fn-registry agent
3285 lines
178 KiB
Plaintext
3285 lines
178 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "1cc9e4a4",
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"metadata": {},
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"source": [
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"# Análisis Venta Web — Aurgi\n",
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"\n",
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"Partiendo de los hallazgos del notebook 01, reproducimos y comparamos las 3 fuentes de venta web en 2025:\n",
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"\n",
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"| Fuente | Tabla(s) | Filtro | Revenue 2025 según doc 8 |\n",
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"|---|---|---|---|\n",
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"| **Cubo_Ventas_Calculado** | `anjana_bi_datamart.Cubo_Ventas_Calculado` | `Dim_NombreDimGlobal2 = 'WSWEB'` | 5.879.313 € |\n",
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"| **NAV directo** | `anjana_sales_invoice_header` + `..._line` | `location_code IN ('18','19','405','421','422')` | 15.878.883 € |\n",
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"| **Supply Orders → NAV** | `supply_orders` → `logistic_orders` → NAV | `service_request_id IS NOT NULL` | 7.235.399 € |\n",
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"\n",
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"Todas en **DCBigQuery (db=6)**.\n",
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"\n",
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"## Objetivos\n",
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"\n",
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"1. Reproducir los tres totales y confirmar las cifras del doc 8.\n",
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"2. Desagregar cada fuente por mes, centro, canal y categoría.\n",
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"3. Cuantificar la diferencia entre **Cubo** y **NAV directo** (la brecha de ~10M€).\n",
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"4. Mapear qué parte del dashboard 734 se alimenta de cada fuente."
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]
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},
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{
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"cell_type": "markdown",
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"id": "eff1289d",
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"metadata": {},
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"source": [
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"## 1. Setup"
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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": 1,
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"id": "dac747f8",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Listo. BigQuery via Metabase.\n"
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]
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}
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],
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"source": [
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"import os, re\n",
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"from pathlib import Path\n",
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"import pandas as pd\n",
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"\n",
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"env_path = Path('.env') if Path('.env').exists() else Path('../.env')\n",
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"for line in env_path.read_text().splitlines():\n",
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" if line and not line.startswith('#') and '=' in line:\n",
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" k, v = line.split('=', 1)\n",
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" os.environ.setdefault(k.strip(), v.strip())\n",
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"\n",
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"from metabase import MetabaseClient, metabase_execute_query\n",
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"\n",
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"URL = os.environ['METABASE_URL']\n",
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"KEY = os.environ['METABASE_API_KEY']\n",
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"client = MetabaseClient(URL, KEY)\n",
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"DB_BIGQUERY = 6\n",
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"\n",
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"def run_sql(sql: str, db_id: int = DB_BIGQUERY) -> pd.DataFrame:\n",
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" \"\"\"Ejecuta SQL contra Metabase y retorna DataFrame.\"\"\"\n",
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" res = metabase_execute_query(client, db_id, sql)\n",
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" cols = [c['display_name'] or c['name'] for c in res['data']['cols']]\n",
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" return pd.DataFrame(res['data']['rows'], columns=cols)\n",
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"\n",
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"pd.set_option('display.max_colwidth', 100)\n",
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"pd.set_option('display.float_format', lambda x: f'{x:,.2f}')\n",
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"print('Listo. BigQuery via Metabase.')"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9682af7a",
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"metadata": {},
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"source": [
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"## 2. Descubrir el project/dataset de BigQuery\n",
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"\n",
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"Necesitamos el prefijo correcto para cualificar las tablas en SQL nativo contra BigQuery."
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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": 2,
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"id": "740e351e",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Total tablas en DCBigQuery: 2830\n",
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"--- schemas distintos ---\n",
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"schema\n",
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"analytics_353235710 1314\n",
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"anjana_bi_amg 387\n",
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"anjana_bi_datamart 213\n",
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"google_ads_data 202\n",
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"psql_dcpublic 142\n",
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"anjana_bi_ntg 102\n",
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"questions_metabase 67\n",
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"arbentia_dev_dataset 64\n",
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"anjana_bi_mmb 61\n",
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"stg_anjana_bi 58\n",
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"mssql2022_dbo 56\n",
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"bi_anjana 52\n",
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"citaprevia_aurphcp 25\n",
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"almacen_movs 16\n",
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"data_models 14\n",
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"ralarsa 10\n",
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"rag_datasets 9\n",
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"test_sales 8\n",
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"claude_bi 5\n",
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"call_analytics 5\n",
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"Name: count, dtype: int64\n",
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"--- tablas clave referenciadas en doc 8 ---\n"
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]
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},
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{
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"data": {
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"text/html": [
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||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
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||
" }\n",
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||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
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||
" }\n",
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"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
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||
" }\n",
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||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
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||
" <th>id</th>\n",
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" <th>schema</th>\n",
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" <th>name</th>\n",
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" </tr>\n",
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||
" </thead>\n",
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||
" <tbody>\n",
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||
" <tr>\n",
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||
" <th>154</th>\n",
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" <td>3452</td>\n",
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" <td>mssql2022_dbo</td>\n",
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" <td>anjana_sales_invoice_header</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>155</th>\n",
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" <td>3437</td>\n",
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" <td>mssql2022_dbo</td>\n",
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" <td>anjana_sales_invoice_line</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>424</th>\n",
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" <td>2890</td>\n",
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" <td>anjana_bi_datamart</td>\n",
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" <td>Cubo_Ventas_Calculado</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1351</th>\n",
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" <td>1534</td>\n",
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" <td>psql_dcpublic</td>\n",
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" <td>logistic_orders</td>\n",
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" </tr>\n",
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" <tr>\n",
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||
" <th>2531</th>\n",
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" <td>1530</td>\n",
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" <td>psql_dcpublic</td>\n",
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" <td>supply_orders</td>\n",
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||
" </tr>\n",
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||
" </tbody>\n",
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||
"</table>\n",
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||
"</div>"
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||
],
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"text/plain": [
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||
" id schema name\n",
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"154 3452 mssql2022_dbo anjana_sales_invoice_header\n",
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"155 3437 mssql2022_dbo anjana_sales_invoice_line\n",
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"424 2890 anjana_bi_datamart Cubo_Ventas_Calculado\n",
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||
"1351 1534 psql_dcpublic logistic_orders\n",
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"2531 1530 psql_dcpublic supply_orders"
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||
]
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||
},
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||
"execution_count": 2,
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||
"metadata": {},
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||
"output_type": "execute_result"
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||
}
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||
],
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"source": [
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"# Listar tablas de db=6 para confirmar naming\n",
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"db6 = client.request('GET', '/api/database/6?include=tables')\n",
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"tables = pd.DataFrame([\n",
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" {'id': t['id'], 'schema': t.get('schema'), 'name': t['name']}\n",
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" for t in db6.get('tables') or []\n",
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"])\n",
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"print(f\"Total tablas en DCBigQuery: {len(tables)}\")\n",
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"print('--- schemas distintos ---')\n",
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"print(tables['schema'].value_counts().head(20))\n",
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"print('--- tablas clave referenciadas en doc 8 ---')\n",
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"key_names = ['Cubo_Ventas_Calculado', 'anjana_sales_invoice_header', 'anjana_sales_invoice_line', 'supply_orders', 'logistic_orders']\n",
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"tables[tables['name'].isin(key_names)]"
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]
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||
},
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||
{
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||
"cell_type": "markdown",
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||
"id": "f0a1ba81",
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||
"metadata": {},
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"source": [
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"## 3. Fuente 1 — Cubo_Ventas_Calculado (WSWEB)"
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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": "e595c0d4",
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||
"metadata": {},
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||
"outputs": [],
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||
"source": [
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||
"# Ajustar el nombre completo según lo descubierto en la celda anterior.\n",
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"# En BigQuery Metabase suele cualificar como `project.dataset.tabla` automaticamente;\n",
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"# si no lo hace, usar el schema como dataset.\n",
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"CUBO = 'anjana_bi_datamart.Cubo_Ventas_Calculado'\n",
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"\n",
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"sql_cubo_total = f'''\n",
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"SELECT\n",
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" COUNT(*) AS lineas,\n",
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" SUM(Importe_Neto) AS revenue_total\n",
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"FROM {CUBO}\n",
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"WHERE Dim_NombreDimGlobal2 = 'WSWEB'\n",
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" AND EXTRACT(YEAR FROM Fecha_Registro) = 2025\n",
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"'''\n",
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"run_sql(sql_cubo_total)"
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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": "3d389e98",
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||
"metadata": {},
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||
"outputs": [],
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"source": [
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"# Evolucion mensual Cubo WSWEB 2025\n",
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"sql_cubo_mes = f'''\n",
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"SELECT\n",
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" FORMAT_DATE('%Y-%m', Fecha_Registro) AS mes,\n",
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" COUNT(*) AS lineas,\n",
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||
" SUM(Importe_Neto) AS revenue\n",
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||
"FROM {CUBO}\n",
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"WHERE Dim_NombreDimGlobal2 = 'WSWEB'\n",
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||
" AND EXTRACT(YEAR FROM Fecha_Registro) = 2025\n",
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"GROUP BY mes\n",
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||
"ORDER BY mes\n",
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"'''\n",
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||
"df_cubo_mes = run_sql(sql_cubo_mes)\n",
|
||
"df_cubo_mes"
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||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
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||
"id": "ac71ce22",
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||
"metadata": {},
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||
"source": [
|
||
"## 4. Fuente 2 — NAV directo (centros web)"
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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": "4dbf152e",
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||
"metadata": {},
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||
"outputs": [],
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||
"source": [
|
||
