.user_id\n",
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" JOIN `{PROJECT}.{DATASET}.tpv_orders_order` o ON q.order_id = o.id\n",
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" JOIN `{PROJECT}.{DATASET}.tpv_orders_invoice` i ON i.order_id = o.id\n",
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" LEFT JOIN `{PROJECT}.{DATASET}.tpv_terminals` t ON o.terminal_id = t.id\n",
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" WHERE q.created_at >= t_start\n",
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" AND q.deleted_at IS NULL\n",
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"),\n",
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"-- Clientes \"tocados\" por call_center (customer_id + vehicle_id)\n",
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"cc_clients AS (\n",
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" SELECT DISTINCT center_id, customer_id, vehicle_id\n",
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" FROM cc_converted\n",
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" WHERE customer_id IS NOT NULL\n",
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"),\n",
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"-- Todas las facturas en la ventana, con centro real\n",
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"all_invoices AS (\n",
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" SELECT\n",
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" i.id AS invoice_id,\n",
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" i.order_id,\n",
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" i.created_at AS invoice_ts,\n",
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" o.customer_id,\n",
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" o.vehicle_id,\n",
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" o.terminal_id,\n",
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" t.center_id,\n",
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" o.total_cost\n",
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" FROM `{PROJECT}.{DATASET}.tpv_orders_invoice` i\n",
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" JOIN `{PROJECT}.{DATASET}.tpv_orders_order` o ON i.order_id = o.id\n",
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" LEFT JOIN `{PROJECT}.{DATASET}.tpv_terminals` t ON o.terminal_id = t.id\n",
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" WHERE i.created_at >= t_start\n",
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"),\n",
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"-- B: facturas de los mismos clientes en cualquier centro NO call_center\n",
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"client_invoices_in_centers AS (\n",
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" SELECT ai.*\n",
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" FROM all_invoices ai\n",
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" JOIN cc_clients cc ON ai.customer_id = cc.customer_id\n",
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" WHERE ai.center_id NOT IN (159, 162) -- excluye los propios centros call_center\n",
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"),\n",
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"kpi_a AS (\n",
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" SELECT center_id,\n",
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" COUNT(DISTINCT quote_id) AS quotes_cc_convertidos,\n",
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" COUNT(DISTINCT invoice_id) AS invoices_a,\n",
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" SUM(total_cost) AS valor_a\n",
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" FROM cc_converted\n",
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" WHERE center_id IS NOT NULL\n",
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" GROUP BY center_id\n",
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"),\n",
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"kpi_b AS (\n",
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" SELECT center_id,\n",
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" COUNT(DISTINCT invoice_id) AS invoices_b,\n",
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" SUM(total_cost) AS valor_b\n",
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" FROM client_invoices_in_centers\n",
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" GROUP BY center_id\n",
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"),\n",
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"kpi_c AS (\n",
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" SELECT center_id,\n",
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" COUNT(DISTINCT invoice_id) AS invoices_c,\n",
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" SUM(total_cost) AS valor_c\n",
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" FROM all_invoices\n",
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" WHERE center_id IS NOT NULL\n",
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" GROUP BY center_id\n",
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")\n",
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"SELECT\n",
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" c.id AS center_id,\n",
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" c.name AS center_name,\n",
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" COALESCE(a.quotes_cc_convertidos, 0) AS quotes_cc_convertidos,\n",
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" ROUND(COALESCE(a.valor_a, 0), 2) AS A_valor_quote_cc_convertido,\n",
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" ROUND(COALESCE(b.valor_b, 0), 2) AS B_valor_mismo_cliente_centro,\n",
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" ROUND(COALESCE(c2.valor_c, 0), 2) AS C_valor_total_centro,\n",
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" ROUND(SAFE_DIVIDE(COALESCE(a.valor_a, 0), c2.valor_c), 4) AS A_sobre_C,\n",
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" ROUND(SAFE_DIVIDE(COALESCE(b.valor_b, 0), c2.valor_c), 4) AS B_sobre_C\n",
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"FROM `{PROJECT}.{DATASET}.centers` c\n",
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"LEFT JOIN kpi_a a ON c.id = a.center_id\n",
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"LEFT JOIN kpi_b b ON c.id = b.center_id\n",
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"LEFT JOIN kpi_c c2 ON c.id = c2.center_id\n",
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"WHERE c.id NOT IN (159, 162)\n",
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" AND COALESCE(c2.valor_c, 0) > 0\n",
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"ORDER BY C_valor_total_centro DESC\n",
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"\"\"\"\n",
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"\n",
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"df = q(SQL_KPI)\n",
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"print(f\"Centros con actividad ({WINDOW_DAYS}d): {len(df)}\")\n",
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"df.head(30)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "724baf5c",
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"metadata": {},
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"source": [
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"## Totales globales"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "75c3297e",
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"metadata": {},
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"outputs": [],
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"source": [
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"totals = df[[\"A_valor_quote_cc_convertido\", \"B_valor_mismo_cliente_centro\", \"C_valor_total_centro\"]].sum()\n",
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"print(totals.to_string())\n",
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"print()\n",
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"print(f\"A/C global: {totals.A_valor_quote_cc_convertido / totals.C_valor_total_centro:.4f}\")\n",
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"print(f\"B/C global: {totals.B_valor_mismo_cliente_centro / totals.C_valor_total_centro:.4f}\")\n",
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"print(f\"Lift B vs A: {totals.B_valor_mismo_cliente_centro / totals.A_valor_quote_cc_convertido:.2f}x\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0fba60db",
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"metadata": {},
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"source": [
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"## Top 15 centros por A (valor traído por call_center)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f90abe7e",
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"metadata": {},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt\n",
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"\n",
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"top = df.sort_values(\"A_valor_quote_cc_convertido\", ascending=False).head(15)\n",
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"fig, ax = plt.subplots(figsize=(10, 6))\n",
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"x = range(len(top))\n",
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"ax.barh(x, top.A_valor_quote_cc_convertido, label=\"A (cc → factura)\")\n",
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"ax.barh(x, top.B_valor_mismo_cliente_centro - top.A_valor_quote_cc_convertido,\n",
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" left=top.A_valor_quote_cc_convertido, label=\"B−A (mismo cliente extra)\")\n",
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"ax.set_yticks(x)\n",
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"ax.set_yticklabels(top.center_name)\n",
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"ax.invert_yaxis()\n",
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"ax.set_xlabel(\"€ facturados\")\n",
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"ax.legend()\n",
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"ax.set_title(f\"Top 15 centros — quotes call_center ({WINDOW_DAYS}d)\")\n",
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"plt.tight_layout()\n",
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"plt.show()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.13.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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