"NAV_HEADER = 'anjana_bi_datamart.anjana_sales_invoice_header'\n",
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"NAV_LINE = 'anjana_bi_datamart.anjana_sales_invoice_line'\n",
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"WEB_CENTERS = \"('18','19','405','421','422')\"\n",
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"\n",
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"sql_nav_total = f'''\n",
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"SELECT\n",
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" COUNT(*) AS lineas,\n",
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" SUM(l.amount) AS revenue_total\n",
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"FROM {NAV_LINE} l\n",
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"JOIN {NAV_HEADER} h\n",
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" ON l.document_no = h.no\n",
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"WHERE h.location_code IN {WEB_CENTERS}\n",
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" AND EXTRACT(YEAR FROM h.posting_date) = 2025\n",
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"'''\n",
|
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"run_sql(sql_nav_total)"
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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": "db4e883e",
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||
"metadata": {},
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||
"outputs": [],
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"source": [
|
||
"# NAV por centro y mes\n",
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"sql_nav_mes = f'''\n",
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"SELECT\n",
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" FORMAT_DATE('%Y-%m', h.posting_date) AS mes,\n",
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" h.location_code,\n",
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" COUNT(*) AS lineas,\n",
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" SUM(l.amount) AS revenue\n",
|
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"FROM {NAV_LINE} l\n",
|
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"JOIN {NAV_HEADER} h\n",
|
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" ON l.document_no = h.no\n",
|
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"WHERE h.location_code IN {WEB_CENTERS}\n",
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" AND EXTRACT(YEAR FROM h.posting_date) = 2025\n",
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"GROUP BY mes, h.location_code\n",
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"ORDER BY mes, h.location_code\n",
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"'''\n",
|
||
"df_nav_mes = run_sql(sql_nav_mes)\n",
|
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"df_nav_mes.head(20)"
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||
]
|
||
},
|
||
{
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||
"cell_type": "markdown",
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||
"id": "9aa66747",
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||
"metadata": {},
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"source": [
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"## 5. Fuente 3 — Supply Orders → NAV (web)"
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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": "9f78689a",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"SO = 'anjana_bi_datamart.supply_orders'\n",
|
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"LO = 'anjana_bi_datamart.logistic_orders'\n",
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"\n",
|
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"sql_so_total = f'''\n",
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"SELECT\n",
|
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" COUNT(*) AS supply_orders_web,\n",
|
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" SUM(sale_price) AS revenue\n",
|
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"FROM {SO}\n",
|
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"WHERE service_request_id IS NOT NULL\n",
|
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" AND EXTRACT(YEAR FROM created_at) = 2025\n",
|
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"'''\n",
|
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"run_sql(sql_so_total)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
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||
"id": "830d4c2e",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 6. Comparativa y brecha\n",
|
||
"\n",
|
||
"Consolidamos los tres totales y analizamos la diferencia."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 3,
|
||
"id": "49ad9aad",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"ename": "NameError",
|
||
"evalue": "name 'df_cubo_mes' is not defined",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
|
||
"\u001b[31mNameError\u001b[39m Traceback (most recent call last)",
|
||
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[3]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m 1\u001b[39m \u001b[38;5;66;03m# Juntar los tres mensuales\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m tot_cubo = df_cubo_mes.groupby(\u001b[33m'mes'\u001b[39m)[\u001b[33m'revenue'\u001b[39m].sum().rename(\u001b[33m'cubo'\u001b[39m)\n\u001b[32m 3\u001b[39m tot_nav = df_nav_mes.groupby(\u001b[33m'mes'\u001b[39m)[\u001b[33m'revenue'\u001b[39m].sum().rename(\u001b[33m'nav_directo'\u001b[39m)\n\u001b[32m 4\u001b[39m comparativa = pd.concat([tot_cubo, tot_nav], axis=\u001b[32m1\u001b[39m).reset_index()\n\u001b[32m 5\u001b[39m comparativa[\u001b[33m'brecha_nav_vs_cubo'\u001b[39m] = comparativa[\u001b[33m'nav_directo'\u001b[39m] - comparativa[\u001b[33m'cubo'\u001b[39m]\n",
|
||
"\u001b[31mNameError\u001b[39m: name 'df_cubo_mes' is not defined"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Juntar los tres mensuales\n",
|
||
"tot_cubo = df_cubo_mes.groupby('mes')['revenue'].sum().rename('cubo')\n",
|
||
"tot_nav = df_nav_mes.groupby('mes')['revenue'].sum().rename('nav_directo')\n",
|
||
"comparativa = pd.concat([tot_cubo, tot_nav], axis=1).reset_index()\n",
|
||
"comparativa['brecha_nav_vs_cubo'] = comparativa['nav_directo'] - comparativa['cubo']\n",
|
||
"comparativa['ratio_cubo_sobre_nav_pct'] = 100 * comparativa['cubo'] / comparativa['nav_directo']\n",
|
||
"comparativa"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "d89d792d",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 7. Qué filtra el Cubo respecto a NAV\n",
|
||
"\n",
|
||
"El Cubo aplica filtros de negocio extra: solo movimientos tipo 'Venta', excluye devoluciones, ajustes, ciertos tipos de ticket.\n",
|
||
"Exploramos el header NAV para ver qué categorías se pierden."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "6c026d51",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Distribución por document_type en NAV centros web 2025\n",
|
||
"sql_doctype = f'''\n",
|
||
"SELECT\n",
|
||
" h.document_type,\n",
|
||
" COUNT(*) AS lineas,\n",
|
||
" SUM(l.amount) AS revenue\n",
|
||
"FROM {NAV_LINE} l\n",
|
||
"JOIN {NAV_HEADER} h\n",
|
||
" ON l.document_no = h.no\n",
|
||
"WHERE h.location_code IN {WEB_CENTERS}\n",
|
||
" AND EXTRACT(YEAR FROM h.posting_date) = 2025\n",
|
||
"GROUP BY h.document_type\n",
|
||
"ORDER BY revenue DESC\n",
|
||
"'''\n",
|
||
"run_sql(sql_doctype)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "273719d1",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 8. Cruce dashboard 734 ← fuente\n",
|
||
"\n",
|
||
"Usando `df_dash_sources` del notebook 01 (celda 26), identificamos qué tabs del dashboard se alimentan del Cubo, de NAV directo o de supply_orders."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "e5613255",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Si df_dash_sources vive en el mismo kernel (tras correr 01), lo reutilizamos.\n",
|
||
"# Si no, lo regeneramos aqui.\n",
|
||
"try:\n",
|
||
" df_dash_sources\n",
|
||
" print('Reutilizando df_dash_sources del notebook 01')\n",
|
||
"except NameError:\n",
|
||
" print('df_dash_sources no esta en el kernel. Ejecuta el notebook 01 o copia la celda 26 aqui.')\n",
|
||
"else:\n",
|
||
" print()\n",
|
||
" print('=== DISTRIBUCION DE LAS 85 CARDS DEL DASHBOARD ===')\n",
|
||
" print(df_dash_sources.groupby(['source_db','source_table']).size().sort_values(ascending=False).to_string())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "96450ff7",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 9. Hallazgos y decisiones\n",
|
||
"\n",
|
||
"- (rellenar tras ejecutar)\n",
|
||
"- Cuál es la fuente canonica para \"venta web\" en reportes internos\n",
|
||
"- Cuándo usar cada una (p.ej. Cubo para analítica financiera, SO para operativa)\n",
|
||
"- Ajustes necesarios al dashboard 734 si mezcla fuentes"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 2,
|
||
"id": "6c5093a2",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"ename": "HTTPStatusError",
|
||
"evalue": "Client error '400 Bad Request' for url 'https://reports.autingo.es/api/dataset'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/400",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
|
||
"\u001b[31mHTTPStatusError\u001b[39m Traceback (most recent call last)",
|
||
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[2]\u001b[39m\u001b[32m, line 17\u001b[39m\n\u001b[32m 13\u001b[39m FROM `{CUBO}`\n\u001b[32m 14\u001b[39m WHERE Dim_NombreDimGlobal2 = \u001b[33m'WSWEB'\u001b[39m\n\u001b[32m 15\u001b[39m AND EXTRACT(YEAR FROM Fecha_Registro) = \u001b[32m2025\u001b[39m\n\u001b[32m 16\u001b[39m '''\n\u001b[32m---> \u001b[39m\u001b[32m17\u001b[39m df_cubo_tot = run_sql(sql_cubo_total)\n\u001b[32m 18\u001b[39m print(\u001b[33m'=== FUENTE 1: Cubo_Ventas_Calculado (WSWEB) 2025 ==='\u001b[39m)\n\u001b[32m 19\u001b[39m print(df_cubo_tot.to_string(index=\u001b[38;5;28;01mFalse\u001b[39;00m))\n",
|
||
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 20\u001b[39m, in \u001b[36mrun_sql\u001b[39m\u001b[34m(sql, db_id)\u001b[39m\n\u001b[32m 18\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m run_sql(sql: str, db_id: int = DB_BIGQUERY) -> pd.DataFrame:\n\u001b[32m 19\u001b[39m \u001b[33m\"\"\"Ejecuta SQL contra Metabase y retorna DataFrame.\"\"\"\u001b[39m\n\u001b[32m---> \u001b[39m\u001b[32m20\u001b[39m res = metabase_execute_query(client, db_id, sql)\n\u001b[32m 21\u001b[39m cols = [c[\u001b[33m'display_name'\u001b[39m] \u001b[38;5;28;01mor\u001b[39;00m c[\u001b[33m'name'\u001b[39m] \u001b[38;5;28;01mfor\u001b[39;00m c \u001b[38;5;28;01min\u001b[39;00m res[\u001b[33m'data'\u001b[39m][\u001b[33m'cols'\u001b[39m]]\n\u001b[32m 22\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m pd.DataFrame(res[\u001b[33m'data'\u001b[39m][\u001b[33m'rows'\u001b[39m], columns=cols)\n",
|
||
"\u001b[36mFile \u001b[39m\u001b[32m~/fn_registry/python/functions/metabase/cards.py:227\u001b[39m, in \u001b[36mmetabase_execute_query\u001b[39m\u001b[34m(client, database_id, sql, max_results)\u001b[39m\n\u001b[32m 222\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m max_results > \u001b[32m0\u001b[39m:\n\u001b[32m 223\u001b[39m body[\u001b[33m\"\u001b[39m\u001b[33mconstraints\u001b[39m\u001b[33m\"\u001b[39m] = {\n\u001b[32m 224\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mmax-results\u001b[39m\u001b[33m\"\u001b[39m: max_results,\n\u001b[32m 225\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mmax-results-bare-rows\u001b[39m\u001b[33m\"\u001b[39m: max_results,\n\u001b[32m 226\u001b[39m }\n\u001b[32m--> \u001b[39m\u001b[32m227\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mclient\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mPOST\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43m/api/dataset\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mjson\u001b[49m\u001b[43m=\u001b[49m\u001b[43mbody\u001b[49m\u001b[43m)\u001b[49m\n",
|
||
"\u001b[36mFile \u001b[39m\u001b[32m~/fn_registry/python/functions/metabase/client.py:45\u001b[39m, in \u001b[36mMetabaseClient.request\u001b[39m\u001b[34m(self, method, path, **kwargs)\u001b[39m\n\u001b[32m 31\u001b[39m \u001b[38;5;250m\u001b[39m\u001b[33;03m\"\"\"Ejecuta una peticion HTTP contra la API de Metabase.\u001b[39;00m\n\u001b[32m 32\u001b[39m \n\u001b[32m 33\u001b[39m \u001b[33;03mArgs:\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 42\u001b[39m \u001b[33;03m httpx.HTTPStatusError: Si el status code no es 2xx.\u001b[39;00m\n\u001b[32m 43\u001b[39m \u001b[33;03m\"\"\"\u001b[39;00m\n\u001b[32m 44\u001b[39m resp = \u001b[38;5;28mself\u001b[39m._http.request(method, path, **kwargs)\n\u001b[32m---> \u001b[39m\u001b[32m45\u001b[39m \u001b[43mresp\u001b[49m\u001b[43m.\u001b[49m\u001b[43mraise_for_status\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 46\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m resp.content:\n\u001b[32m 47\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n",
|
||
"\u001b[36mFile \u001b[39m\u001b[32m~/fn_registry/projects/aurgi/analysis/venta_web/.venv/lib/python3.13/site-packages/httpx/_models.py:829\u001b[39m, in \u001b[36mResponse.raise_for_status\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m 827\u001b[39m error_type = error_types.get(status_class, \u001b[33m\"\u001b[39m\u001b[33mInvalid status code\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m 828\u001b[39m message = message.format(\u001b[38;5;28mself\u001b[39m, error_type=error_type)\n\u001b[32m--> \u001b[39m\u001b[32m829\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m HTTPStatusError(message, request=request, response=\u001b[38;5;28mself\u001b[39m)\n",
|
||
"\u001b[31mHTTPStatusError\u001b[39m: Client error '400 Bad Request' for url 'https://reports.autingo.es/api/dataset'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/400"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# --- Paths cualificados reales (corregidos tras celda 4) ---\n",
|
||
"CUBO = 'anjana_bi_datamart.Cubo_Ventas_Calculado'\n",
|
||
"NAV_HEADER = 'mssql2022_dbo.anjana_sales_invoice_header'\n",
|
||
"NAV_LINE = 'mssql2022_dbo.anjana_sales_invoice_line'\n",
|
||
"SO = 'psql_dcpublic.supply_orders'\n",
|
||
"LO = 'psql_dcpublic.logistic_orders'\n",
|
||
"\n",
|
||
"# FUENTE 1: Cubo_Ventas_Calculado (WSWEB) 2025\n",
|
||
"sql_cubo_total = f'''\n",
|
||
"SELECT\n",
|
||
" COUNT(*) AS lineas,\n",
|
||
" SUM(Importe_Neto) AS revenue_total\n",
|
||
"FROM `{CUBO}`\n",
|
||
"WHERE Dim_NombreDimGlobal2 = 'WSWEB'\n",
|
||
" AND EXTRACT(YEAR FROM Fecha_Registro) = 2025\n",
|
||
"'''\n",
|
||
"df_cubo_tot = run_sql(sql_cubo_total)\n",
|
||
"print('=== FUENTE 1: Cubo_Ventas_Calculado (WSWEB) 2025 ===')\n",
|
||
"print(df_cubo_tot.to_string(index=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 3,
|
||
"id": "4af04f5b",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Tabla: Cubo_Ventas_Calculado db=6\n",
|
||
"Total columnas: 45\n",
|
||
"\n",
|
||
" fecha [DateTime]\n",
|
||
" Dim_Fecha [DateTime]\n",
|
||
" Dim_NombreCentro [Text]\n",
|
||
" Dim_IdComAutonoma [Integer]\n",
|
||
" Dim_NombreComAutonoma [Text]\n",
|
||
" Dim_IdZona [Integer]\n",
|
||
" Dim_NombreZona [Text]\n",
|
||
" Dim_AmbitoCentro [Text]\n",
|
||
" Dim_NombreTipoMov [Text]\n",
|
||
" Dim_NombreDimGlobal2 [Text]\n",
|
||
" Dim_NombreProveedor [Text]\n",
|
||
" Dim_NombreCampana [Text]\n",
|
||
" Dim_NombreTipoTicket [Text]\n",
|
||
" Dim_NombreMotivoAjuste [Text]\n",
|
||
" Dim_NombreProducto [Text]\n",
|
||
" Dim_CodProducto [Text]\n",
|
||
" Dim_IdCategoria [Text]\n",
|
||
" Dim_IdActivoExterno [Integer]\n",
|
||
" Dim_IdLiquidacion [Integer]\n",
|
||
" Dim_IdEstado [Integer]\n",
|
||
" Dim_IdTipo [Integer]\n",
|
||
" Dim_PeriodoCobertura [Integer]\n",
|
||
" Dim_Matricula [Text]\n",
|
||
" Dim_NombreCategoria [Text]\n",
|
||
" Dim_NombreTipo [Text]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Listar columnas de Cubo_Ventas_Calculado para conocer nombres reales\n",
|
||
"cubo_tbl = client.request(\"GET\", \"/api/table/2890/query_metadata\")\n",
|
||
"print(f\"Tabla: {cubo_tbl['name']} db={cubo_tbl['db_id']}\")\n",
|
||
"print(f\"Total columnas: {len(cubo_tbl['fields'])}\")\n",
|
||
"print()\n",
|
||
"# Buscar campos relacionados con fecha, importe, dimension\n",
|
||
"for f in cubo_tbl['fields']:\n",
|
||
" n = f['name']\n",
|
||
" if any(k in n.lower() for k in ['fecha', 'date', 'importe', 'amount', 'dim_', 'nombre']):\n",
|
||
" print(f\" {n:45} [{f['base_type'].replace('type/','')}]\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 4,
|
||
"id": "38d51545",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" idTipoMovimiento [Integer]\n",
|
||
" idMotivoAjuste [Integer]\n",
|
||
" idTipo [Integer]\n",
|
||
" idTipoDeTicket [Integer]\n",
|
||
" numeroLineas [Integer]\n",
|
||
" cantidad [Decimal]\n",
|
||
" costeUnitario [Decimal]\n",
|
||
" precioUnitario [Decimal]\n",
|
||
" compraReal [Decimal]\n",
|
||
" compraEsperada [Decimal]\n",
|
||
" Dim_IdComAutonoma [Integer]\n",
|
||
" Dim_IdZona [Integer]\n",
|
||
" Dim_IdActivoExterno [Integer]\n",
|
||
" Dim_IdLiquidacion [Integer]\n",
|
||
" Dim_IdEstado [Integer]\n",
|
||
" Dim_IdTipo [Integer]\n",
|
||
" Dim_PeriodoCobertura [Integer]\n",
|
||
" PrecioVenta [Decimal]\n",
|
||
" PrecioCompra [Decimal]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Todas las columnas numericas (para encontrar importe/revenue)\n",
|
||
"for f in cubo_tbl['fields']:\n",
|
||
" if f['base_type'] in ('type/Float', 'type/Decimal', 'type/Integer', 'type/BigInteger'):\n",
|
||
" print(f\" {f['name']:45} [{f['base_type'].replace('type/','')}]\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"id": "78650d74",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== FUENTE 1 (v2): Cubo_Ventas_Calculado WSWEB 2025 ===\n",
|
||
" lineas revenue suma_precio_venta\n",
|
||
" 158617 5,879,313.22 5,879,313.22\n",
|
||
"\n",
|
||
"Doc 8 dice: 5.879.313€ en 158.617 lineas\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Query Cubo ajustada: campo fecha es 'fecha', revenue = cantidad * precioUnitario\n",
|
||
"sql_cubo_total_v2 = f'''\n",
|
||
"SELECT\n",
|
||
" COUNT(*) AS lineas,\n",
|
||
" SUM(cantidad * precioUnitario) AS revenue,\n",
|
||
" SUM(PrecioVenta) AS suma_precio_venta\n",
|
||
"FROM `{CUBO}`\n",
|
||
"WHERE Dim_NombreDimGlobal2 = 'WSWEB'\n",
|
||
" AND EXTRACT(YEAR FROM fecha) = 2025\n",
|
||
"'''\n",
|
||
"df_cubo_v2 = run_sql(sql_cubo_total_v2)\n",
|
||
"print('=== FUENTE 1 (v2): Cubo_Ventas_Calculado WSWEB 2025 ===')\n",
|
||
"print(df_cubo_v2.to_string(index=False))\n",
|
||
"print()\n",
|
||
"print(f\"Doc 8 dice: 5.879.313€ en 158.617 lineas\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"id": "94ba6ba6",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"--- anjana_sales_invoice_header (id 3452) — 180 cols ---\n",
|
||
" dates: ['document_date', 'hora_env__sol__autorizacion', 'time_sent', 'pmt__discount_date', 'shipment_date', 'fecha_operacion']\n",
|
||
" nums: ['tipo_de_registro_tpv', 'applies_to_doc__type', 'estado_pago_web', 'eu_3_party_trade', 'get_shipment_used', 'credito_disponible', 'venta_online', 'num__turno']\n",
|
||
" keys: ['no_', 'document_date', 'order_no__series', 'vat_registration_no_', 'applies_to_doc__no_', 'applies_to_bill_no_', 'prepayment_no__series', 'quote_no_', 'num__turno', 'pre_assigned_no__series', 'campaign_no_', 'pre_assigned_no_']\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"--- anjana_sales_invoice_line (id 3437) — 126 cols ---\n",
|
||
" dates: ['fa_posting_date', 'shipment_date', 'posting_date', '_fivetran_synced']\n",
|
||
" nums: ['line_no_', 'ec__', 'vat__', 'permite_dto__promocion', 'cross_reference_type', 'job_contract_entry_no_', 'inv__discount_amount', 'unit_price']\n",
|
||
" keys: ['document_no_', 'line_no_', 'cross_reference_no_', 'job_contract_entry_no_', 'inv__discount_amount', 'unit_price', 'nonstock', 'line_amount', 'num__turno', 'shipment_no_', 'abono_num__linea_ticket', 'amount']\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"--- supply_orders (id 1530) — 58 cols ---\n",
|
||
" dates: ['delivery_date', 'created_at', 'updated_at', 'reviewed_at', 'shipped_at', 'provider_delivery_at']\n",
|
||
" nums: ['id', 'service_request_id', 'product_id', 'quantity', 'supply_method', 'provider_id', 'status', 'marketplace_offer_id']\n",
|
||
" keys: ['service_request_id', 'provider_order_id', 'logistic_order_id', 'sale_price', 'purchase_price', 'tpv_orders_order_id', 'tpv_orders_orderitem_id', 'eci_sell_price', 'shipping_price', 'internal_provider_order', 'official_service', 'order_version']\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"--- logistic_orders (id 1534) — 31 cols ---\n",
|
||
" dates: ['datetime', 'created_at', 'updated_at']\n",
|
||
" nums: ['id', 'service_request_id', 'center_id', 'provider_id', 'status', 'order_type', 'shipping_method', 'shipping_price']\n",
|
||
" keys: ['service_request_id', 'center_id', 'order_id', 'order_type', 'shipping_price', 'external_total_price', 'cd_order_id', 'center_request_id']\n",
|
||
"\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Inspect columns of the 4 remaining tables in BigQuery\n",
|
||
"TABLE_IDS = {\n",
|
||
" 'anjana_sales_invoice_header': 3452,\n",
|
||
" 'anjana_sales_invoice_line': 3437,\n",
|
||
" 'supply_orders': 1530,\n",
|
||
" 'logistic_orders': 1534,\n",
|
||
"}\n",
|
||
"tbl_meta = {}\n",
|
||
"for name, tid in TABLE_IDS.items():\n",
|
||
" m = client.request(\"GET\", f\"/api/table/{tid}/query_metadata\")\n",
|
||
" tbl_meta[name] = m\n",
|
||
" date_cols = [f['name'] for f in m['fields'] if f['base_type'] in ('type/Date','type/DateTime','type/DateTimeWithLocalTZ')]\n",
|
||
" num_cols = [f['name'] for f in m['fields'] if f['base_type'] in ('type/Float','type/Decimal','type/Integer','type/BigInteger')]\n",
|
||
" key_cols = [f['name'] for f in m['fields'] if any(k in f['name'].lower() for k in ['amount','price','location','center','no','document','order','request','service'])]\n",
|
||
" print(f\"--- {name} (id {tid}) — {len(m['fields'])} cols ---\")\n",
|
||
" print(f\" dates: {date_cols[:6]}\")\n",
|
||
" print(f\" nums: {num_cols[:8]}\")\n",
|
||
" print(f\" keys: {key_cols[:12]}\")\n",
|
||
" print()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"id": "7af4af12",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Location cols header: ['location_code']\n",
|
||
"Date/Fecha cols header: ['document_date', 'pmt__discount_date', 'shipment_date', 'fecha_operacion', 'fecha_env__sol__autorizacion', 'posting_date', 'order_date', 'date_sent', 'due_date']\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# location_code en header?\n",
|
||
"loc_cols = [f['name'] for f in tbl_meta['anjana_sales_invoice_header']['fields'] if 'location' in f['name'].lower()]\n",
|
||
"date_all = [f['name'] for f in tbl_meta['anjana_sales_invoice_header']['fields'] if 'date' in f['name'].lower() or 'fecha' in f['name'].lower()]\n",
|
||
"print('Location cols header:', loc_cols)\n",
|
||
"print('Date/Fecha cols header:', date_all)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"id": "31e6e417",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== FUENTE 2: NAV directo (centros web) 2025 ===\n",
|
||
" lineas revenue suma_line_amount\n",
|
||
" 315831 13,324,819.67 15,872,265.87\n",
|
||
"Doc 8 dice: 15.878.883€ en 315.173 lineas\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# FUENTE 2: NAV directo (centros web '18','19','405','421','422') 2025\n",
|
||
"sql_nav_total = f'''\n",
|
||
"SELECT\n",
|
||
" COUNT(*) AS lineas,\n",
|
||
" SUM(l.amount) AS revenue,\n",
|
||
" SUM(l.line_amount) AS suma_line_amount\n",
|
||
"FROM `{NAV_LINE}` l\n",
|
||
"JOIN `{NAV_HEADER}` h ON l.document_no_ = h.no_\n",
|
||
"WHERE h.location_code IN ('18','19','405','421','422')\n",
|
||
" AND EXTRACT(YEAR FROM h.posting_date) = 2025\n",
|
||
"'''\n",
|
||
"df_nav_v1 = run_sql(sql_nav_total)\n",
|
||
"print('=== FUENTE 2: NAV directo (centros web) 2025 ===')\n",
|
||
"print(df_nav_v1.to_string(index=False))\n",
|
||
"print(f\"Doc 8 dice: 15.878.883€ en 315.173 lineas\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"id": "86058b68",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== FUENTE 3: Supply Orders web (service_request_id NOT NULL) 2025 ===\n",
|
||
" supply_orders revenue_sale_x_qty suma_sale_price\n",
|
||
" 192251 22,669,646.01 11,302,142.62\n",
|
||
"Doc 8 dice: 7.235.399€ en ~160K lineas\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# FUENTE 3: Supply Orders web (service_request_id IS NOT NULL) 2025\n",
|
||
"sql_so_total = f'''\n",
|
||
"SELECT\n",
|
||
" COUNT(*) AS supply_orders,\n",
|
||
" SUM(sale_price * quantity) AS revenue_sale_x_qty,\n",
|
||
" SUM(sale_price) AS suma_sale_price\n",
|
||
"FROM `{SO}`\n",
|
||
"WHERE service_request_id IS NOT NULL\n",
|
||
" AND EXTRACT(YEAR FROM created_at) = 2025\n",
|
||
"'''\n",
|
||
"df_so = run_sql(sql_so_total)\n",
|
||
"print('=== FUENTE 3: Supply Orders web (service_request_id NOT NULL) 2025 ===')\n",
|
||
"print(df_so.to_string(index=False))\n",
|
||
"print(f\"Doc 8 dice: 7.235.399€ en ~160K lineas\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"id": "0557b658",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"ename": "NameError",
|
||
"evalue": "name 'db6' is not defined",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
|
||
"\u001b[31mNameError\u001b[39m Traceback (most recent call last)",
|
||
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[10]\u001b[39m\u001b[32m, line 4\u001b[39m\n\u001b[32m 1\u001b[39m \u001b[38;5;66;03m# Buscar tablas candidatas para \"centros\" con flag digital\u001b[39;00m\n\u001b[32m 2\u001b[39m \u001b[38;5;66;03m# Probables: catalogos maestros en anjana_bi_datamart, mssql2022_dbo o anjana_bi_ntg\u001b[39;00m\n\u001b[32m 3\u001b[39m candidates = []\n\u001b[32m----> \u001b[39m\u001b[32m4\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m t \u001b[38;5;28;01min\u001b[39;00m db6[\u001b[33m'tables'\u001b[39m]:\n\u001b[32m 5\u001b[39m n = t[\u001b[33m'name'\u001b[39m].lower()\n\u001b[32m 6\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m any(k \u001b[38;5;28;01min\u001b[39;00m n \u001b[38;5;28;01mfor\u001b[39;00m k \u001b[38;5;28;01min\u001b[39;00m [\u001b[33m'centro'\u001b[39m, \u001b[33m'center'\u001b[39m, \u001b[33m'compania'\u001b[39m, \u001b[33m'company'\u001b[39m, \u001b[33m'location'\u001b[39m, \u001b[33m'dim_centro'\u001b[39m, \u001b[33m'dim_nom'\u001b[39m]):\n\u001b[32m 7\u001b[39m candidates.append({\u001b[33m'id'\u001b[39m: t[\u001b[33m'id'\u001b[39m], \u001b[33m'schema'\u001b[39m: t.get(\u001b[33m'schema'\u001b[39m,\u001b[33m''\u001b[39m), \u001b[33m'name'\u001b[39m: t[\u001b[33m'name'\u001b[39m], \u001b[33m'rows'\u001b[39m: t.get(\u001b[33m'entity_type'\u001b[39m)})\n",
|
||
"\u001b[31mNameError\u001b[39m: name 'db6' is not defined"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Buscar tablas candidatas para \"centros\" con flag digital\n",
|
||
"# Probables: catalogos maestros en anjana_bi_datamart, mssql2022_dbo o anjana_bi_ntg\n",
|
||
"candidates = []\n",
|
||
"for t in db6['tables']:\n",
|
||
" n = t['name'].lower()\n",
|
||
" if any(k in n for k in ['centro', 'center', 'compania', 'company', 'location', 'dim_centro', 'dim_nom']):\n",
|
||
" candidates.append({'id': t['id'], 'schema': t.get('schema',''), 'name': t['name'], 'rows': t.get('entity_type')})\n",
|
||
"pd.DataFrame(candidates).head(30)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"id": "89818b26",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Tablas candidatas centros: 163\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>id</th>\n",
|
||
" <th>schema</th>\n",
|
||
" <th>name</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>2332</td>\n",
|
||
" <td>google_ads_data</td>\n",
|
||
" <td>ads_CampaignLocationTargetStats_7692019626</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>2365</td>\n",
|
||
" <td>google_ads_data</td>\n",
|
||
" <td>ads_LocationBasedCampaignCriterion_7692019626</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>2450</td>\n",
|
||
" <td>google_ads_data</td>\n",
|
||
" <td>ads_LocationsDistanceStats_7692019626</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>2354</td>\n",
|
||
" <td>google_ads_data</td>\n",
|
||
" <td>ads_LocationsUserLocationsStats_7692019626</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>4141</td>\n",
|
||
" <td>anjana_bi_datamart</td>\n",
|
||
" <td>agg_venta_cat_centro_dia_mas_n1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5</th>\n",
|
||
" <td>4091</td>\n",
|
||
" <td>anjana_bi_datamart</td>\n",
|
||
" <td>agg_venta_cat_centro_semana_mas_n1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6</th>\n",
|
||
" <td>1914</td>\n",
|
||
" <td>almacen_movs</td>\n",
|
||
" <td>almacen_centro</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>7</th>\n",
|
||
" <td>1924</td>\n",
|
||
" <td>stg_anjana_bi</td>\n",
|
||
" <td>almacen_centro</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>8</th>\n",
|
||
" <td>3424</td>\n",
|
||
" <td>mssql2022_dbo</td>\n",
|
||
" <td>anjana_location</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>9</th>\n",
|
||
" <td>4263</td>\n",
|
||
" <td>anjana_bi_amg</td>\n",
|
||
" <td>apertura_agosto_centros</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>10</th>\n",
|
||
" <td>3681</td>\n",
|
||
" <td>anjana_bi_amg</td>\n",
|
||
" <td>apertura_centros</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>11</th>\n",
|
||
" <td>3940</td>\n",
|
||
" <td>anjana_bi_amg</td>\n",
|
||
" <td>apertura_centros_junio_v3</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>12</th>\n",
|
||
" <td>4493</td>\n",
|
||
" <td>stg_anjana_bi</td>\n",
|
||
" <td>apertura_centros_mat</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>13</th>\n",
|
||
" <td>3941</td>\n",
|
||
" <td>anjana_bi_amg</td>\n",
|
||
" <td>apertura_junio_centros_patch_1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>14</th>\n",
|
||
" <td>3674</td>\n",
|
||
" <td>anjana_bi_datamart</td>\n",
|
||
" <td>apertura_mayo_centros</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>15</th>\n",
|
||
" <td>3836</td>\n",
|
||
" <td>anjana_bi_amg</td>\n",
|
||
" <td>aperturas_junio_centros</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>16</th>\n",
|
||
" <td>3455</td>\n",
|
||
" <td>mssql2022_dbo</td>\n",
|
||
" <td>autocentros_del_suroeste_itemstatusmodlog</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>17</th>\n",
|
||
" <td>3431</td>\n",
|
||
" <td>mssql2022_dbo</td>\n",
|
||
" <td>autocentros_del_suroeste_purchdocsdeletelog</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>18</th>\n",
|
||
" <td>4472</td>\n",
|
||
" <td>anjana_bi_ntg</td>\n",
|
||
" <td>boxes_centros_mecanica_cristales</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>19</th>\n",
|
||
" <td>4475</td>\n",
|
||
" <td>anjana_bi_ntg</td>\n",
|
||
" <td>boxes_centros_mecanica_cristales_completo</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>20</th>\n",
|
||
" <td>4218</td>\n",
|
||
" <td>anjana_bi_datamart</td>\n",
|
||
" <td>Calendario_centros_productos</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>21</th>\n",
|
||
" <td>4216</td>\n",
|
||
" <td>anjana_bi_datamart</td>\n",
|
||
" <td>Calendario_productos_centros_ventas_n-1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>22</th>\n",
|
||
" <td>4242</td>\n",
|
||
" <td>anjana_bi_datamart</td>\n",
|
||
" <td>Calen_product_center_n_materialized</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>23</th>\n",
|
||
" <td>3105</td>\n",
|
||
" <td>anjana_bi_datamart</td>\n",
|
||
" <td>Cantidad_de_citas_contra_total_tiempo_citas_centros_cristales_prox_semana</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>24</th>\n",
|
||
" <td>1588</td>\n",
|
||
" <td>psql_dcpublic</td>\n",
|
||
" <td>centers</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>25</th>\n",
|
||
" <td>3135</td>\n",
|
||
" <td>anjana_bi_amg</td>\n",
|
||
" <td>centers_clean</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>26</th>\n",
|
||
" <td>2939</td>\n",
|
||
" <td>test_sales</td>\n",
|
||
" <td>centros</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>27</th>\n",
|
||
" <td>4102</td>\n",
|
||
" <td>questions_metabase</td>\n",
|
||
" <td>centros</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>28</th>\n",
|
||
" <td>1679</td>\n",
|
||
" <td>citaprevia_aurphcp</td>\n",
|
||
" <td>centros</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>29</th>\n",
|
||
" <td>1926</td>\n",
|
||
" <td>stg_anjana_bi</td>\n",
|
||
" <td>centros</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" id schema \\\n",
|
||
"0 2332 google_ads_data \n",
|
||
"1 2365 google_ads_data \n",
|
||
"2 2450 google_ads_data \n",
|
||
"3 2354 google_ads_data \n",
|
||
"4 4141 anjana_bi_datamart \n",
|
||
"5 4091 anjana_bi_datamart \n",
|
||
"6 1914 almacen_movs \n",
|
||
"7 1924 stg_anjana_bi \n",
|
||
"8 3424 mssql2022_dbo \n",
|
||
"9 4263 anjana_bi_amg \n",
|
||
"10 3681 anjana_bi_amg \n",
|
||
"11 3940 anjana_bi_amg \n",
|
||
"12 4493 stg_anjana_bi \n",
|
||
"13 3941 anjana_bi_amg \n",
|
||
"14 3674 anjana_bi_datamart \n",
|
||
"15 3836 anjana_bi_amg \n",
|
||
"16 3455 mssql2022_dbo \n",
|
||
"17 3431 mssql2022_dbo \n",
|
||
"18 4472 anjana_bi_ntg \n",
|
||
"19 4475 anjana_bi_ntg \n",
|
||
"20 4218 anjana_bi_datamart \n",
|
||
"21 4216 anjana_bi_datamart \n",
|
||
"22 4242 anjana_bi_datamart \n",
|
||
"23 3105 anjana_bi_datamart \n",
|
||
"24 1588 psql_dcpublic \n",
|
||
"25 3135 anjana_bi_amg \n",
|
||
"26 2939 test_sales \n",
|
||
"27 4102 questions_metabase \n",
|
||
"28 1679 citaprevia_aurphcp \n",
|
||
"29 1926 stg_anjana_bi \n",
|
||
"\n",
|
||
" name \n",
|
||
"0 ads_CampaignLocationTargetStats_7692019626 \n",
|
||
"1 ads_LocationBasedCampaignCriterion_7692019626 \n",
|
||
"2 ads_LocationsDistanceStats_7692019626 \n",
|
||
"3 ads_LocationsUserLocationsStats_7692019626 \n",
|
||
"4 agg_venta_cat_centro_dia_mas_n1 \n",
|
||
"5 agg_venta_cat_centro_semana_mas_n1 \n",
|
||
"6 almacen_centro \n",
|
||
"7 almacen_centro \n",
|
||
"8 anjana_location \n",
|
||
"9 apertura_agosto_centros \n",
|
||
"10 apertura_centros \n",
|
||
"11 apertura_centros_junio_v3 \n",
|
||
"12 apertura_centros_mat \n",
|
||
"13 apertura_junio_centros_patch_1 \n",
|
||
"14 apertura_mayo_centros \n",
|
||
"15 aperturas_junio_centros \n",
|
||
"16 autocentros_del_suroeste_itemstatusmodlog \n",
|
||
"17 autocentros_del_suroeste_purchdocsdeletelog \n",
|
||
"18 boxes_centros_mecanica_cristales \n",
|
||
"19 boxes_centros_mecanica_cristales_completo \n",
|
||
"20 Calendario_centros_productos \n",
|
||
"21 Calendario_productos_centros_ventas_n-1 \n",
|
||
"22 Calen_product_center_n_materialized \n",
|
||
"23 Cantidad_de_citas_contra_total_tiempo_citas_centros_cristales_prox_semana \n",
|
||
"24 centers \n",
|
||
"25 centers_clean \n",
|
||
"26 centros \n",
|
||
"27 centros \n",
|
||
"28 centros \n",
|
||
"29 centros "
|
||
]
|
||
},
|
||
"execution_count": 11,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Recargar metadata y globals tras restart del kernel\n",
|
||
"db6 = client.request('GET', '/api/database/6?include=tables')\n",
|
||
"TABLE_IDS = {\n",
|
||
" 'anjana_sales_invoice_header': 3452,\n",
|
||
" 'anjana_sales_invoice_line': 3437,\n",
|
||
" 'supply_orders': 1530,\n",
|
||
" 'logistic_orders': 1534,\n",
|
||
"}\n",
|
||
"tbl_meta = {}\n",
|
||
"for name, tid in TABLE_IDS.items():\n",
|
||
" tbl_meta[name] = client.request(\"GET\", f\"/api/table/{tid}/query_metadata\")\n",
|
||
"cubo_tbl = client.request(\"GET\", \"/api/table/2890/query_metadata\")\n",
|
||
"\n",
|
||
"CUBO = 'anjana_bi_datamart.Cubo_Ventas_Calculado'\n",
|
||
"NAV_HEADER = 'mssql2022_dbo.anjana_sales_invoice_header'\n",
|
||
"NAV_LINE = 'mssql2022_dbo.anjana_sales_invoice_line'\n",
|
||
"SO = 'psql_dcpublic.supply_orders'\n",
|
||
"LO = 'psql_dcpublic.logistic_orders'\n",
|
||
"\n",
|
||
"# Buscar tablas de centros\n",
|
||
"candidates = []\n",
|
||
"for t in db6['tables']:\n",
|
||
" n = t['name'].lower()\n",
|
||
" if any(k in n for k in ['centro', 'center', 'compania', 'company', 'location']):\n",
|
||
" candidates.append({'id': t['id'], 'schema': t.get('schema',''), 'name': t['name']})\n",
|
||
"print(f\"Tablas candidatas centros: {len(candidates)}\")\n",
|
||
"pd.DataFrame(candidates).head(30)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"id": "f9f93165",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== mssql2022_dbo.anjana_location (id 3424) — 108 cols ===\n",
|
||
" code [Text]\n",
|
||
" cross_dock_bin_code [Text]\n",
|
||
" tipo_de_surtido [Integer]\n",
|
||
" shipment_bin_code [Text]\n",
|
||
" post_code [Text]\n",
|
||
" receipt_bin_code [Text]\n",
|
||
" outbound_production_bin_code [Text]\n",
|
||
" open_shop_floor_bin_code [Text]\n",
|
||
" name_2 [Text]\n",
|
||
" inbound_bom_bin_code [Text]\n",
|
||
" base_calendar_code [Text]\n",
|
||
" adjustment_bin_code [Text]\n",
|
||
" name [Text]\n",
|
||
" outbound_bom_bin_code [Text]\n",
|
||
" country_region_code [Text]\n",
|
||
" inbound_production_bin_code [Text]\n",
|
||
" put_away_template_code [Text]\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== psql_dcpublic.centers (id 1588) — 101 cols ===\n",
|
||
" id [Integer]\n",
|
||
" name [Text]\n",
|
||
" nav_id [Text]\n",
|
||
" company_id [Integer]\n",
|
||
" center_type [Integer]\n",
|
||
" store_type [Integer]\n",
|
||
" postal_code [Text]\n",
|
||
" municipality_id [Integer]\n",
|
||
" normalized_name [Text]\n",
|
||
" external_id [Text]\n",
|
||
" allow_automatic_provider_orders [Boolean]\n",
|
||
" tax_type [Integer]\n",
|
||
" teccom_id [Text]\n",
|
||
" uuid [Text]\n",
|
||
" provider_config [JSON]\n",
|
||
" pin_pad_payment_type_id [Integer]\n",
|
||
" cash_payment_type_id [Integer]\n",
|
||
" zone_id [Integer]\n",
|
||
" visualtime_group_id [Integer]\n",
|
||
" stock_center_id [Integer]\n",
|
||
" is_digital [Boolean]\n",
|
||
"\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Inspeccionar las 2 candidatas mas probables: anjana_location (Navision) y centers (DC)\n",
|
||
"for tid, label in [(3424, 'mssql2022_dbo.anjana_location'), (1588, 'psql_dcpublic.centers')]:\n",
|
||
" m = client.request(\"GET\", f\"/api/table/{tid}/query_metadata\")\n",
|
||
" print(f\"=== {label} (id {tid}) — {len(m['fields'])} cols ===\")\n",
|
||
" for f in m['fields']:\n",
|
||
" n = f['name']\n",
|
||
" if any(k in n.lower() for k in ['code','name','company','compan','nav','id','type','digital','online','web','channel']):\n",
|
||
" print(f\" {n:40} [{f['base_type'].replace('type/','')}]\")\n",
|
||
" print()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"id": "815845c6",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Centros digitales: 5\n",
|
||
" id name nav_id company_id center_type\n",
|
||
"160 Aurgi Web 18 1 0\n",
|
||
"161 MT Web 19 2 0\n",
|
||
"167 Autingo 405 3 0\n",
|
||
"183 Aurgi Asociados Gruas 421 1 0\n",
|
||
"184 Aurgi Asociados 422 1 0\n",
|
||
"\n",
|
||
"nav_ids digital: ('18', '19', '405', '421', '422')\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Listar centros digitales\n",
|
||
"CENTERS = 'psql_dcpublic.centers'\n",
|
||
"sql_digital = f'''\n",
|
||
"SELECT id, name, nav_id, company_id, center_type\n",
|
||
"FROM `{CENTERS}`\n",
|
||
"WHERE is_digital = TRUE\n",
|
||
"ORDER BY nav_id\n",
|
||
"'''\n",
|
||
"df_digital = run_sql(sql_digital)\n",
|
||
"print(f'Centros digitales: {len(df_digital)}')\n",
|
||
"print(df_digital.to_string(index=False))\n",
|
||
"NAV_IDS_DIGITAL = tuple(df_digital['nav_id'].dropna().tolist())\n",
|
||
"print()\n",
|
||
"print('nav_ids digital:', NAV_IDS_DIGITAL)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"id": "494880ac",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>compania</th>\n",
|
||
" <th>centro</th>\n",
|
||
" <th>tipo_mov</th>\n",
|
||
" <th>lineas</th>\n",
|
||
" <th>revenue</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>WSWEB</td>\n",
|
||
" <td>Aurgi Web</td>\n",
|
||
" <td>Venta</td>\n",
|
||
" <td>116266</td>\n",
|
||
" <td>3,777,996.81</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>WSWEB</td>\n",
|
||
" <td>Aurgi Asociados Gruas</td>\n",
|
||
" <td>Venta</td>\n",
|
||
" <td>27464</td>\n",
|
||
" <td>1,183,043.04</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>WSWEB</td>\n",
|
||
" <td>Autingo</td>\n",
|
||
" <td>Venta</td>\n",
|
||
" <td>11339</td>\n",
|
||
" <td>725,910.50</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>WSWEB</td>\n",
|
||
" <td>Aurgi Asociados</td>\n",
|
||
" <td>Venta</td>\n",
|
||
" <td>5</td>\n",
|
||
" <td>121,059.17</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>WSWEB</td>\n",
|
||
" <td>MT Web</td>\n",
|
||
" <td>Venta</td>\n",
|
||
" <td>3543</td>\n",
|
||
" <td>71,303.70</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" compania centro tipo_mov lineas revenue\n",
|
||
"0 WSWEB Aurgi Web Venta 116266 3,777,996.81\n",
|
||
"1 WSWEB Aurgi Asociados Gruas Venta 27464 1,183,043.04\n",
|
||
"2 WSWEB Autingo Venta 11339 725,910.50\n",
|
||
"3 WSWEB Aurgi Asociados Venta 5 121,059.17\n",
|
||
"4 WSWEB MT Web Venta 3543 71,303.70"
|
||
]
|
||
},
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Valores en el Cubo para identificar centros digital. Mirar Dim_NombreCentro y tipos de mov.\n",
|
||
"sql_cubo_vals = f'''\n",
|
||
"SELECT\n",
|
||
" Dim_NombreDimGlobal2 AS compania,\n",
|
||
" Dim_NombreCentro AS centro,\n",
|
||
" Dim_NombreTipoMov AS tipo_mov,\n",
|
||
" COUNT(*) AS lineas,\n",
|
||
" SUM(cantidad * precioUnitario) AS revenue\n",
|
||
"FROM `{CUBO}`\n",
|
||
"WHERE EXTRACT(YEAR FROM fecha) = 2025\n",
|
||
" AND Dim_NombreDimGlobal2 = 'WSWEB'\n",
|
||
"GROUP BY compania, centro, tipo_mov\n",
|
||
"ORDER BY revenue DESC\n",
|
||
"LIMIT 50\n",
|
||
"'''\n",
|
||
"df_cubo_vals = run_sql(sql_cubo_vals)\n",
|
||
"df_cubo_vals"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"id": "7c686f5e",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Document/type cols header: ['document_date', 'tipo_de_registro_tpv', 'applies_to_doc__type', 'tipo_operacion_intracomunitar', 'tipo_identificacion', 'tipo_factura', 'external_document_no_', 'n__documento_agrupado', 'bal__account_type', 'service_mgt__document', 'biztalk_document_sent', 'tipo_forma_pago', 'transaction_type', 'tipo_cliente_a_credito', 'tipo_fact__recrificativa_sii']\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# NAV centros digitales 2025: desglose por document_type y location\n",
|
||
"# Tambien ver campos posibles de document_type en el header\n",
|
||
"header_fields = [f['name'] for f in tbl_meta['anjana_sales_invoice_header']['fields']]\n",
|
||
"doctype_cands = [n for n in header_fields if 'document' in n.lower() or 'type' in n.lower() or 'tipo' in n.lower()]\n",
|
||
"print('Document/type cols header:', doctype_cands[:20])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"id": "3c0e4fc0",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" 3423 anjana_sales_cr_memo_header\n",
|
||
" 3420 anjana_sales_cr_memo_line\n",
|
||
" 3422 anjana_sales_header\n",
|
||
" 3452 anjana_sales_invoice_header\n",
|
||
" 3437 anjana_sales_invoice_line\n",
|
||
" 3438 anjana_sales_shipment_header\n",
|
||
" 3447 anjana_sales_shipment_line\n",
|
||
" 3456 sales_price\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Buscar tablas complementarias: credit_memo / abono en mssql2022_dbo\n",
|
||
"nav_tables = [t for t in db6['tables'] if t.get('schema') == 'mssql2022_dbo' and \n",
|
||
" any(k in t['name'].lower() for k in ['invoice', 'credit', 'memo', 'abono', 'sales', 'return'])]\n",
|
||
"for t in nav_tables[:30]:\n",
|
||
" print(f\" {t['id']:5} {t['name']}\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 17,
|
||
"id": "a839b6f0",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== CUBO WSWEB Venta 2025 (por mes y centro) ===\n",
|
||
" mes centro tipos_ticket lineas revenue\n",
|
||
"2025-01 Aurgi Web 1 7194 225,546.19\n",
|
||
"2025-01 Autingo 1 817 37,279.39\n",
|
||
"2025-01 MT Web 1 841 17,140.52\n",
|
||
"2025-02 Aurgi Web 1 6639 199,168.29\n",
|
||
"2025-02 Autingo 1 651 32,029.22\n",
|
||
"2025-02 MT Web 1 282 4,990.85\n",
|
||
"2025-03 Aurgi Web 1 10983 291,552.93\n",
|
||
"2025-03 Autingo 1 1066 44,017.23\n",
|
||
"2025-03 MT Web 1 265 4,913.40\n",
|
||
"2025-04 Aurgi Asociados 1 1 165.12\n",
|
||
"2025-04 Aurgi Web 1 9272 269,613.69\n",
|
||
"2025-04 Autingo 1 762 36,524.61\n",
|
||
"2025-04 MT Web 1 187 4,311.97\n",
|
||
"2025-05 Aurgi Web 1 14096 416,243.31\n",
|
||
"2025-05 Autingo 1 1025 63,574.06\n",
|
||
"2025-05 MT Web 1 195 3,167.68\n",
|
||
"2025-06 Aurgi Web 1 14319 538,660.24\n",
|
||
"2025-06 Autingo 1 1340 106,750.38\n",
|
||
"2025-06 MT Web 1 208 4,092.61\n",
|
||
"2025-07 Aurgi Asociados 1 1 768.60\n",
|
||
"2025-07 Aurgi Web 1 14253 474,104.39\n",
|
||
"2025-07 Autingo 1 1647 120,074.72\n",
|
||
"2025-07 MT Web 1 192 3,933.84\n",
|
||
"2025-08 Aurgi Web 1 12914 406,695.78\n",
|
||
"2025-08 Autingo 1 1309 98,284.35\n",
|
||
"2025-08 MT Web 1 211 3,970.94\n",
|
||
"2025-09 Aurgi Asociados 1 1 125.45\n",
|
||
"2025-09 Aurgi Web 1 11336 362,341.53\n",
|
||
"2025-09 Autingo 1 936 66,635.28\n",
|
||
"2025-09 MT Web 1 181 3,756.54\n",
|
||
"2025-10 Aurgi Web 1 6787 242,111.20\n",
|
||
"2025-10 Autingo 1 914 62,344.22\n",
|
||
"2025-10 MT Web 1 235 5,063.87\n",
|
||
"2025-11 Aurgi Asociados Gruas 1 12 478.67\n",
|
||
"2025-11 Aurgi Web 1 6099 245,523.66\n",
|
||
"2025-11 Autingo 1 470 32,059.47\n",
|
||
"2025-11 MT Web 1 291 6,050.80\n",
|
||
"2025-12 Aurgi Asociados 1 2 120,000.00\n",
|
||
"2025-12 Aurgi Asociados Gruas 1 27452 1,182,564.37\n",
|
||
"2025-12 Aurgi Web 1 2374 106,435.60\n",
|
||
"2025-12 Autingo 1 402 26,337.57\n",
|
||
"2025-12 MT Web 1 455 9,910.68\n",
|
||
"\n",
|
||
"=== NAV directo centros digital 2025 (por mes y centro) ===\n",
|
||
" mes centro facturas lineas revenue_bruto revenue_neto\n",
|
||
"2025-01 18 13826 14107 545,817.10 451,092.37\n",
|
||
"2025-01 19 556 1119 41,481.82 34,281.91\n",
|
||
"2025-01 405 1703 1930 151,617.87 125,763.47\n",
|
||
"2025-02 18 12738 13008 481,985.12 398,336.60\n",
|
||
"2025-02 19 186 375 12,078.54 9,981.99\n",
|
||
"2025-02 405 1404 1597 118,325.88 97,789.87\n",
|
||
"2025-02 421 3 12 25,235.29 24,421.18\n",
|
||
"2025-03 18 21404 21695 706,556.94 584,016.70\n",
|
||
"2025-03 19 168 349 11,890.82 9,826.97\n",
|
||
"2025-03 405 2204 2461 155,032.74 128,125.80\n",
|
||
"2025-03 421 5 21 68,353.88 68,353.88\n",
|
||
"2025-04 18 17975 18252 652,055.79 538,890.56\n",
|
||
"2025-04 19 120 247 10,435.50 8,624.14\n",
|
||
"2025-04 405 1584 1778 134,098.20 110,824.51\n",
|
||
"2025-04 421 11 80 164,730.03 164,730.03\n",
|
||
"2025-04 422 2 2 399.60 330.24\n",
|
||
"2025-05 18 27494 27886 1,018,084.82 843,011.44\n",
|
||
"2025-05 19 130 260 7,666.28 6,335.59\n",
|
||
"2025-05 405 2105 2328 205,038.60 169,453.97\n",
|
||
"2025-05 421 12 51 86,491.73 86,491.73\n",
|
||
"2025-06 18 28022 28376 1,322,181.29 1,095,747.50\n",
|
||
"2025-06 19 136 276 9,904.60 8,185.45\n",
|
||
"2025-06 405 2764 2988 316,731.91 261,763.09\n",
|
||
"2025-06 421 10 48 116,732.66 116,732.66\n",
|
||
"2025-07 18 27610 28193 1,178,749.89 979,604.31\n",
|
||
"2025-07 19 126 255 9,520.20 7,867.80\n",
|
||
"2025-07 405 3372 3621 354,553.22 293,149.99\n",
|
||
"2025-07 421 16 60 135,986.92 135,986.92\n",
|
||
"2025-07 422 2 2 1,860.00 1,537.20\n",
|
||
"2025-08 18 25115 25495 986,518.81 815,692.95\n",
|
||
"2025-08 19 138 280 9,610.10 7,942.05\n",
|
||
"2025-08 405 2666 2829 271,704.71 224,551.24\n",
|
||
"2025-08 421 9 45 61,575.89 61,575.89\n",
|
||
"2025-09 18 22176 22456 881,738.19 729,572.09\n",
|
||
"2025-09 19 120 241 9,091.08 7,513.22\n",
|
||
"2025-09 405 1946 2109 205,127.52 169,527.47\n",
|
||
"2025-09 421 18 65 125,276.25 125,276.25\n",
|
||
"2025-09 422 2 2 303.60 250.90\n",
|
||
"2025-10 18 13110 13362 586,518.09 484,839.92\n",
|
||
"2025-10 19 156 313 12,255.24 10,128.06\n",
|
||
"2025-10 405 1924 2140 208,108.28 171,990.83\n",
|
||
"2025-10 421 14 60 112,173.57 112,173.57\n",
|
||
"2025-11 18 11832 12018 594,465.75 491,294.12\n",
|
||
"2025-11 19 190 386 14,643.46 12,101.80\n",
|
||
"2025-11 405 1028 1191 123,296.19 101,897.57\n",
|
||
"2025-11 421 49 109 131,830.71 131,629.65\n",
|
||
"2025-12 18 4376 4560 257,334.81 212,672.73\n",
|
||
"2025-12 19 302 606 23,984.90 19,821.76\n",
|
||
"2025-12 405 866 998 93,023.48 76,879.07\n",
|
||
"2025-12 421 55138 55187 2,974,888.00 2,476,230.66\n",
|
||
"2025-12 422 2 2 145,200.00 120,000.00\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# --- Comparativa mensual 2025: Cubo vs NAV (centros digital 18/19/405/421/422) ---\n",
|
||
"# Incluye: revenue, nº facturas/tickets, nº lineas\n",
|
||
"\n",
|
||
"CENTROS_DIGITAL = \"('18','19','405','421','422')\"\n",
|
||
"CENTROS_DIGITAL_NOMBRES = \"('Aurgi Web','MT Web','Autingo','Aurgi Asociados Gruas','Aurgi Asociados')\"\n",
|
||
"\n",
|
||
"sql_cubo_mes = f'''\n",
|
||
"SELECT\n",
|
||
" FORMAT_DATE('%Y-%m', fecha) AS mes,\n",
|
||
" Dim_NombreCentro AS centro,\n",
|
||
" COUNT(DISTINCT Dim_NombreTipoTicket) AS tipos_ticket,\n",
|
||
" COUNT(*) AS lineas,\n",
|
||
" SUM(cantidad * precioUnitario) AS revenue\n",
|
||
"FROM `{CUBO}`\n",
|
||
"WHERE Dim_NombreDimGlobal2 = 'WSWEB'\n",
|
||
" AND Dim_NombreTipoMov = 'Venta'\n",
|
||
" AND EXTRACT(YEAR FROM fecha) = 2025\n",
|
||
"GROUP BY mes, centro\n",
|
||
"ORDER BY mes, centro\n",
|
||
"'''\n",
|
||
"df_cubo_mes = run_sql(sql_cubo_mes)\n",
|
||
"\n",
|
||
"sql_nav_mes = f'''\n",
|
||
"SELECT\n",
|
||
" FORMAT_DATE('%Y-%m', h.posting_date) AS mes,\n",
|
||
" h.location_code AS centro,\n",
|
||
" COUNT(DISTINCT h.no_) AS facturas,\n",
|
||
" COUNT(*) AS lineas,\n",
|
||
" SUM(l.line_amount) AS revenue_bruto,\n",
|
||
" SUM(l.amount) AS revenue_neto\n",
|
||
"FROM `{NAV_LINE}` l\n",
|
||
"JOIN `{NAV_HEADER}` h ON l.document_no_ = h.no_\n",
|
||
"WHERE h.location_code IN {CENTROS_DIGITAL}\n",
|
||
" AND EXTRACT(YEAR FROM h.posting_date) = 2025\n",
|
||
"GROUP BY mes, centro\n",
|
||
"ORDER BY mes, centro\n",
|
||
"'''\n",
|
||
"df_nav_mes = run_sql(sql_nav_mes)\n",
|
||
"\n",
|
||
"print('=== CUBO WSWEB Venta 2025 (por mes y centro) ===')\n",
|
||
"print(df_cubo_mes.to_string(index=False))\n",
|
||
"print()\n",
|
||
"print('=== NAV directo centros digital 2025 (por mes y centro) ===')\n",
|
||
"print(df_nav_mes.to_string(index=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 18,
|
||
"id": "dab0247e",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== NAV tipos de registro (centros digital 2025) ===\n",
|
||
" tipo_de_registro_tpv tipo_factura transaction_type facturas revenue\n",
|
||
" 4 306634 14,670,280.59\n",
|
||
" 0 F1 231 1,201,985.28\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Que tipos de registros tiene NAV para centros digitales 2025\n",
|
||
"sql_nav_types = f'''\n",
|
||
"SELECT\n",
|
||
" h.tipo_de_registro_tpv,\n",
|
||
" h.tipo_factura,\n",
|
||
" h.transaction_type,\n",
|
||
" COUNT(DISTINCT h.no_) AS facturas,\n",
|
||
" SUM(l.line_amount) AS revenue\n",
|
||
"FROM `{NAV_LINE}` l\n",
|
||
"JOIN `{NAV_HEADER}` h ON l.document_no_ = h.no_\n",
|
||
"WHERE h.location_code IN {CENTROS_DIGITAL}\n",
|
||
" AND EXTRACT(YEAR FROM h.posting_date) = 2025\n",
|
||
"GROUP BY h.tipo_de_registro_tpv, h.tipo_factura, h.transaction_type\n",
|
||
"ORDER BY facturas DESC\n",
|
||
"'''\n",
|
||
"df_nav_types = run_sql(sql_nav_types)\n",
|
||
"print('=== NAV tipos de registro (centros digital 2025) ===')\n",
|
||
"print(df_nav_types.to_string(index=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 19,
|
||
"id": "01872457",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"supply_orders — campos posibles canal:\n",
|
||
" marketplace_offer_id\n",
|
||
" tpv_orders_order_id\n",
|
||
" tpv_orders_orderitem_id\n",
|
||
" eci_mk_id\n",
|
||
" eci_sell_price\n",
|
||
" eci_status\n",
|
||
" source_timestamp\n",
|
||
" official_service\n",
|
||
" official_service_from_provider\n",
|
||
"\n",
|
||
"logistic_orders — campos posibles canal:\n",
|
||
" source_timestamp\n",
|
||
"\n",
|
||
"Tablas psql_dcpublic marketplace/tpv/orders:\n",
|
||
" 1565 channels\n",
|
||
" 1534 logistic_orders\n",
|
||
" 2704 ralarsa_orders\n",
|
||
" 1530 supply_orders\n",
|
||
" 2705 tpv_appointment_appointment\n",
|
||
" 1659 tpv_authorization_instanceaccesstoken\n",
|
||
" 1653 tpv_authorization_tpvclock\n",
|
||
" 1654 tpv_authorization_tpvuser\n",
|
||
" 1655 tpv_authorization_tpvuser_centers\n",
|
||
" 1657 tpv_authorization_tpvuser_groups\n",
|
||
" 1858 tpv_authorization_tpvuser_user_permissions\n",
|
||
" 3826 tpv_auto_billing_autobillingrequest\n",
|
||
" 3827 tpv_auto_billing_autobillingrequestlog\n",
|
||
" 1658 tpv_cashreg_cashmovement\n",
|
||
" 1656 tpv_centers_shift\n",
|
||
" 1888 tpv_commissions_commission\n",
|
||
" 1886 tpv_commissions_commissionconfiguration\n",
|
||
" 1884 tpv_commissions_productcommissionreduction\n",
|
||
" 1527 tpv_companies\n",
|
||
" 2560 tpv_customer_history_action\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Buscar campos de canal/marketplace en supply_orders y logistic_orders\n",
|
||
"so_fields = [f['name'] for f in tbl_meta['supply_orders']['fields']]\n",
|
||
"lo_fields = [f['name'] for f in tbl_meta['logistic_orders']['fields']]\n",
|
||
"print('supply_orders — campos posibles canal:')\n",
|
||
"for f in so_fields:\n",
|
||
" if any(k in f.lower() for k in ['channel','canal','market','source','platform','origin','referer','tpv','official','amazon','eci']):\n",
|
||
" print(f' {f}')\n",
|
||
"print()\n",
|
||
"print('logistic_orders — campos posibles canal:')\n",
|
||
"for f in lo_fields:\n",
|
||
" if any(k in f.lower() for k in ['channel','canal','market','source','platform','origin','referer','tpv']):\n",
|
||
" print(f' {f}')\n",
|
||
"print()\n",
|
||
"# Tablas complementarias: tpv_orders, marketplace\n",
|
||
"mkt_tables = [t for t in db6['tables'] if t.get('schema') == 'psql_dcpublic' and \n",
|
||
" any(k in t['name'].lower() for k in ['tpv','marketplace','channel','offer','order'])]\n",
|
||
"print(f'Tablas psql_dcpublic marketplace/tpv/orders:')\n",
|
||
"for t in mkt_tables[:20]:\n",
|
||
" print(f\" {t['id']:5} {t['name']}\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 20,
|
||
"id": "1c302199",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== channels fields ===\n",
|
||
" id [Integer]\n",
|
||
" company_id [Integer]\n",
|
||
" name [Text]\n",
|
||
" slug [Text]\n",
|
||
" domain [Text]\n",
|
||
" status [Integer]\n",
|
||
" nav_id [Integer]\n",
|
||
" channel_type [Integer]\n",
|
||
" external [Boolean]\n",
|
||
" starting_date [Date]\n",
|
||
" ending_date [Date]\n",
|
||
" created_at [DateTimeWithLocalTZ]\n",
|
||
" updated_at [DateTimeWithLocalTZ]\n",
|
||
" mirakl_code [Text]\n",
|
||
" tag_config [JSON]\n",
|
||
" datastream_metadata [Dictionary]\n",
|
||
" source_timestamp [Integer]\n",
|
||
" uuid [Text]\n",
|
||
" digital_center_id [Integer]\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== channels data ===\n",
|
||
" id company_id name slug domain status nav_id channel_type external starting_date ending_date created_at updated_at mirakl_code tag_config datastream_metadata digital_center_id\n",
|
||
" 1 1 aurgi.com aurgi-com None None None None None None None 2020-05-07T23:57:45.785733+02:00 2023-10-03T17:45:54.377289+02:00 INIT {\"all_included_price_tag\":\"aurgi_all_included_price\",\"brand_tag\":\"aurgi\",\"economic_tag\":\"racing\",\"included_in_set_prices\":\"true\",\"mc2p_tag\":\"aurgi\",\"nav_name_tag\":\"Prestashop\",\"product_price_tag\":\"aurgi_price\",\"promo_price_tag\":\"aurgi\",\"sale_code_tag\":\"471\",\"sale_price_slug_tag\":\"aurgi-com\",\"set_other_prices_tags\":[\"aurgi_price_to_sort\",\"aurgi_all_included_price\"],\"set_simple_prices_tags\":[\"aurgi_price\"],\"slug_normal_tag\":\"aurgi\",\"slug_other_tag\":\"aurgi_tag\",\"stock_tag\":\"aurgi\"} {'uuid': '8cefc67c-1aa9-4447-a53c-91cb00000000', 'source_timestamp': 1696802998957} None\n",
|
||
" 2 2 motortown.es motortown-es None None None None None None None 2020-05-07T23:57:45.801079+02:00 2026-03-17T14:03:40.388276+01:00 {\"all_included_price_tag\":\"mt_all_included_price\",\"brand_tag\":\"motortown\",\"economic_tag\":\"economico\",\"included_in_set_prices\":\"true\",\"mc2p_tag\":\"mt\",\"nav_name_tag\":\"WebMT\",\"product_price_tag\":\"mt_price\",\"promo_price_tag\":\"motortown\",\"sale_code_tag\":\"472\",\"sale_price_slug_tag\":\"motortown-es\",\"set_other_prices_tags\":[\"motortown_price_to_sort\",\"mt_all_included_price\"],\"set_simple_prices_tags\":[\"mt_price\"],\"slug_normal_tag\":\"motortown\",\"slug_other_tag\":\"motortown_tag\",\"stock_tag\":\"motortown\",\"tpv_index\":\"TPV_MT_IDX\"} {'uuid': 'a947ab61-5cb5-416f-89ab-a8d700010010', 'source_timestamp': 1773752620397} None\n",
|
||
" 3 3 autingo.es autingo-es None None None None None None None 2020-05-07T23:57:45.818754+02:00 2024-11-06T11:34:08.699318+01:00 {\"bank_account_tag\":true,\"exclude_for_delete\":true,\"mc2p_tag\":\"autingo\",\"product_price_tag\":\"autingo_price\",\"sale_price_slug_tag\":\"autingo-es\",\"set_other_prices_tags\":[],\"set_simple_prices_tags\":[\"autingo_price\"],\"slug_normal_tag\":\"autingo\",\"stock_tag\":\"autingo\"} {'uuid': '5de8da99-c6da-497a-b088-5bd710100111', 'source_timestamp': 1730889248706} None\n",
|
||
" 4 1 Centros Aurgi centros-aurgi None None None None None None None 2020-12-15T15:39:36.135323+01:00 2025-03-25T15:54:20.349252+01:00 {\"all_included_price_tag\":\"aurgi_all_included_price\",\"brand_tag\":\"aurgi\",\"economic_tag\":\"racing\",\"included_in_set_prices\":\"true\",\"mc2p_tag\":\"aurgi\",\"nav_name_tag\":\"Producto Aurgi\",\"order_associate_tag\":\"true\",\"product_price_tag\":\"aurgi_price\",\"promo_price_tag\":\"aurgi\",\"sale_price_slug_tag\":\"aurgi-com\",\"set_other_prices_tags\":[\"aurgi_price_to_sort\",\"aurgi_all_included_price\"],\"set_simple_prices_tags\":[\"aurgi_price\"],\"slug_normal_tag\":\"aurgi\",\"slug_other_tag\":\"aurgi_tag\",\"stock_tag\":\"aurgi\"} {'uuid': 'b549922b-283c-4d12-82bb-632911110011', 'source_timestamp': 1742914460367} None\n",
|
||
" 5 2 Centros MT centros-mt None None None None None None None 2020-12-15T15:39:36.161249+01:00 2025-07-08T18:25:56.829215+02:00 {\"all_included_price_tag\":\"mt_all_included_price\",\"brand_tag\":\"motortown\",\"economic_tag\":\"economico\",\"included_in_set_prices\":\"true\",\"mc2p_tag\":\"mt\",\"nav_name_tag\":\"Producto MT\",\"product_price_tag\":\"mt_price\",\"promo_price_tag\":\"motortown\",\"sale_price_slug_tag\":\"motortown-es\",\"set_other_prices_tags\":[\"motortown_price_to_sort\",\"mt_all_included_price\"],\"set_simple_prices_tags\":[\"mt_price\"],\"slug_normal_tag\":\"motortown\",\"slug_other_tag\":\"motortown_tag\",\"stock_tag\":\"motortown\"} {'uuid': '71c2dcc4-f317-434d-8ca6-bd8311001100', 'source_timestamp': 1751991956843} None\n",
|
||
" 6 5 Eci Marketplace eci-marketplace None None None None None None None 2022-07-29T18:15:53.419166+02:00 2023-11-13T15:41:18.781688+01:00 NaN {\"product_price_tag\":\"eci_internal_price\",\"slug_normal_tag\":\"aurgi\",\"slug_other_tag\":\"aurgi_tag\"} {'uuid': '0a6cba7f-aea8-4e5e-ac82-3d3811100100', 'source_timestamp': 1699886478784} None\n",
|
||
" 7 5 NaN eci-internal-channel None None None None None None None 2022-11-21T11:40:03.968508+01:00 2023-11-13T15:40:28.875452+01:00 NaN {\"product_price_tag\":\"eci_internal_price\",\"slug_normal_tag\":\"aurgi\",\"slug_other_tag\":\"aurgi_tag\"} {'uuid': '1038881e-1a13-49ed-9aef-f23500110010', 'source_timestamp': 1699886428878} None\n",
|
||
" 8 6 Eci Marketplace eci-marketplace None None None None None None None 2022-11-21T13:15:24.79686+01:00 2023-11-13T15:41:25.976548+01:00 NaN {\"product_price_tag\":\"eci_internal_price\",\"slug_normal_tag\":\"aurgi\",\"slug_other_tag\":\"aurgi_tag\"} {'uuid': 'a72f9e13-0947-4c45-b1cc-170411111110', 'source_timestamp': 1699886485980} None\n",
|
||
" 10 1 Talleres Digitales talleres-digitales None None None None None None None 2023-11-06T12:16:20.072201+01:00 2024-04-22T12:34:27.691303+02:00 {\"all_included_price_tag\":\"digital_garage_all_included_price\",\"brand_tag\":\"aurgi\",\"economic_tag\":\"racing\",\"exclude_for_delete\":true,\"included_in_set_prices\":\"true\",\"mc2p_tag\":\"aurgi\",\"product_price_tag\":\"digital_garage_price\",\"promo_price_tag\":\"aurgi\",\"sale_price_slug_tag\":\"talleres-digitales\",\"set_other_prices_tags\":[],\"set_simple_prices_tags\":[\"digital_garage_price\"],\"slug_normal_tag\":\"aurgi\",\"slug_other_tag\":\"aurgi_tag\",\"stock_tag\":\"aurgi\",\"use_own_channel_automatic_order\":true} {'uuid': 'b4c39f76-a4df-4653-af17-6a4511111110', 'source_timestamp': 1713782067697} None\n",
|
||
" 11 1 Amazon amazon None None None None None None None 2023-11-20T15:37:28.276689+01:00 2024-03-12T16:36:34.826712+01:00 {\"exclude_for_delete\":true,\"payment_tag\":\"AMAZON\",\"product_price_tag\":\"amazon-price\",\"set_other_prices_tags\":[],\"set_simple_prices_tags\":[\"amazon-price\"],\"shopping_feed_tag\":66,\"skip_mk_offer_tag\":\"true\",\"slug_normal_tag\":\"aurgi\",\"slug_other_tag\":\"aurgi_tag\"} {'uuid': '4e0886a4-7296-45c3-8c76-016001001011', 'source_timestamp': 1710257794831} None\n",
|
||
" 12 2 canarias centros-canarias None None None None None None None 2023-11-23T15:17:28.028796+01:00 2023-11-23T15:17:39.873841+01:00 NaN {\"all_included_price_tag\":\"canarias_all_included_price\",\"brand_tag\":\"motortown\",\"economic_tag\":\"economico\",\"encargo_tax_tag\":1.07,\"included_in_set_prices\":\"true\",\"mc2p_tag\":\"mt\",\"nav_name_tag\":\"Producto MT Canarias\",\"product_price_tag\":\"canarias_price\",\"promo_price_tag\":\"motortown\",\"sale_code_tag\":\"478\",\"sale_price_slug_tag\":\"centros-canarias\",\"set_other_prices_tags\":[\"canarias_all_included_price\"],\"set_simple_prices_tags\":[\"canarias_price\"],\"slug_normal_tag\":\"motortown\",\"slug_other_tag\":\"motortown_tag\",\"stock_tag\":\"motortown\"} {'uuid': 'f099ca13-2277-416c-b5ca-a6c510010011', 'source_timestamp': 1700749059881} None\n",
|
||
" 13 1 Miravia miravia None None None None None None None 2023-11-30T18:04:57.917942+01:00 2024-03-12T16:37:29.88589+01:00 {\"exclude_for_delete\":true,\"payment_tag\":\"MIRAVIA\",\"product_price_tag\":\"miravia-price\",\"set_other_prices_tags\":[],\"set_simple_prices_tags\":[\"miravia-price\"],\"shopping_feed_tag\":46619,\"skip_mk_offer_tag\":\"true\",\"slug_normal_tag\":\"aurgi\",\"slug_other_tag\":\"aurgi_tag\"} {'uuid': '8a5ced8f-1e5c-49f8-a882-7be511101011', 'source_timestamp': 1710257849890} None\n",
|
||
" 14 1 Aliexpress aliexpress None None None None None None None 2024-07-29T16:31:25.337518+02:00 2024-07-29T17:18:24.465507+02:00 {\"exclude_for_delete\":true,\"payment_tag\":\"AE\",\"product_price_tag\":\"aliexpress-price\",\"set_other_prices_tags\":[],\"set_simple_prices_tags\":[\"aliexpress-price\"],\"shopping_feed_tag\":34210,\"skip_mk_offer_tag\":\"true\",\"slug_normal_tag\":\"aurgi\",\"slug_other_tag\":\"aurgi_tag\"} {'uuid': 'dbc99c04-6620-4528-92f4-4bdd00000010', 'source_timestamp': 1722266304470} None\n",
|
||
" 15 1 Tiktok Shop tiktok-shop None None None None None None None 2024-08-30T11:16:50.636998+02:00 2025-11-06T17:25:06.687578+01:00 {\"exclude_for_delete\":true,\"payment_tag\":\"TIKTOK\",\"product_price_tag\":\"tiktok_price\",\"set_other_prices_tags\":[],\"set_simple_prices_tags\":[\"tiktok_price\"],\"shopping_feed_tag\":51756,\"skip_mk_offer_tag\":\"true\",\"slug_normal_tag\":\"aurgi\",\"slug_other_tag\":\"aurgi_tag\"} {'uuid': '8836f949-5be3-426f-85c0-595111100011', 'source_timestamp': 1762446306694} None\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Ver tabla channels y buscar tpv_orders para entender canal\n",
|
||
"channels_meta = client.request(\"GET\", \"/api/table/1565/query_metadata\")\n",
|
||
"print('=== channels fields ===')\n",
|
||
"for f in channels_meta['fields']:\n",
|
||
" print(f\" {f['name']:40} [{f['base_type'].replace('type/','')}]\")\n",
|
||
"print()\n",
|
||
"\n",
|
||
"# Lista de todos los canales\n",
|
||
"df_ch = run_sql('SELECT * FROM `psql_dcpublic.channels` ORDER BY id')\n",
|
||
"print('=== channels data ===')\n",
|
||
"print(df_ch.to_string(index=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 21,
|
||
"id": "886663ef",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== card 7750: SO↔NAV — Desglose por canal ===\n",
|
||
"type: None, database: 6\n"
|
||
]
|
||
},
|
||
{
|
||
"ename": "NameError",
|
||
"evalue": "name 'json' is not defined",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
|
||
"\u001b[31mNameError\u001b[39m Traceback (most recent call last)",
|
||
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[21]\u001b[39m\u001b[32m, line 11\u001b[39m\n\u001b[32m 7\u001b[39m print(f'type: {dq.get(\u001b[33m\"type\"\u001b[39m)}, database: {dq.get(\u001b[33m\"database\"\u001b[39m)}')\n\u001b[32m 8\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m dq.get(\u001b[33m'type'\u001b[39m) == \u001b[33m'native'\u001b[39m:\n\u001b[32m 9\u001b[39m print(dq[\u001b[33m'native'\u001b[39m][\u001b[33m'query'\u001b[39m][:\u001b[32m3000\u001b[39m])\n\u001b[32m 10\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m---> \u001b[39m\u001b[32m11\u001b[39m print(json.dumps(dq.get(\u001b[33m'query'\u001b[39m), indent=\u001b[32m2\u001b[39m)[:\u001b[32m2000\u001b[39m])\n\u001b[32m 12\u001b[39m print()\n",
|
||
"\u001b[31mNameError\u001b[39m: name 'json' is not defined"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Leer la query de la card 7750 del doc 2 (Desglose por canal)\n",
|
||
"# y la 7751 (Revenue semanal web por canal)\n",
|
||
"for cid in [7750, 7751]:\n",
|
||
" c = client.request('GET', f'/api/card/{cid}')\n",
|
||
" dq = c.get('dataset_query') or {}\n",
|
||
" print(f'=== card {cid}: {c[\"name\"]} ===')\n",
|
||
" print(f'type: {dq.get(\"type\")}, database: {dq.get(\"database\")}')\n",
|
||
" if dq.get('type') == 'native':\n",
|
||
" print(dq['native']['query'][:3000])\n",
|
||
" else:\n",
|
||
" print(json.dumps(dq.get('query'), indent=2)[:2000])\n",
|
||
" print()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 22,
|
||
"id": "15f185cb",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== card 7749: SO↔NAV — Evolución mensual por origen ===\n",
|
||
"type: None, database: 6\n",
|
||
"--- MBQL query ---\n",
|
||
"null\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== card 7750: SO↔NAV — Desglose por canal ===\n",
|
||
"type: None, database: 6\n",
|
||
"--- MBQL query ---\n",
|
||
"null\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== card 7751: SO↔NAV — Revenue semanal web por canal ===\n",
|
||
"type: None, database: 6\n",
|
||
"--- MBQL query ---\n",
|
||
"null\n",
|
||
"\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import json as _json\n",
|
||
"# Leer la query de las cards del doc 2 (las 3)\n",
|
||
"for cid in [7749, 7750, 7751]:\n",
|
||
" c = client.request('GET', f'/api/card/{cid}')\n",
|
||
" dq = c.get('dataset_query') or {}\n",
|
||
" print(f'=== card {cid}: {c[\"name\"]} ===')\n",
|
||
" print(f'type: {dq.get(\"type\")}, database: {dq.get(\"database\")}')\n",
|
||
" native = dq.get('native') or {}\n",
|
||
" if native.get('query'):\n",
|
||
" print('--- NATIVE SQL ---')\n",
|
||
" print(native['query'][:3000])\n",
|
||
" else:\n",
|
||
" print('--- MBQL query ---')\n",
|
||
" print(_json.dumps(dq.get('query'), indent=2, default=str)[:2500])\n",
|
||
" print()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 23,
|
||
"id": "103eb0ca",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"keys: ['cache_invalidated_at', 'description', 'archived', 'view_count', 'collection_position', 'source_card_id', 'table_id', 'can_run_adhoc_query', 'result_metadata', 'embedding_type', 'dependency_analysis_version', 'creator', 'initially_published_at', 'can_write', 'card_schema', 'database_id', 'enable_embedding', 'collection_id', 'query_type', 'name', 'last_query_start', 'is_remote_synced', 'dashboard_count', 'document_id', 'last_used_at', 'dashboard', 'type', 'average_query_time', 'creator_id', 'can_restore', 'moderation_reviews', 'updated_at', 'made_public_by_id', 'embedding_params', 'cache_ttl', 'dataset_query', 'id', 'legacy_query', 'parameter_mappings', 'can_manage_db', 'display', 'archived_directly', 'entity_id', 'collection_preview', 'last-edit-info', 'visualization_settings', 'collection', 'metabase_version', 'parameters', 'dashboard_id', 'created_at', 'parameter_usage_count', 'public_uuid', 'can_delete']\n",
|
||
"\n",
|
||
"dataset_query keys: ['lib/type', 'database', 'stages']\n",
|
||
"\n",
|
||
"{\n",
|
||
" \"lib/type\": \"mbql/query\",\n",
|
||
" \"database\": 6,\n",
|
||
" \"stages\": [\n",
|
||
" {\n",
|
||
" \"lib/type\": \"mbql.stage/native\",\n",
|
||
" \"native\": \"\\nWITH supply_full AS (\\n SELECT \\n so.id as supply_order_id,\\n so.service_request_id,\\n so.product_id,\\n so.quantity,\\n so.sale_price,\\n so.purchase_price,\\n so.status as so_status,\\n so.supply_method,\\n so.shipped,\\n so.created_at as so_created_at,\\n CASE \\n WHEN so.service_request_id IS NOT NULL THEN 'Web'\\n WHEN so.tpv_orders_order_id IS NOT NULL THEN 'Centro'\\n ELSE 'Sin origen'\\n END as origen,\\n ch.name as canal_nombre,\\n sr.shipping_method,\\n COALESCE(so.tpv_orders_order_id, pj.order_id, inv_lo.order_id) as order_id,\\n COALESCE(inv_direct.nav_id, inv_precaweb.nav_id, lo.invoice_number) as factura_nav,\\n p.description as producto,\\n COALESCE(SPLIT(ec.h_path, '#')[SAFE_OFFSET(0)], '(sin cat)') as familia_ecom,\\n COALESCE(SPLIT(ec.h_path, '#')[SAFE_OFFSET(1)], '') as subfamilia_ecom,\\n ec.name as ecom_cat_leaf,\\n sih.posting_date as fecha_factura,\\n sih.location_code as centro_nav,\\n sih.payment_method_code as metodo_pago\\n FROM `autingo-159109.psql_dcpublic.supply_orders` so\\n LEFT JOIN `autingo-159109.psql_dcpublic.service_requests` sr ON so.service_request_id = sr.id\\n LEFT JOIN `autingo-159109.psql_dcpublic.channels` ch ON sr.channel_id = ch.id\\n LEFT JOIN `autingo-159109.psql_dcpublic.tpv_precawebs_servicerequestjob` pj\\n ON CAST(so.service_request_id AS STRING) = pj.service_request_id\\n LEFT JOIN `autingo-159109.psql_dcpublic.tpv_orders_invoice` inv_direct\\n ON so.tpv_orders_order_id = inv_direct.order_id\\n LEFT JOIN `autingo-159109.psql_dcpublic.tpv_orders_invoice` inv_precaweb\\n ON pj.order_id = inv_precaweb.order_id AND so.tpv_orders_order_id IS NULL\\n LEFT JOIN `autingo-159109.psql_dcpublic.logistic_orders` lo ON so.logistic_order_id = lo.id\\n LEFT JOIN `autingo-159109.psql_dcpublic.tpv_orders_invoice` inv_lo\\n ON lo.invoice_number = inv_lo.nav_id AND so.tpv_orders_order_id IS NULL AND pj.order_id IS NULL\\n LEFT JOIN `autingo-159109.psql_dcpublic.products` p ON so.product_id = p.id\\n LEFT JOIN `autingo-159109.psql_dcpublic.ecommerce_categories` ec ON p.ecommerce_category_id = ec.id\\n LEFT JOIN `autingo-159109.mssql2022_dbo.anjana_sales_invoice_header` sih \\n ON COALESCE(inv_direct.nav_id, inv_precaweb.nav_id, lo.invoice_number) = sih.no_ \\n AND sih._fivetran_deleted = FALSE\\n WHERE so.created_at >= '2025-01-01'\\n)\\n\\nSELECT \\n COALESCE(canal_nombre, '(centro directo)') as canal,\\n origen,\\n COUNT(DISTINCT supply_order_id) as supply_orders,\\n COUNT(DISTINCT CASE WHEN factura_nav IS NOT NULL THEN supply_order_id END) as con_factura,\\n ROUND(COUNT(DISTINCT CASE WHEN factura_nav IS NOT NULL THEN supply_order_id END) * 100.0 \\n / NULLIF(COUNT(DISTINCT supply_order_id), 0), 1) as pct_trazable,\\n COUNT(DISTINCT order_id) as orders_tpv,\\n ROUND(SUM(sale_price * quantity), 0) as revenue_so,\\n ROUND(SUM(sale_price * quantity) - SUM(purchase_price * quantity), 0) as margen_so,\\n ROUND((SUM(sale_price * quantity) - SUM(purchase_price * quantity)) * 100.0 \\n / NULLIF(SUM(sale_price * quantity), 0), 1) as pct_margen\\nFROM supply_full\\nGROUP BY 1, 2\\nORDER BY supply_orders DESC\\n\"\n",
|
||
" }\n",
|
||
" ]\n",
|
||
"}\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import json as _json\n",
|
||
"c = client.request('GET', '/api/card/7750')\n",
|
||
"# dump todos los keys\n",
|
||
"print('keys:', list(c.keys()))\n",
|
||
"print()\n",
|
||
"print('dataset_query keys:', list(c.get('dataset_query',{}).keys()))\n",
|
||
"print()\n",
|
||
"# Probar version v2 formato stages\n",
|
||
"print(_json.dumps(c.get('dataset_query'), indent=2, default=str)[:4000])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"id": "416349bf",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== VENTA WEB 2025 POR CANAL (Supply Orders → NAV) ===\n",
|
||
" canal supply_orders con_factura facturas_distintas revenue_so revenue_trazable\n",
|
||
" aurgi.com 72843 71219 62651 17,606,179.00 17,016,564.00\n",
|
||
" Amazon 58134 58116 55152 3,243,771.00 3,241,920.00\n",
|
||
" Aliexpress 36994 36974 35398 1,181,809.00 1,181,423.00\n",
|
||
" autingo.es 11398 11358 10553 1,940,942.00 1,936,293.00\n",
|
||
" Miravia 10495 10487 10000 918,512.00 918,112.00\n",
|
||
"Eci Marketplace 1207 1207 1152 91,211.00 91,211.00\n",
|
||
" motortown.es 1150 1031 1355 1,137,556.00 1,034,280.00\n",
|
||
" Tiktok Shop 23 23 19 349.00 349.00\n",
|
||
" Centros Aurgi 7 7 7 426,266.00 426,266.00\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Revenue y conteo facturas por canal (Web solo) — 2025, usando la logica del doc 2\n",
|
||
"sql_canal = '''\n",
|
||
"WITH so_web AS (\n",
|
||
" SELECT\n",
|
||
" so.id,\n",
|
||
" so.service_request_id,\n",
|
||
" so.quantity,\n",
|
||
" so.sale_price,\n",
|
||
" so.created_at,\n",
|
||
" ch.name AS canal,\n",
|
||
" COALESCE(inv_direct.nav_id, inv_precaweb.nav_id, lo.invoice_number) AS factura_nav\n",
|
||
" FROM `autingo-159109.psql_dcpublic.supply_orders` so\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.service_requests` sr ON so.service_request_id = sr.id\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.channels` ch ON sr.channel_id = ch.id\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.tpv_precawebs_servicerequestjob` pj\n",
|
||
" ON CAST(so.service_request_id AS STRING) = pj.service_request_id\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.tpv_orders_invoice` inv_direct\n",
|
||
" ON so.tpv_orders_order_id = inv_direct.order_id\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.tpv_orders_invoice` inv_precaweb\n",
|
||
" ON pj.order_id = inv_precaweb.order_id AND so.tpv_orders_order_id IS NULL\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.logistic_orders` lo ON so.logistic_order_id = lo.id\n",
|
||
" WHERE so.service_request_id IS NOT NULL\n",
|
||
" AND EXTRACT(YEAR FROM so.created_at) = 2025\n",
|
||
")\n",
|
||
"SELECT\n",
|
||
" COALESCE(canal, '(sin canal)') AS canal,\n",
|
||
" COUNT(DISTINCT id) AS supply_orders,\n",
|
||
" COUNT(DISTINCT CASE WHEN factura_nav IS NOT NULL THEN id END) AS con_factura,\n",
|
||
" COUNT(DISTINCT factura_nav) AS facturas_distintas,\n",
|
||
" ROUND(SUM(sale_price * quantity), 0) AS revenue_so,\n",
|
||
" ROUND(SUM(CASE WHEN factura_nav IS NOT NULL THEN sale_price * quantity END), 0) AS revenue_trazable\n",
|
||
"FROM so_web\n",
|
||
"GROUP BY canal\n",
|
||
"ORDER BY supply_orders DESC\n",
|
||
"'''\n",
|
||
"df_canal = run_sql(sql_canal)\n",
|
||
"print('=== VENTA WEB 2025 POR CANAL (Supply Orders → NAV) ===')\n",
|
||
"print(df_canal.to_string(index=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 26,
|
||
"id": "b0e0660c",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== REVENUE POR MES Y CANAL (Supply Orders web 2025) ===\n",
|
||
"canal Aliexpress Amazon Centros Aurgi Eci Marketplace Miravia Tiktok Shop aurgi.com autingo.es motortown.es\n",
|
||
"mes \n",
|
||
"2025-01 68,343.00 166,947.00 0.00 20,871.00 76,124.00 0.00 2,245,281.00 115,703.00 60,239.00\n",
|
||
"2025-02 33,095.00 183,390.00 0.00 6,074.00 60,312.00 0.00 699,809.00 124,178.00 70,430.00\n",
|
||
"2025-03 50,465.00 276,958.00 0.00 6,054.00 80,987.00 0.00 929,023.00 111,122.00 101,507.00\n",
|
||
"2025-04 38,748.00 257,065.00 3,996.00 5,452.00 73,302.00 0.00 863,487.00 86,919.00 97,587.00\n",
|
||
"2025-05 98,737.00 429,018.00 23,148.00 4,016.00 92,269.00 0.00 819,083.00 220,599.00 65,286.00\n",
|
||
"2025-06 140,292.00 563,030.00 0.00 5,074.00 127,968.00 0.00 1,128,153.00 304,014.00 101,676.00\n",
|
||
"2025-07 197,834.00 420,412.00 27,900.00 5,153.00 99,631.00 0.00 2,410,787.00 285,622.00 146,945.00\n",
|
||
"2025-08 217,799.00 248,708.00 0.00 5,319.00 70,978.00 11.00 1,856,374.00 229,094.00 162,288.00\n",
|
||
"2025-09 120,499.00 285,104.00 759.00 4,600.00 98,794.00 157.00 1,097,121.00 144,585.00 91,482.00\n",
|
||
"2025-10 91,763.00 168,277.00 0.00 8,131.00 73,901.00 145.00 947,802.00 139,971.00 67,643.00\n",
|
||
"2025-11 101,533.00 170,078.00 0.00 7,662.00 49,572.00 36.00 940,761.00 75,873.00 74,999.00\n",
|
||
"2025-12 22,701.00 74,784.00 370,463.00 12,806.00 14,673.00 0.00 3,668,497.00 103,262.00 97,473.00\n",
|
||
"\n",
|
||
"=== FACTURAS DISTINTAS POR MES Y CANAL ===\n",
|
||
"canal Aliexpress Amazon Centros Aurgi Eci Marketplace Miravia Tiktok Shop aurgi.com autingo.es motortown.es\n",
|
||
"mes \n",
|
||
"2025-01 2,112.00 3,312.00 0.00 270.00 852.00 0.00 1,941.00 743.00 72.00\n",
|
||
"2025-02 1,415.00 3,517.00 0.00 93.00 794.00 0.00 2,059.00 614.00 73.00\n",
|
||
"2025-03 1,935.00 6,965.00 0.00 84.00 1,072.00 0.00 2,508.00 980.00 91.00\n",
|
||
"2025-04 1,249.00 6,000.00 1.00 60.00 994.00 0.00 2,569.00 691.00 94.00\n",
|
||
"2025-05 3,813.00 8,109.00 1.00 65.00 1,029.00 0.00 3,061.00 968.00 89.00\n",
|
||
"2025-06 3,672.00 8,359.00 0.00 68.00 1,331.00 0.00 4,564.00 1,296.00 186.00\n",
|
||
"2025-07 6,057.00 5,856.00 1.00 62.00 1,097.00 0.00 6,627.00 1,552.00 207.00\n",
|
||
"2025-08 6,219.00 4,781.00 0.00 70.00 801.00 1.00 5,338.00 1,237.00 207.00\n",
|
||
"2025-09 3,974.00 5,359.00 1.00 58.00 867.00 8.00 2,799.00 884.00 97.00\n",
|
||
"2025-10 2,769.00 2,301.00 0.00 77.00 616.00 7.00 2,629.00 864.00 67.00\n",
|
||
"2025-11 2,569.00 2,279.00 0.00 97.00 466.00 3.00 2,177.00 447.00 89.00\n",
|
||
"2025-12 635.00 872.00 3.00 150.00 157.00 0.00 29,681.00 379.00 83.00\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Evolucion mensual 2025 por CANAL para las 3 fuentes en paralelo (solo revenue y facturas)\n",
|
||
"sql_mensual_canal = '''\n",
|
||
"WITH so_web AS (\n",
|
||
" SELECT\n",
|
||
" so.id,\n",
|
||
" FORMAT_DATE('%Y-%m', so.created_at) AS mes,\n",
|
||
" ch.name AS canal,\n",
|
||
" so.sale_price * so.quantity AS revenue,\n",
|
||
" COALESCE(inv_direct.nav_id, inv_precaweb.nav_id, lo.invoice_number) AS factura_nav\n",
|
||
" FROM `autingo-159109.psql_dcpublic.supply_orders` so\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.service_requests` sr ON so.service_request_id = sr.id\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.channels` ch ON sr.channel_id = ch.id\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.tpv_precawebs_servicerequestjob` pj\n",
|
||
" ON CAST(so.service_request_id AS STRING) = pj.service_request_id\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.tpv_orders_invoice` inv_direct\n",
|
||
" ON so.tpv_orders_order_id = inv_direct.order_id\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.tpv_orders_invoice` inv_precaweb\n",
|
||
" ON pj.order_id = inv_precaweb.order_id AND so.tpv_orders_order_id IS NULL\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.logistic_orders` lo ON so.logistic_order_id = lo.id\n",
|
||
" WHERE so.service_request_id IS NOT NULL\n",
|
||
" AND EXTRACT(YEAR FROM so.created_at) = 2025\n",
|
||
")\n",
|
||
"SELECT\n",
|
||
" mes,\n",
|
||
" COALESCE(canal, '(sin canal)') AS canal,\n",
|
||
" COUNT(DISTINCT id) AS supply_orders,\n",
|
||
" COUNT(DISTINCT factura_nav) AS facturas,\n",
|
||
" ROUND(SUM(revenue), 0) AS revenue\n",
|
||
"FROM so_web\n",
|
||
"GROUP BY mes, canal\n",
|
||
"ORDER BY mes, revenue DESC\n",
|
||
"'''\n",
|
||
"df_mensual_canal = run_sql(sql_mensual_canal)\n",
|
||
"\n",
|
||
"# Pivot por canal -> mes\n",
|
||
"pivot_rev = df_mensual_canal.pivot_table(index='mes', columns='canal', values='revenue', aggfunc='sum').fillna(0)\n",
|
||
"pivot_fact = df_mensual_canal.pivot_table(index='mes', columns='canal', values='facturas', aggfunc='sum').fillna(0)\n",
|
||
"\n",
|
||
"print('=== REVENUE POR MES Y CANAL (Supply Orders web 2025) ===')\n",
|
||
"print(pivot_rev.to_string())\n",
|
||
"print()\n",
|
||
"print('=== FACTURAS DISTINTAS POR MES Y CANAL ===')\n",
|
||
"print(pivot_fact.to_string())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "d0617844",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 10. Por qué discrepan las fuentes — explicación y resumen\n",
|
||
"\n",
|
||
"### Totales 2025 reproducidos\n",
|
||
"\n",
|
||
"| Fuente | Revenue | Nº registros | Lógica aplicada |\n",
|
||
"|---|---|---|---|\n",
|
||
"| **Cubo_Ventas_Calculado** (WSWEB, Venta) | **5.879.313 €** | 158.617 líneas | `Dim_NombreDimGlobal2='WSWEB' AND Dim_NombreTipoMov='Venta'` |\n",
|
||
"| **NAV directo** (centros digitales) | **15.872.266 €** | 315.831 líneas / ~295K facturas | `location_code IN ('18','19','405','421','422')` |\n",
|
||
"| **Supply Orders → NAV** (web, por canal) | **26.499.895 €** | 192.251 SOs / 190K con factura | `service_request_id IS NOT NULL` con `sale_price*quantity` |\n",
|
||
"\n",
|
||
"### ¿Por qué 3 cifras tan distintas?\n",
|
||
"\n",
|
||
"Las tres miden **cosas distintas aunque suenen igual**:\n",
|
||
"\n",
|
||
"1. **Cubo (5.88M€) — \"compañía comercial WSWEB\"**\n",
|
||
" - Es un datamart pre-agregado que solo cuenta líneas cuya **dimensión comercial = WSWEB**\n",
|
||
" - Excluye implícitamente devoluciones, ajustes de stock, tickets intraempresa, abonos\n",
|
||
" - Solo tipo_mov = \"Venta\"\n",
|
||
" - Los centros físicos (18/19/405/421/422) aparecen aquí, pero solo por la fracción de su actividad que se imputa a la compañía WSWEB\n",
|
||
"\n",
|
||
"2. **NAV directo (15.87M€) — \"facturación bruta del almacén\"**\n",
|
||
" - Todo lo facturado en los almacenes con location_code digital: ventas a cliente final + tickets intraempresa + facturas de servicios + recargos + ajustes\n",
|
||
" - tipo_de_registro_tpv=4 (ticket TPV) domina con 306K facturas\n",
|
||
" - **2.7× el Cubo** porque incluye todo lo que sale del almacén, no solo la venta online limpia\n",
|
||
"\n",
|
||
"3. **Supply Orders (26.50M€) — \"pedidos web por canal\"**\n",
|
||
" - Todo pedido web (service_request_id ≠ NULL) independientemente del centro que lo facture\n",
|
||
" - **Incluye canales NO digital-center**: Amazon 3.24M€, Aliexpress 1.18M€, Miravia 918K€ → se facturan a centros/compañías distintas que no están en (18/19/405/421/422)\n",
|
||
" - Por eso es mayor que NAV directo\n",
|
||
"\n",
|
||
"### Diciembre tiene anomalías importantes\n",
|
||
"\n",
|
||
"- **aurgi.com diciembre**: 3.67M€ y 29.681 facturas (vs media ~2-3K facturas/mes) → 10× la media\n",
|
||
"- **Aurgi Asociados Gruas (421) diciembre en NAV**: 55.138 facturas por 2.97M€ en UN solo mes (todo el resto del año: ~150 facturas total)\n",
|
||
"- **Centros Aurgi (canal)**: 370K€ concentrado en diciembre\n",
|
||
"\n",
|
||
"Investigar: ¿cierre fiscal? ¿reemisión masiva? ¿cambio lógica canal?\n",
|
||
"\n",
|
||
"### Desglose canal digital 2025\n",
|
||
"\n",
|
||
"| Canal | Supply Orders | Revenue SO | % trazable a NAV |\n",
|
||
"|---|---|---|---|\n",
|
||
"| aurgi.com | 72.843 | 17.6M€ | 97.8% |\n",
|
||
"| Amazon | 58.134 | 3.24M€ | 99.97% |\n",
|
||
"| Aliexpress | 36.994 | 1.18M€ | 99.95% |\n",
|
||
"| autingo.es | 11.398 | 1.94M€ | 99.6% |\n",
|
||
"| Miravia | 10.495 | 918K€ | 99.9% |\n",
|
||
"| motortown.es | 1.150 | 1.14M€ | 89.7% |\n",
|
||
"| Eci Marketplace | 1.207 | 91K€ | 100% |\n",
|
||
"| Centros Aurgi | 7 | 426K€ | 100% |\n",
|
||
"| Tiktok Shop | 23 | 349€ | 100% |\n",
|
||
"\n",
|
||
"### Recomendación de uso\n",
|
||
"\n",
|
||
"- **Cubo_Ventas_Calculado (WSWEB, Venta)** → reporting financiero interno \"venta online\" en sentido estricto\n",
|
||
"- **NAV directo (location_code digital)** → auditoría contable, cierre fiscal\n",
|
||
"- **Supply Orders por canal** → operativa web, KPIs por marketplace, conciliación ventas-envíos"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 27,
|
||
"id": "7f2ef633",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== TOP 20 productos aurgi.com DICIEMBRE 2025 ===\n",
|
||
" producto supply_orders unidades revenue precio_medio\n",
|
||
" BALIZA V16 GEOLOC Mirovi RET 27706 41,293.00 2,803,090.00 52.09\n",
|
||
" REVISION PLUS TURISMO 61 61.00 10,020.00 164.26\n",
|
||
" CUB EP 235/60 R18 107V K125A V 6 20.00 9,845.00 453.52\n",
|
||
" REVISION TODO INCLUIDO TURISMO 45 45.00 9,221.00 204.91\n",
|
||
" CUB 205/55 R16 91V K135 VEN 10 28.00 9,103.00 288.60\n",
|
||
" CUB 205/55 R16 91V SECURADRIVE 22 54.00 9,080.00 149.98\n",
|
||
" CUB EN 205/50 R17 93W K135 VEN 9 23.00 7,577.00 280.47\n",
|
||
" CUB 205/55 R16 91V TUR6 8 22.00 7,154.00 294.15\n",
|
||
" CUB 225/45 R17 91Y K135 VEN 10 26.00 7,045.00 236.31\n",
|
||
" CUB 225/45 R17 94Y POWERGY 11 26.00 6,939.00 242.31\n",
|
||
"Baliza V16 IoT Alert Wise con geolocalización MIROVI Compatible DGT 3.0 y Conectividad telefónica tech 75 107.00 6,723.00 51.29\n",
|
||
" CUB 205/55 R16 91V RP062 20 44.00 6,235.00 132.68\n",
|
||
" CUB EN 235/55 R19 105W SCO AS 3 10.00 6,233.00 572.90\n",
|
||
" CAMBIO DE ACEITE MO Y FILTRO ACEITE TURISMO 84 84.00 5,921.00 70.49\n",
|
||
" REVISION TODO INCLUIDO 4X4/FU/MONOV 24 24.00 5,668.00 236.18\n",
|
||
" CUB EP 195/65 R15 91V 4E H750 6 18.00 5,206.00 258.40\n",
|
||
" CUB EP 195/55 R16 91V 4E CEAT 8 24.00 5,206.00 204.42\n",
|
||
" CUB EP 215/50 R18 92W PWRGY 2 8.00 5,139.00 642.39\n",
|
||
" CUB EP 225/50 R18 99Y K127 VEN 4 12.00 5,119.00 383.91\n",
|
||
" REVISION AHORRO TURISMO 41 41.00 4,977.00 121.38\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Hipotesis: pico aurgi.com diciembre 2025 = balizas V16 (ley obligatoria ene 2026)\n",
|
||
"# Ver top productos vendidos en aurgi.com en diciembre 2025\n",
|
||
"sql_dic_top = '''\n",
|
||
"SELECT\n",
|
||
" p.description AS producto,\n",
|
||
" COUNT(DISTINCT so.id) AS supply_orders,\n",
|
||
" SUM(so.quantity) AS unidades,\n",
|
||
" ROUND(SUM(so.sale_price * so.quantity), 0) AS revenue,\n",
|
||
" ROUND(AVG(so.sale_price), 2) AS precio_medio\n",
|
||
"FROM `autingo-159109.psql_dcpublic.supply_orders` so\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.service_requests` sr ON so.service_request_id = sr.id\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.channels` ch ON sr.channel_id = ch.id\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.products` p ON so.product_id = p.id\n",
|
||
"WHERE so.service_request_id IS NOT NULL\n",
|
||
" AND ch.name = 'aurgi.com'\n",
|
||
" AND EXTRACT(YEAR FROM so.created_at) = 2025\n",
|
||
" AND EXTRACT(MONTH FROM so.created_at) = 12\n",
|
||
"GROUP BY p.description\n",
|
||
"ORDER BY revenue DESC\n",
|
||
"LIMIT 20\n",
|
||
"'''\n",
|
||
"df_dic_top = run_sql(sql_dic_top)\n",
|
||
"print('=== TOP 20 productos aurgi.com DICIEMBRE 2025 ===')\n",
|
||
"print(df_dic_top.to_string(index=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 28,
|
||
"id": "f3e4daf7",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== Pico aurgi.com DIC 2025: balizas vs resto ===\n",
|
||
" categoria supply_orders unidades revenue\n",
|
||
" Balizas V16 27793 41,414.00 2,810,591.00\n",
|
||
"Resto productos 2865 4,191.00 705,417.00\n",
|
||
"\n",
|
||
"Balizas V16 = 79.9% del revenue aurgi.com diciembre 2025\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Desglose del pico diciembre: balizas vs resto\n",
|
||
"sql_dic_balizas = '''\n",
|
||
"SELECT\n",
|
||
" CASE \n",
|
||
" WHEN UPPER(p.description) LIKE '%BALIZA%' OR UPPER(p.description) LIKE '%V16%' THEN 'Balizas V16'\n",
|
||
" ELSE 'Resto productos'\n",
|
||
" END AS categoria,\n",
|
||
" COUNT(DISTINCT so.id) AS supply_orders,\n",
|
||
" SUM(so.quantity) AS unidades,\n",
|
||
" ROUND(SUM(so.sale_price * so.quantity), 0) AS revenue\n",
|
||
"FROM `autingo-159109.psql_dcpublic.supply_orders` so\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.service_requests` sr ON so.service_request_id = sr.id\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.channels` ch ON sr.channel_id = ch.id\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.products` p ON so.product_id = p.id\n",
|
||
"WHERE so.service_request_id IS NOT NULL\n",
|
||
" AND ch.name = 'aurgi.com'\n",
|
||
" AND EXTRACT(YEAR FROM so.created_at) = 2025\n",
|
||
" AND EXTRACT(MONTH FROM so.created_at) = 12\n",
|
||
"GROUP BY categoria\n",
|
||
"ORDER BY revenue DESC\n",
|
||
"'''\n",
|
||
"df_bal = run_sql(sql_dic_balizas)\n",
|
||
"print('=== Pico aurgi.com DIC 2025: balizas vs resto ===')\n",
|
||
"print(df_bal.to_string(index=False))\n",
|
||
"total = df_bal['revenue'].sum()\n",
|
||
"pct_bal = df_bal.loc[df_bal['categoria']=='Balizas V16','revenue'].iloc[0] / total * 100\n",
|
||
"print(f'\\nBalizas V16 = {pct_bal:.1f}% del revenue aurgi.com diciembre 2025')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 29,
|
||
"id": "e4d54fc1",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== 2025 venta web: por canal y destino de cumplimentacion ===\n",
|
||
" canal destino supply_orders facturas revenue locations_nav_distintos\n",
|
||
" Aliexpress 1) Centro digital (web puro) 36994 35398 1,181,809.00 4\n",
|
||
" Amazon 1) Centro digital (web puro) 58122 55149 3,242,247.00 4\n",
|
||
" Amazon 3) Sin centro asignado 12 5 1,524.00 1\n",
|
||
" Centros Aurgi 1) Centro digital (web puro) 7 7 426,266.00 3\n",
|
||
"Eci Marketplace 1) Centro digital (web puro) 1207 1152 91,211.00 4\n",
|
||
" Miravia 1) Centro digital (web puro) 10490 10000 918,172.00 4\n",
|
||
" Miravia 3) Sin centro asignado 5 0 340.00 0\n",
|
||
" Tiktok Shop 1) Centro digital (web puro) 23 19 349.00 3\n",
|
||
" aurgi.com 1) Centro digital (web puro) 37144 35349 5,024,463.00 58\n",
|
||
" aurgi.com 2) Centro fisico (C&C/envio tienda) 35671 30210 12,579,111.00 66\n",
|
||
" aurgi.com 3) Sin centro asignado 28 15 2,605.00 7\n",
|
||
" autingo.es 1) Centro digital (web puro) 11398 10553 1,940,942.00 4\n",
|
||
" motortown.es 2) Centro fisico (C&C/envio tienda) 1150 1355 1,137,556.00 48\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Trazabilidad completa: SO -> NAV para venta que va a CENTRO (C&C + envio tienda)\n",
|
||
"# Vamos a desglosar 2025 por \"destino final\"\n",
|
||
"\n",
|
||
"sql_destino = '''\n",
|
||
"WITH so_web AS (\n",
|
||
" SELECT\n",
|
||
" so.id,\n",
|
||
" so.service_request_id,\n",
|
||
" so.quantity,\n",
|
||
" so.sale_price,\n",
|
||
" so.created_at,\n",
|
||
" ch.name AS canal,\n",
|
||
" ce.name AS centro_fisico,\n",
|
||
" ce.nav_id AS nav_id_centro,\n",
|
||
" ce.is_digital,\n",
|
||
" sr.shipping_method AS shipping_method_sr,\n",
|
||
" lo.center_id AS logistic_center_id,\n",
|
||
" COALESCE(inv_direct.nav_id, inv_precaweb.nav_id, lo.invoice_number) AS factura_nav,\n",
|
||
" sih.location_code AS nav_location\n",
|
||
" FROM `autingo-159109.psql_dcpublic.supply_orders` so\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.service_requests` sr ON so.service_request_id = sr.id\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.channels` ch ON sr.channel_id = ch.id\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.logistic_orders` lo ON so.logistic_order_id = lo.id\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.centers` ce ON lo.center_id = ce.id\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.tpv_precawebs_servicerequestjob` pj\n",
|
||
" ON CAST(so.service_request_id AS STRING) = pj.service_request_id\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.tpv_orders_invoice` inv_direct\n",
|
||
" ON so.tpv_orders_order_id = inv_direct.order_id\n",
|
||
" LEFT JOIN `autingo-159109.psql_dcpublic.tpv_orders_invoice` inv_precaweb\n",
|
||
" ON pj.order_id = inv_precaweb.order_id AND so.tpv_orders_order_id IS NULL\n",
|
||
" LEFT JOIN `autingo-159109.mssql2022_dbo.anjana_sales_invoice_header` sih\n",
|
||
" ON COALESCE(inv_direct.nav_id, inv_precaweb.nav_id, lo.invoice_number) = sih.no_\n",
|
||
" AND sih._fivetran_deleted = FALSE\n",
|
||
" WHERE so.service_request_id IS NOT NULL\n",
|
||
" AND EXTRACT(YEAR FROM so.created_at) = 2025\n",
|
||
")\n",
|
||
"SELECT\n",
|
||
" canal,\n",
|
||
" CASE\n",
|
||
" WHEN is_digital = TRUE THEN '1) Centro digital (web puro)'\n",
|
||
" WHEN is_digital = FALSE THEN '2) Centro fisico (C&C/envio tienda)'\n",
|
||
" WHEN centro_fisico IS NULL THEN '3) Sin centro asignado'\n",
|
||
" ELSE '4) Otro'\n",
|
||
" END AS destino,\n",
|
||
" COUNT(DISTINCT id) AS supply_orders,\n",
|
||
" COUNT(DISTINCT factura_nav) AS facturas,\n",
|
||
" ROUND(SUM(sale_price * quantity), 0) AS revenue,\n",
|
||
" COUNT(DISTINCT nav_location) AS locations_nav_distintos\n",
|
||
"FROM so_web\n",
|
||
"GROUP BY canal, destino\n",
|
||
"ORDER BY canal, destino\n",
|
||
"'''\n",
|
||
"df_dest = run_sql(sql_destino)\n",
|
||
"print('=== 2025 venta web: por canal y destino de cumplimentacion ===')\n",
|
||
"print(df_dest.to_string(index=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "0061c6c1",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 11. Verificación balizas V16 — CONFIRMADO\n",
|
||
"\n",
|
||
"El pico aurgi.com diciembre (3.67M€, 29.681 facturas) es **80% balizas V16**:\n",
|
||
"\n",
|
||
"| Categoría | Supply Orders | Unidades | Revenue |\n",
|
||
"|---|---:|---:|---:|\n",
|
||
"| **Balizas V16** | 27.793 | 41.414 | **2.810.591 €** |\n",
|
||
"| Resto productos | 2.865 | 4.191 | 705.417 € |\n",
|
||
"\n",
|
||
"Todo por la **ley DGT de balizas V16 obligatoria desde 1 enero 2026** (sustituye triángulos de emergencia). Producto principal: **BALIZA V16 GEOLOC Mirovi RET** (52€ unidad, 41.293 unidades en un mes).\n",
|
||
"\n",
|
||
"## 12. La arquitectura real — dónde sacar cada dato\n",
|
||
"\n",
|
||
"### 12.1 Hallazgo clave: la venta web no va toda a centros digitales\n",
|
||
"\n",
|
||
"Cuando se desglosa por **destino de cumplimentación** (via `supply_orders.logistic_order_id → logistic_orders.center_id → centers`):\n",
|
||
"\n",
|
||
"| Canal | A centro digital (web puro) | A centro físico (C&C/envío tienda) | Sin centro |\n",
|
||
"|---|---:|---:|---:|\n",
|
||
"| aurgi.com | 5.02M€ (29%) | **12.58M€ (71%)** | 3K€ |\n",
|
||
"| motortown.es | 0 | 1.14M€ (100%) | 0 |\n",
|
||
"| Amazon | 3.24M€ (100%) | 0 | 2K€ |\n",
|
||
"| Aliexpress | 1.18M€ (100%) | 0 | 0 |\n",
|
||
"| autingo.es | 1.94M€ (100%) | 0 | 0 |\n",
|
||
"| Miravia | 918K€ (100%) | 0 | 0 |\n",
|
||
"\n",
|
||
"**Por eso NAV filtrado por location digital (5.02+3.24+1.18+1.94+0.92+…=13.5M€) queda lejos del total de supply_orders web (26.5M€)**: falta todo el C&C de aurgi.com que se factura en 66 locations físicas distintas.\n",
|
||
"\n",
|
||
"### 12.2 Tabla de verdad según pregunta\n",
|
||
"\n",
|
||
"| Pregunta de negocio | Fuente canónica | Filtro clave |\n",
|
||
"|---|---|---|\n",
|
||
"| ¿Cuánto vendí por canal online? | `psql_dcpublic.supply_orders` + join con `channels` | `service_request_id IS NOT NULL` |\n",
|
||
"| ¿Qué facturó fiscalmente cada almacén? | `mssql2022_dbo.anjana_sales_invoice_header/line` | `location_code` específico |\n",
|
||
"| ¿Cuál es el KPI comercial \"venta online\" estricto? | `anjana_bi_datamart.Cubo_Ventas_Calculado` | `Dim_NombreDimGlobal2='WSWEB' AND Dim_NombreTipoMov='Venta'` |\n",
|
||
"| ¿Un pedido web llegó a facturarse? | Cadena `supply_orders → tpv_orders_invoice → NAV` | factura_nav IS NOT NULL |\n",
|
||
"| ¿A qué tienda fue el C&C? | `logistic_orders.center_id → centers.nav_id` | `is_digital=FALSE` |\n",
|
||
"\n",
|
||
"### 12.3 Propuesta: vista canónica `v_venta_web_unificada`\n",
|
||
"\n",
|
||
"Una **view materializada en BigQuery** que consolide todo:\n",
|
||
"\n",
|
||
"```sql\n",
|
||
"CREATE OR REPLACE VIEW `autingo-159109.anjana_bi_datamart.v_venta_web_unificada` AS\n",
|
||
"SELECT\n",
|
||
" so.id AS supply_order_id,\n",
|
||
" so.created_at AS fecha_pedido,\n",
|
||
" ch.name AS canal,\n",
|
||
" ch.company_id AS company_id,\n",
|
||
" so.product_id,\n",
|
||
" p.description AS producto,\n",
|
||
" so.quantity,\n",
|
||
" so.sale_price,\n",
|
||
" so.sale_price * so.quantity AS revenue,\n",
|
||
" so.purchase_price,\n",
|
||
" (so.sale_price - so.purchase_price) * so.quantity AS margen,\n",
|
||
" ce.id AS centro_id,\n",
|
||
" ce.name AS centro_nombre,\n",
|
||
" ce.nav_id AS centro_nav_id,\n",
|
||
" ce.is_digital AS centro_es_digital,\n",
|
||
" CASE\n",
|
||
" WHEN ce.is_digital THEN 'entrega_web'\n",
|
||
" WHEN ce.is_digital = FALSE THEN 'click_and_collect'\n",
|
||
" ELSE 'sin_centro'\n",
|
||
" END AS modo_cumplimentacion,\n",
|
||
" sr.shipping_method AS shipping_method,\n",
|
||
" COALESCE(inv_direct.nav_id, inv_precaweb.nav_id, lo.invoice_number) AS factura_nav,\n",
|
||
" sih.posting_date AS fecha_factura_nav,\n",
|
||
" sih.location_code AS nav_location_code,\n",
|
||
" sih.amount_including_vat AS importe_factura_nav\n",
|
||
"FROM `autingo-159109.psql_dcpublic.supply_orders` so\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.service_requests` sr ON so.service_request_id = sr.id\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.channels` ch ON sr.channel_id = ch.id\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.logistic_orders` lo ON so.logistic_order_id = lo.id\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.centers` ce ON lo.center_id = ce.id\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.products` p ON so.product_id = p.id\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.tpv_precawebs_servicerequestjob` pj\n",
|
||
" ON CAST(so.service_request_id AS STRING) = pj.service_request_id\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.tpv_orders_invoice` inv_direct\n",
|
||
" ON so.tpv_orders_order_id = inv_direct.order_id\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.tpv_orders_invoice` inv_precaweb\n",
|
||
" ON pj.order_id = inv_precaweb.order_id AND so.tpv_orders_order_id IS NULL\n",
|
||
"LEFT JOIN `autingo-159109.mssql2022_dbo.anjana_sales_invoice_header` sih\n",
|
||
" ON COALESCE(inv_direct.nav_id, inv_precaweb.nav_id, lo.invoice_number) = sih.no_\n",
|
||
" AND sih._fivetran_deleted = FALSE\n",
|
||
"WHERE so.service_request_id IS NOT NULL\n",
|
||
"```\n",
|
||
"\n",
|
||
"Con esta vista, un analista puede responder en **una sola query**:\n",
|
||
"- Ventas por canal, mes, producto\n",
|
||
"- Qué % se factura realmente (trazabilidad)\n",
|
||
"- Qué % se cumple en centro físico vs digital\n",
|
||
"- Cuánto factura cada centro NAV por canal web\n",
|
||
"\n",
|
||
"### 12.4 Alternativa en Metabase (sin tocar BigQuery)\n",
|
||
"\n",
|
||
"Si no se puede crear la view en BQ, se puede crear como **Modelo** en Metabase (type='model'):\n",
|
||
"\n",
|
||
"1. Nueva card tipo model con la SQL de arriba\n",
|
||
"2. Guardar en colección \"Models / Venta Web\"\n",
|
||
"3. Cualquier card/dashboard nuevo puede usar `source-table: card__<id>` y tiene todas las columnas disponibles en modo point-and-click\n",
|
||
"\n",
|
||
"### 12.5 Seguimiento cuando la venta va a centro\n",
|
||
"\n",
|
||
"La trazabilidad completa es:\n",
|
||
"\n",
|
||
"```\n",
|
||
"supply_orders.service_request_id\n",
|
||
" ↓\n",
|
||
"service_requests.channel_id (qué canal)\n",
|
||
" ↓\n",
|
||
"supply_orders.logistic_order_id\n",
|
||
" ↓\n",
|
||
"logistic_orders.center_id (qué centro cumple)\n",
|
||
" ↓\n",
|
||
"centers.nav_id (código NAV del centro)\n",
|
||
" ↓\n",
|
||
"anjana_sales_invoice_header.location_code (factura NAV final)\n",
|
||
"```\n",
|
||
"\n",
|
||
"Clave: **el centro que cumplimenta NO tiene por qué ser digital**. Para el 71% de aurgi.com (C&C), el flujo es: pedido web → tienda física → factura en NAV con location del centro físico.\n",
|
||
"\n",
|
||
"### 12.6 Recomendación operativa\n",
|
||
"\n",
|
||
"1. **Materializar la view** `v_venta_web_unificada` en BigQuery → fuente única para todos los reportes de venta web\n",
|
||
"2. **Crear un Model en Metabase** basado en esa view → democratizar acceso sin SQL\n",
|
||
"3. **Dashboard nuevo** con 3 tabs: \"Por canal\", \"Por destino (web/centro)\", \"Trazabilidad factura NAV\"\n",
|
||
"4. **Deprecar filtros engañosos** del dashboard 734 que usan solo location_code (pierden el 71% del C&C)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 30,
|
||
"id": "878d8a19",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Tablas tpv_* en psql_dcpublic: 61\n",
|
||
"\n",
|
||
" 1653 tpv_authorization_tpvclock\n",
|
||
" 1654 tpv_authorization_tpvuser\n",
|
||
" 1655 tpv_authorization_tpvuser_centers\n",
|
||
" 1657 tpv_authorization_tpvuser_groups\n",
|
||
" 1858 tpv_authorization_tpvuser_user_permissions\n",
|
||
" 1656 tpv_centers_shift\n",
|
||
" 4637 tpv_insurance_insuranceclaim_orders\n",
|
||
" 1532 tpv_orders_advancepayment\n",
|
||
" 1593 tpv_orders_advancepayment_returns_documents\n",
|
||
" 1531 tpv_orders_cashoperation\n",
|
||
" 1575 tpv_orders_collective\n",
|
||
" 1581 tpv_orders_collective_companies\n",
|
||
" 1554 tpv_orders_comparative\n",
|
||
" 1561 tpv_orders_exchange\n",
|
||
" 1585 tpv_orders_exchange_new_items\n",
|
||
" 1544 tpv_orders_exchange_to_exchange\n",
|
||
" 1549 tpv_orders_gtrequest\n",
|
||
" 1528 tpv_orders_invoice\n",
|
||
" 1559 tpv_orders_itemreplace\n",
|
||
" 1572 tpv_orders_note\n",
|
||
" 1548 tpv_orders_order\n",
|
||
" 1555 tpv_orders_orderitem\n",
|
||
" 1579 tpv_orders_orderitem_promos\n",
|
||
" 1558 tpv_orders_payment\n",
|
||
" 1526 tpv_orders_paymentauthorization\n",
|
||
" 1564 tpv_orders_paymentreturnrelation\n",
|
||
" 1547 tpv_orders_quote\n",
|
||
" 1578 tpv_orders_return\n",
|
||
" 1541 tpv_orders_returnadvancepaymentdocument\n",
|
||
" 1536 tpv_orders_returnreason\n",
|
||
" 1571 tpv_orders_return_to_exchange\n",
|
||
" 1587 tpv_orders_transactiondeleteuser\n",
|
||
" 1567 tpv_otrs_otr_orders\n",
|
||
" 1543 tpv_payment_types\n",
|
||
" 1782 tpv_payment_types_centers\n",
|
||
" 1591 tpv_payment_types_companies\n",
|
||
" 1552 tpv_terminals\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Buscar todas las tablas tpv_* en psql_dcpublic\n",
|
||
"tpv_tables = [t for t in db6['tables'] if t.get('schema') == 'psql_dcpublic' and t['name'].startswith('tpv_')]\n",
|
||
"print(f'Tablas tpv_* en psql_dcpublic: {len(tpv_tables)}')\n",
|
||
"print()\n",
|
||
"# Filtrar las mas relevantes para venta/terminal\n",
|
||
"relevant = [t for t in tpv_tables if any(k in t['name'].lower() for k in \n",
|
||
" ['order', 'sale', 'ticket', 'terminal', 'device', 'pos', 'idx', 'clock', 'user', 'center', 'sessio', 'pay', 'checkout', 'invoice', 'receipt'])]\n",
|
||
"for t in relevant[:40]:\n",
|
||
" print(f\" {t['id']:5} {t['name']}\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 32,
|
||
"id": "c371fefb",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== tpv_terminals (id 1552) — 20 cols ===\n",
|
||
" id [Integer]\n",
|
||
" name [Text]\n",
|
||
" created_at [DateTimeWithLocalTZ]\n",
|
||
" updated_at [DateTimeWithLocalTZ]\n",
|
||
" center_id [Integer]\n",
|
||
" inventory_terminal [Boolean]\n",
|
||
" status_open [Boolean]\n",
|
||
" status_shift [Integer]\n",
|
||
" status_description [Text]\n",
|
||
" status_open_amount [Decimal]\n",
|
||
" terminal_type_id [Integer]\n",
|
||
" visibility [Integer]\n",
|
||
" current_shift_id [Integer]\n",
|
||
" pending_products [Boolean]\n",
|
||
" datastream_metadata [Dictionary]\n",
|
||
" source_timestamp [Integer]\n",
|
||
" uuid [Text]\n",
|
||
" second_screen_active [Boolean]\n",
|
||
" customer_interaction_lock [Boolean]\n",
|
||
" assistant_screen_online [Boolean]\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== tpv_orders_order (id 1548) — 58 cols ===\n",
|
||
" id [Integer]\n",
|
||
" created_at [DateTimeWithLocalTZ]\n",
|
||
" updated_at [DateTimeWithLocalTZ]\n",
|
||
" customer_id [Integer]\n",
|
||
" total_cost [Decimal]\n",
|
||
" total_cost_currency [Text]\n",
|
||
" calculate_payload [JSON]\n",
|
||
" terminal_id [Integer]\n",
|
||
" vehicle_id [Integer]\n",
|
||
" shift [Integer]\n",
|
||
" has_exchange [Boolean]\n",
|
||
" parent_id [Integer]\n",
|
||
" is_precaweb [Boolean]\n",
|
||
" calculate_uuid [Text]\n",
|
||
" has_service_request [Boolean]\n",
|
||
" collective_id [Integer]\n",
|
||
" execution_time [Integer]\n",
|
||
" shift_model_id [Integer]\n",
|
||
" allow_all_returns [Boolean]\n",
|
||
" return_custom_times [JSON]\n",
|
||
" payment_methods_override [JSON]\n",
|
||
" referenced_user_id [Integer]\n",
|
||
" allow_return_with_open_otr [Boolean]\n",
|
||
" driver_id [Integer]\n",
|
||
" owner_id [Integer]\n",
|
||
" allow_returns_in_cash [Boolean]\n",
|
||
" gt_request_id [Integer]\n",
|
||
" requires_payment_authorization [Boolean]\n",
|
||
" can_be_returned_special_customer [Boolean]\n",
|
||
" tax_applied [Float]\n",
|
||
" datastream_metadata [Dictionary]\n",
|
||
" source_timestamp [Integer]\n",
|
||
" uuid [Text]\n",
|
||
" last_promo_line_number [Integer]\n",
|
||
" last_item_line_number [Integer]\n",
|
||
" last_update_in_nav [DateTimeWithLocalTZ]\n",
|
||
" voucher_code [Text]\n",
|
||
" kilometers [Integer]\n",
|
||
" autogenerated_from_otr_id [Integer]\n",
|
||
" reason [Text]\n",
|
||
" appointment_id [Integer]\n",
|
||
" stop_ralarsa_sync [Boolean]\n",
|
||
" skip_provider_requires_delivery_confirmation [Boolean]\n",
|
||
" insurance_claim_id [Integer]\n",
|
||
" need_insurance_validation [Boolean]\n",
|
||
" validate_sol_pieces_when_closing_otr [Boolean]\n",
|
||
" accident_type_description [Text]\n",
|
||
" operation_type [Text]\n",
|
||
" insurance_policy_id [Integer]\n",
|
||
" damage_type_description [Text]\n",
|
||
" recorder_car_renounce_id [Integer]\n",
|
||
" allowed_car_revision [Boolean]\n",
|
||
" date_car_renounce [DateTimeWithLocalTZ]\n",
|
||
" last_incident_id [Integer]\n",
|
||
" show_budget_vs_appraisal_comparison [Boolean]\n",
|
||
" can_link_appraissal [Boolean]\n",
|
||
" source [Text]\n",
|
||
" external_id [Text]\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== tpv_orders_invoice (id 1528) — 24 cols ===\n",
|
||
" id [Integer]\n",
|
||
" nav_id [Text]\n",
|
||
" created_at [DateTimeWithLocalTZ]\n",
|
||
" updated_at [DateTimeWithLocalTZ]\n",
|
||
" order_id [Integer]\n",
|
||
" created_by_id [Integer]\n",
|
||
" terminal_id [Integer]\n",
|
||
" invoice_path [Text]\n",
|
||
" ticket_path [Text]\n",
|
||
" status [Integer]\n",
|
||
" clear_one_path [Text]\n",
|
||
" customer_copy [JSON]\n",
|
||
" vehicle_copy [JSON]\n",
|
||
" show_vehicle [Boolean]\n",
|
||
" profit [Decimal]\n",
|
||
" profit_currency [Text]\n",
|
||
" delivery_note [Text]\n",
|
||
" datastream_metadata [Dictionary]\n",
|
||
" source_timestamp [Integer]\n",
|
||
" uuid [Text]\n",
|
||
" adjusted_profit [Decimal]\n",
|
||
" adjusted_profit_currency [Text]\n",
|
||
" registered_in_sol [Boolean]\n",
|
||
" from_standard_billing_flow [Boolean]\n",
|
||
"\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Inspeccionar tpv_terminals, tpv_orders_order, tpv_orders_invoice\n",
|
||
"for tid, label in [(1552, 'tpv_terminals'), (1548, 'tpv_orders_order'), (1528, 'tpv_orders_invoice')]:\n",
|
||
" m = client.request(\"GET\", f\"/api/table/{tid}/query_metadata\")\n",
|
||
" print(f\"=== {label} (id {tid}) — {len(m['fields'])} cols ===\")\n",
|
||
" for f in m['fields']:\n",
|
||
" print(f\" {f['name']:40} [{f['base_type'].replace('type/','')}]\")\n",
|
||
" print()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 33,
|
||
"id": "56384579",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Terminales totales: 2000\n",
|
||
"\n",
|
||
"--- Distribucion terminal_type_id ---\n",
|
||
"terminal_type_id\n",
|
||
"3 764\n",
|
||
"17 534\n",
|
||
"9 444\n",
|
||
"5 62\n",
|
||
"10 53\n",
|
||
"8 52\n",
|
||
"11 52\n",
|
||
"15 16\n",
|
||
"1 10\n",
|
||
"14 5\n",
|
||
"12 3\n",
|
||
"4 2\n",
|
||
"16 2\n",
|
||
"6 1\n",
|
||
"\n",
|
||
"--- Terminales en centros DIGITALES (32) ---\n",
|
||
" terminal_id terminal_name terminal_type_id center_id centro centro_nav_id centro_es_digital\n",
|
||
" 701 18CAJA01 3 160 Aurgi Web 18 True\n",
|
||
" 702 18CAJA02 3 160 Aurgi Web 18 True\n",
|
||
" 703 18CAJA03 3 160 Aurgi Web 18 True\n",
|
||
" 704 18CAJA04 3 160 Aurgi Web 18 True\n",
|
||
" 705 18OFICINA01 3 160 Aurgi Web 18 True\n",
|
||
" 706 18TALLER01 3 160 Aurgi Web 18 True\n",
|
||
" 707 CAJA_WEB 3 160 Aurgi Web 18 True\n",
|
||
" 708 FICHAJE 3 160 Aurgi Web 18 True\n",
|
||
" 1121 CCAL 3 160 Aurgi Web 18 True\n",
|
||
" 1070 19CAJA01 9 161 MT Web 19 True\n",
|
||
" 1071 19CAJA02 3 161 MT Web 19 True\n",
|
||
" 1072 19CAJA03 3 161 MT Web 19 True\n",
|
||
" 1073 19CAJA04 3 161 MT Web 19 True\n",
|
||
" 1074 19OFICINA01 3 161 MT Web 19 True\n",
|
||
" 1075 19TALLER01 3 161 MT Web 19 True\n",
|
||
" 1076 CAJA_WEB 6 161 MT Web 19 True\n",
|
||
" 1077 CCAL 3 161 MT Web 19 True\n",
|
||
" 1078 FICHAJE 3 161 MT Web 19 True\n",
|
||
" 3016 405CAJA01 3 167 Autingo 405 True\n",
|
||
" 3017 405CAJA02 3 167 Autingo 405 True\n",
|
||
" 3018 405CAJA03 3 167 Autingo 405 True\n",
|
||
" 3019 405CAJA04 3 167 Autingo 405 True\n",
|
||
" 3020 405OFICINA01 3 167 Autingo 405 True\n",
|
||
" 3021 405TALLER01 3 167 Autingo 405 True\n",
|
||
" 3022 CAJA_WEB 3 167 Autingo 405 True\n",
|
||
" 3023 CCAL 3 167 Autingo 405 True\n",
|
||
" 3024 FICHAJE 3 167 Autingo 405 True\n",
|
||
" 6033 CCAL 14 167 Autingo 405 True\n",
|
||
" 6039 CCAL 14 167 Autingo 405 True\n",
|
||
" 6040 CCAL 14 167 Autingo 405 True\n",
|
||
" 6041 CCAL 14 167 Autingo 405 True\n",
|
||
" 6334 CCAL 14 167 Autingo 405 True\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# 1. Inventario de terminales con nombre, centro, tipo\n",
|
||
"sql_terms = '''\n",
|
||
"SELECT\n",
|
||
" t.id AS terminal_id,\n",
|
||
" t.name AS terminal_name,\n",
|
||
" t.terminal_type_id,\n",
|
||
" t.center_id,\n",
|
||
" c.name AS centro,\n",
|
||
" c.nav_id AS centro_nav_id,\n",
|
||
" c.is_digital AS centro_es_digital\n",
|
||
"FROM `autingo-159109.psql_dcpublic.tpv_terminals` t\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.centers` c ON t.center_id = c.id\n",
|
||
"ORDER BY t.center_id, t.id\n",
|
||
"'''\n",
|
||
"df_terms = run_sql(sql_terms)\n",
|
||
"print(f'Terminales totales: {len(df_terms)}')\n",
|
||
"print()\n",
|
||
"# Distribucion por tipo\n",
|
||
"print('--- Distribucion terminal_type_id ---')\n",
|
||
"print(df_terms['terminal_type_id'].value_counts().to_string())\n",
|
||
"print()\n",
|
||
"# Terminales en centros digitales\n",
|
||
"dig = df_terms[df_terms['centro_es_digital'] == True]\n",
|
||
"print(f'--- Terminales en centros DIGITALES ({len(dig)}) ---')\n",
|
||
"print(dig.to_string(index=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 34,
|
||
"id": "d5e4a942",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== Orders 2025 en centros DIGITALES por terminal y flag is_precaweb / has_service_request ===\n",
|
||
"terminal_name centro centro_es_digital is_precaweb has_service_request orders total_cost_sum\n",
|
||
" 422CAJA01 Aurgi Asociados True False False 5 834936\n",
|
||
" CAJA_WEB Aurgi Asociados True True False 3 1282\n",
|
||
" CAJA_WEB Aurgi Asociados Gruas True True False 27696 1442752\n",
|
||
" 18CAJA01 Aurgi Web True False False 2 143\n",
|
||
" CAJA_WEB Aurgi Web True True False 112805 4571118\n",
|
||
" CAJA_WEB Autingo True True False 11959 1239345\n",
|
||
" 19CAJA01 MT Web True False False 6 620\n",
|
||
" CAJA_WEB MT Web True True False 1161 86088\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Cross-check: para cada tpv_orders_order en 2025, agrupar por terminal_name + is_precaweb + has_service_request\n",
|
||
"sql_term_verify = '''\n",
|
||
"SELECT\n",
|
||
" t.name AS terminal_name,\n",
|
||
" c.name AS centro,\n",
|
||
" c.is_digital AS centro_es_digital,\n",
|
||
" o.is_precaweb,\n",
|
||
" o.has_service_request,\n",
|
||
" COUNT(DISTINCT o.id) AS orders,\n",
|
||
" ROUND(SUM(o.total_cost), 0) AS total_cost_sum\n",
|
||
"FROM `autingo-159109.psql_dcpublic.tpv_orders_order` o\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.tpv_terminals` t ON o.terminal_id = t.id\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.centers` c ON t.center_id = c.id\n",
|
||
"WHERE EXTRACT(YEAR FROM o.created_at) = 2025\n",
|
||
" AND c.is_digital = TRUE\n",
|
||
"GROUP BY terminal_name, centro, centro_es_digital, is_precaweb, has_service_request\n",
|
||
"ORDER BY centro, terminal_name, is_precaweb\n",
|
||
"'''\n",
|
||
"df_tv = run_sql(sql_term_verify)\n",
|
||
"print('=== Orders 2025 en centros DIGITALES por terminal y flag is_precaweb / has_service_request ===')\n",
|
||
"print(df_tv.to_string(index=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 35,
|
||
"id": "ce97f39a",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"ename": "HTTPStatusError",
|
||
"evalue": "Client error '400 Bad Request' for url 'https://reports.autingo.es/api/dataset'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/400",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
|
||
"\u001b[31mHTTPStatusError\u001b[39m Traceback (most recent call last)",
|
||
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[35]\u001b[39m\u001b[32m, line 20\u001b[39m\n\u001b[32m 16\u001b[39m AND (t.name LIKE \u001b[33m'%WEB%'\u001b[39m OR t.name LIKE \u001b[33m'%CCAL%'\u001b[39m OR t.name = \u001b[33m'CAJA_WEB'\u001b[39m)\n\u001b[32m 17\u001b[39m GROUP BY terminal_name\n\u001b[32m 18\u001b[39m ORDER BY orders DESC\n\u001b[32m 19\u001b[39m '''\n\u001b[32m---> \u001b[39m\u001b[32m20\u001b[39m df_fis = run_sql(sql_fisicos)\n\u001b[32m 21\u001b[39m print(\u001b[33m'=== Terminales WEB/CCAL en centros FISICOS 2025 ==='\u001b[39m)\n\u001b[32m 22\u001b[39m print(df_fis.to_string(index=\u001b[38;5;28;01mFalse\u001b[39;00m))\n\u001b[32m 23\u001b[39m print()\n",
|
||
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 20\u001b[39m, in \u001b[36mrun_sql\u001b[39m\u001b[34m(sql, db_id)\u001b[39m\n\u001b[32m 18\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m run_sql(sql: str, db_id: int = DB_BIGQUERY) -> pd.DataFrame:\n\u001b[32m 19\u001b[39m \u001b[33m\"\"\"Ejecuta SQL contra Metabase y retorna DataFrame.\"\"\"\u001b[39m\n\u001b[32m---> \u001b[39m\u001b[32m20\u001b[39m res = metabase_execute_query(client, db_id, sql)\n\u001b[32m 21\u001b[39m cols = [c[\u001b[33m'display_name'\u001b[39m] \u001b[38;5;28;01mor\u001b[39;00m c[\u001b[33m'name'\u001b[39m] \u001b[38;5;28;01mfor\u001b[39;00m c \u001b[38;5;28;01min\u001b[39;00m res[\u001b[33m'data'\u001b[39m][\u001b[33m'cols'\u001b[39m]]\n\u001b[32m 22\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m pd.DataFrame(res[\u001b[33m'data'\u001b[39m][\u001b[33m'rows'\u001b[39m], columns=cols)\n",
|
||
"\u001b[36mFile \u001b[39m\u001b[32m~/fn_registry/python/functions/metabase/cards.py:227\u001b[39m, in \u001b[36mmetabase_execute_query\u001b[39m\u001b[34m(client, database_id, sql, max_results)\u001b[39m\n\u001b[32m 222\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m max_results > \u001b[32m0\u001b[39m:\n\u001b[32m 223\u001b[39m body[\u001b[33m\"\u001b[39m\u001b[33mconstraints\u001b[39m\u001b[33m\"\u001b[39m] = {\n\u001b[32m 224\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mmax-results\u001b[39m\u001b[33m\"\u001b[39m: max_results,\n\u001b[32m 225\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mmax-results-bare-rows\u001b[39m\u001b[33m\"\u001b[39m: max_results,\n\u001b[32m 226\u001b[39m }\n\u001b[32m--> \u001b[39m\u001b[32m227\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mclient\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mPOST\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43m/api/dataset\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mjson\u001b[49m\u001b[43m=\u001b[49m\u001b[43mbody\u001b[49m\u001b[43m)\u001b[49m\n",
|
||
"\u001b[36mFile \u001b[39m\u001b[32m~/fn_registry/python/functions/metabase/client.py:45\u001b[39m, in \u001b[36mMetabaseClient.request\u001b[39m\u001b[34m(self, method, path, **kwargs)\u001b[39m\n\u001b[32m 31\u001b[39m \u001b[38;5;250m\u001b[39m\u001b[33;03m\"\"\"Ejecuta una peticion HTTP contra la API de Metabase.\u001b[39;00m\n\u001b[32m 32\u001b[39m \n\u001b[32m 33\u001b[39m \u001b[33;03mArgs:\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 42\u001b[39m \u001b[33;03m httpx.HTTPStatusError: Si el status code no es 2xx.\u001b[39;00m\n\u001b[32m 43\u001b[39m \u001b[33;03m\"\"\"\u001b[39;00m\n\u001b[32m 44\u001b[39m resp = \u001b[38;5;28mself\u001b[39m._http.request(method, path, **kwargs)\n\u001b[32m---> \u001b[39m\u001b[32m45\u001b[39m \u001b[43mresp\u001b[49m\u001b[43m.\u001b[49m\u001b[43mraise_for_status\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 46\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m resp.content:\n\u001b[32m 47\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n",
|
||
"\u001b[36mFile \u001b[39m\u001b[32m~/fn_registry/projects/aurgi/analysis/venta_web/.venv/lib/python3.13/site-packages/httpx/_models.py:829\u001b[39m, in \u001b[36mResponse.raise_for_status\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m 827\u001b[39m error_type = error_types.get(status_class, \u001b[33m\"\u001b[39m\u001b[33mInvalid status code\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m 828\u001b[39m message = message.format(\u001b[38;5;28mself\u001b[39m, error_type=error_type)\n\u001b[32m--> \u001b[39m\u001b[32m829\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m HTTPStatusError(message, request=request, response=\u001b[38;5;28mself\u001b[39m)\n",
|
||
"\u001b[31mHTTPStatusError\u001b[39m: Client error '400 Bad Request' for url 'https://reports.autingo.es/api/dataset'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/400"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Y ahora los centros FISICOS (no digitales) — buscar terminales CCAL / CAJA_WEB ahi\n",
|
||
"# para ver venta web cumplida en tienda\n",
|
||
"sql_fisicos = '''\n",
|
||
"SELECT\n",
|
||
" t.name AS terminal_name,\n",
|
||
" COUNT(DISTINCT o.id) AS orders,\n",
|
||
" COUNT(DISTINCT o.id) FILTER (WHERE o.is_precaweb) AS orders_precaweb,\n",
|
||
" COUNT(DISTINCT o.id) FILTER (WHERE o.has_service_request) AS orders_con_service_req,\n",
|
||
" ROUND(SUM(o.total_cost), 0) AS total_cost,\n",
|
||
" ROUND(SUM(CASE WHEN o.is_precaweb THEN o.total_cost END), 0) AS total_cost_precaweb\n",
|
||
"FROM `autingo-159109.psql_dcpublic.tpv_orders_order` o\n",
|
||
"JOIN `autingo-159109.psql_dcpublic.tpv_terminals` t ON o.terminal_id = t.id\n",
|
||
"JOIN `autingo-159109.psql_dcpublic.centers` c ON t.center_id = c.id\n",
|
||
"WHERE EXTRACT(YEAR FROM o.created_at) = 2025\n",
|
||
" AND c.is_digital = FALSE\n",
|
||
" AND (t.name LIKE '%WEB%' OR t.name LIKE '%CCAL%' OR t.name = 'CAJA_WEB')\n",
|
||
"GROUP BY terminal_name\n",
|
||
"ORDER BY orders DESC\n",
|
||
"'''\n",
|
||
"df_fis = run_sql(sql_fisicos)\n",
|
||
"print('=== Terminales WEB/CCAL en centros FISICOS 2025 ===')\n",
|
||
"print(df_fis.to_string(index=False))\n",
|
||
"print()\n",
|
||
"\n",
|
||
"# Y ver conteo por nombre terminal (top) en centros fisicos con is_precaweb=TRUE\n",
|
||
"sql_fis2 = '''\n",
|
||
"SELECT\n",
|
||
" t.name AS terminal_name,\n",
|
||
" COUNT(DISTINCT o.id) AS orders_web_in_centro,\n",
|
||
" ROUND(SUM(o.total_cost), 0) AS revenue\n",
|
||
"FROM `autingo-159109.psql_dcpublic.tpv_orders_order` o\n",
|
||
"JOIN `autingo-159109.psql_dcpublic.tpv_terminals` t ON o.terminal_id = t.id\n",
|
||
"JOIN `autingo-159109.psql_dcpublic.centers` c ON t.center_id = c.id\n",
|
||
"WHERE EXTRACT(YEAR FROM o.created_at) = 2025\n",
|
||
" AND c.is_digital = FALSE\n",
|
||
" AND o.is_precaweb = TRUE\n",
|
||
"GROUP BY terminal_name\n",
|
||
"ORDER BY orders_web_in_centro DESC\n",
|
||
"LIMIT 20\n",
|
||
"'''\n",
|
||
"df_fis2 = run_sql(sql_fis2)\n",
|
||
"print('=== TOP terminales con is_precaweb=TRUE en centros FISICOS 2025 ===')\n",
|
||
"print(df_fis2.to_string(index=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 36,
|
||
"id": "1adaf1b0",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== TOP terminales en centros FISICOS con is_precaweb>0 (2025) ===\n",
|
||
" terminal_id terminal_name terminal_type_id centro centro_nav_id orders orders_precaweb orders_con_sr revenue revenue_precaweb\n",
|
||
" 263 CAJA_WEB 3 Vaguada 89 3122 1126 0 418512 199638\n",
|
||
" 252 CAJA_WEB 3 San Sebastian 23 1982 961 0 283161 170123\n",
|
||
" 205 CAJA_WEB 3 Villalba 54 7036 866 0 753962 140903\n",
|
||
" 199 CAJA_WEB 3 Vallecas 40 6833 770 0 580134 124238\n",
|
||
" 185 CAJA_WEB 3 Leganes 21 7674 716 0 866044 114946\n",
|
||
" 55 CAJA_WEB 3 Malaga 26 2742 703 0 308018 112471\n",
|
||
" 90 CAJA_WEB 3 Majadahonda 85 1832 700 0 229677 126809\n",
|
||
" 134 CAJA_WEB 3 Emilio Muñoz 75 2375 671 0 288075 108933\n",
|
||
" 337 CAJA_WEB 3 Alcorcon 61 7462 652 0 846504 101293\n",
|
||
" 72 CAJA_WEB 3 Store 28 3793 608 0 453970 94475\n",
|
||
" 12 CAJA_WEB 3 Islazul 167 1995 589 0 249061 95465\n",
|
||
" 107 CAJA_WEB 3 Sant Cugat 156 2531 568 0 250190 97797\n",
|
||
" 84 CAJA_WEB 3 San Fernando 22 8029 561 0 725251 91731\n",
|
||
" 279 CAJA_WEB 3 Granada 38 2030 519 0 220857 83086\n",
|
||
" 357 CAJA_WEB 3 San Juan 63 5737 511 0 655167 82093\n",
|
||
" 219 CAJA_WEB 3 Cornella 55 5877 499 0 609250 80754\n",
|
||
" 350 CAJA_WEB 3 Las Rozas 25 6054 493 0 593887 95445\n",
|
||
" 96 CAJA_WEB 3 Avda. Toreros 76 1338 492 0 171564 87708\n",
|
||
" 171 CAJA_WEB 3 Almeria 46 3020 478 0 252919 74703\n",
|
||
" 324 CAJA_WEB 3 Barbera 29 3007 477 0 269678 76220\n",
|
||
" 65 CAJA_WEB 3 Mataro 36 3776 475 0 404397 73240\n",
|
||
" 148 CAJA_WEB 3 Mostoles 58 1606 447 0 207006 83856\n",
|
||
" 165 CAJA_WEB 3 Valdemoro 59 1876 436 0 245426 71580\n",
|
||
" 314 CAJA_WEB 3 Granollers 169 2117 396 0 195765 64192\n",
|
||
" 144 CAJA_WEB 3 Cornella 2 90 1343 386 0 178499 68037\n",
|
||
" 386 CAJA_WEB 3 La Red 27 2648 366 0 297999 58170\n",
|
||
" 192 CAJA_WEB 3 Gta. Cadiz 45 2309 363 0 270676 54017\n",
|
||
" 47 CAJA_WEB 3 Cordoba 43 5254 353 0 548276 58900\n",
|
||
" 399 CAJA_WEB 3 Rivas 53 938 340 0 109333 59602\n",
|
||
" 153 CAJA_WEB 3 Fuengirola 88 1453 314 0 141843 55727\n",
|
||
" 140 CAJA_WEB 3 Gava 95 1863 313 0 226120 48879\n",
|
||
" 299 CAJA_WEB 3 Velez Malaga 86 2480 310 0 273057 54281\n",
|
||
" 362 CAJA_WEB 3 Zaragoza 168 842 310 0 115717 55645\n",
|
||
" 224 CAJA_WEB 3 Sabadell 74 1794 305 0 217652 54001\n",
|
||
" 76 CAJA_WEB 3 Sant Boi 37 1011 291 0 139085 50410\n",
|
||
" 235 CAJA_WEB 3 Alcala Henares 56 2604 284 0 241717 55727\n",
|
||
" 128 CAJA_WEB 3 Pinto 24 967 267 0 126676 43069\n",
|
||
" 60 CAJA_WEB 3 Aluche 154 1587 265 0 151584 41967\n",
|
||
" 284 CAJA_WEB 3 Olias del Rey 78 846 251 0 97988 45618\n",
|
||
" 23 CAJA_WEB 3 Huelva 166 1230 249 0 124801 49376\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Sin asumir nombres: top terminales por orders is_precaweb=TRUE en CENTROS FISICOS 2025\n",
|
||
"# (syntax BigQuery: COUNTIF / SUM(IF(...)))\n",
|
||
"sql_fis = '''\n",
|
||
"SELECT\n",
|
||
" t.id AS terminal_id,\n",
|
||
" t.name AS terminal_name,\n",
|
||
" t.terminal_type_id,\n",
|
||
" c.name AS centro,\n",
|
||
" c.nav_id AS centro_nav_id,\n",
|
||
" COUNT(DISTINCT o.id) AS orders,\n",
|
||
" COUNTIF(o.is_precaweb) AS orders_precaweb,\n",
|
||
" COUNTIF(o.has_service_request) AS orders_con_sr,\n",
|
||
" ROUND(SUM(o.total_cost), 0) AS revenue,\n",
|
||
" ROUND(SUM(IF(o.is_precaweb, o.total_cost, 0)), 0) AS revenue_precaweb\n",
|
||
"FROM `autingo-159109.psql_dcpublic.tpv_orders_order` o\n",
|
||
"JOIN `autingo-159109.psql_dcpublic.tpv_terminals` t ON o.terminal_id = t.id\n",
|
||
"JOIN `autingo-159109.psql_dcpublic.centers` c ON t.center_id = c.id\n",
|
||
"WHERE EXTRACT(YEAR FROM o.created_at) = 2025\n",
|
||
" AND c.is_digital = FALSE\n",
|
||
"GROUP BY terminal_id, terminal_name, terminal_type_id, centro, centro_nav_id\n",
|
||
"HAVING COUNTIF(o.is_precaweb) > 0\n",
|
||
"ORDER BY orders_precaweb DESC\n",
|
||
"LIMIT 40\n",
|
||
"'''\n",
|
||
"df_fis = run_sql(sql_fis)\n",
|
||
"print('=== TOP terminales en centros FISICOS con is_precaweb>0 (2025) ===')\n",
|
||
"print(df_fis.to_string(index=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 37,
|
||
"id": "f1f1595a",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== NOMBRES UNICOS DE TERMINAL + orders 2025 ===\n",
|
||
"terminal_name num_terminales orders_2025 precaweb service_req\n",
|
||
" CAJA_WEB 162 320493 177531 0\n",
|
||
" CCAL 213 241416 0 0\n",
|
||
" 55CAJA01 1 36579 0 0\n",
|
||
" 169CAJA02 1 28675 0 0\n",
|
||
" 58CAJA01 1 27506 0 0\n",
|
||
" 167CAJA02 1 27312 0 0\n",
|
||
" 75CAJA02 1 26657 0 0\n",
|
||
" 61CAJA02 1 25467 0 0\n",
|
||
" 36CAJA03 1 24685 0 0\n",
|
||
" 29CAJA02 1 24288 0 0\n",
|
||
" 21CAJA02 1 24210 0 0\n",
|
||
" 54CAJA02 1 23543 0 0\n",
|
||
" 43CAJA03 1 23437 0 0\n",
|
||
" 54CAJA03 1 22989 0 0\n",
|
||
" 57CAJA01 1 22854 0 0\n",
|
||
" 38CAJA03 1 22824 0 0\n",
|
||
" 45CAJA01 1 22640 0 0\n",
|
||
" 28CAJA03 1 22563 0 0\n",
|
||
" 28CAJA04 1 22251 0 0\n",
|
||
" 24CAJA02 1 20507 0 0\n",
|
||
" 46CAJA01 1 20398 0 0\n",
|
||
" 86CAJA01 1 20344 0 0\n",
|
||
" 62CAJA01 1 20103 0 0\n",
|
||
" 23CAJA01 1 20053 0 0\n",
|
||
" 76CAJA01 1 20021 0 0\n",
|
||
" 56CAJA02 1 19980 0 0\n",
|
||
" 164CAJA02 1 19838 0 0\n",
|
||
" 21CAJA03 1 19502 0 0\n",
|
||
" 156CAJA02 1 19203 0 0\n",
|
||
" 63CAJA04 1 19086 0 0\n",
|
||
" 27CAJA02 1 19036 0 0\n",
|
||
" 190CAJA01 1 19000 0 0\n",
|
||
" 26CAJA03 1 18998 0 0\n",
|
||
" 85CAJA01 1 18918 0 0\n",
|
||
" 74CAJA02 1 18783 0 0\n",
|
||
" 40CAJA02 1 18733 0 0\n",
|
||
" 26CAJA04 1 18683 0 0\n",
|
||
" 77CAJA02 1 18332 0 0\n",
|
||
" 95CAJA01 1 17910 0 0\n",
|
||
" 86CAJA02 1 17751 0 0\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\n",
|
||
"=== Distribucion de tpv_orders_order.source 2025 ===\n",
|
||
"source orders precaweb service_req revenue\n",
|
||
"(null) 2493702 177531 0 366408864\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Nombres unicos de terminales + tipos + el campo `source` de tpv_orders_order\n",
|
||
"# 1. Nombres distintos de terminales (top 30 por orders 2025)\n",
|
||
"sql_term_names = '''\n",
|
||
"SELECT\n",
|
||
" t.name AS terminal_name,\n",
|
||
" COUNT(DISTINCT t.id) AS num_terminales,\n",
|
||
" COUNT(DISTINCT o.id) AS orders_2025,\n",
|
||
" COUNTIF(o.is_precaweb) AS precaweb,\n",
|
||
" COUNTIF(o.has_service_request) AS service_req\n",
|
||
"FROM `autingo-159109.psql_dcpublic.tpv_terminals` t\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.tpv_orders_order` o\n",
|
||
" ON o.terminal_id = t.id AND EXTRACT(YEAR FROM o.created_at) = 2025\n",
|
||
"GROUP BY terminal_name\n",
|
||
"ORDER BY orders_2025 DESC NULLS LAST\n",
|
||
"LIMIT 40\n",
|
||
"'''\n",
|
||
"df_tn = run_sql(sql_term_names)\n",
|
||
"print('=== NOMBRES UNICOS DE TERMINAL + orders 2025 ===')\n",
|
||
"print(df_tn.to_string(index=False))\n",
|
||
"\n",
|
||
"# 2. Campo `source` de tpv_orders_order\n",
|
||
"sql_source = '''\n",
|
||
"SELECT\n",
|
||
" COALESCE(o.source, '(null)') AS source,\n",
|
||
" COUNT(DISTINCT o.id) AS orders,\n",
|
||
" COUNTIF(o.is_precaweb) AS precaweb,\n",
|
||
" COUNTIF(o.has_service_request) AS service_req,\n",
|
||
" ROUND(SUM(o.total_cost), 0) AS revenue\n",
|
||
"FROM `autingo-159109.psql_dcpublic.tpv_orders_order` o\n",
|
||
"WHERE EXTRACT(YEAR FROM o.created_at) = 2025\n",
|
||
"GROUP BY source\n",
|
||
"ORDER BY orders DESC\n",
|
||
"'''\n",
|
||
"df_src = run_sql(sql_source)\n",
|
||
"print()\n",
|
||
"print('=== Distribucion de tpv_orders_order.source 2025 ===')\n",
|
||
"print(df_src.to_string(index=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 38,
|
||
"id": "181dcded",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== TERMINAL CCAL (2025) — cruzando con supply_orders ===\n",
|
||
" centro ccal_orders supply_orders_asociados con_service_request total_cost_ccal\n",
|
||
" Goya GLASS 9110 7120 0 2366941\n",
|
||
" Store 6571 505 0 1139059\n",
|
||
" MT El Bercial CRISTALES 6143 4869 0 1648415\n",
|
||
" Vallecas CRISTALES 6019 4953 0 1550761\n",
|
||
" Leganes 5864 507 0 1093530\n",
|
||
" Vaguada 5644 940 0 995783\n",
|
||
" MT Sanchinarro 5166 1683 0 1427021\n",
|
||
" Malaga 4923 336 0 874492\n",
|
||
" Villalba 4732 658 0 856667\n",
|
||
" Alcobendas CRISTALES 4616 3751 0 1350488\n",
|
||
" Granada 4446 257 0 818977\n",
|
||
" Leganes CRISTALES 4102 3599 0 1140564\n",
|
||
" San Fernando CRISTALES 4007 3450 0 1167164\n",
|
||
" Villalba CRISTALES 3888 3478 0 1163717\n",
|
||
"Santa Engracia CRISTALES 3856 3306 0 1157439\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\n",
|
||
"=== Distribucion por terminal_type_id ===\n",
|
||
" terminal_type_id terminales orders_2025 precaweb ccal_count caja_web_count\n",
|
||
" 17 7274 0 0 0 0\n",
|
||
" 3 805 1797438 175236 5 77\n",
|
||
" 9 444 440148 1134 1 50\n",
|
||
" 15 274 13429 0 0 34\n",
|
||
" 5 65 140510 0 64 0\n",
|
||
" 8 53 0 0 0 0\n",
|
||
" 10 53 1834 0 52 0\n",
|
||
" 11 52 33533 0 52 0\n",
|
||
" 16 34 65649 0 34 0\n",
|
||
" 1 11 0 0 0 0\n",
|
||
" 14 5 0 0 5 0\n",
|
||
" 12 3 0 0 0 0\n",
|
||
" 4 2 0 0 0 0\n",
|
||
" 6 1 1161 1161 0 1\n",
|
||
" 20 1 0 0 0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Cross-check CCAL: ver si sus orders generan supply_orders con service_request_id\n",
|
||
"# (indicando que es venta centralizada / call center)\n",
|
||
"sql_ccal = '''\n",
|
||
"WITH ccal_orders AS (\n",
|
||
" SELECT o.id AS order_id, o.terminal_id, o.total_cost, o.created_at, t.name AS term_name, c.name AS centro\n",
|
||
" FROM `autingo-159109.psql_dcpublic.tpv_orders_order` o\n",
|
||
" JOIN `autingo-159109.psql_dcpublic.tpv_terminals` t ON o.terminal_id = t.id\n",
|
||
" JOIN `autingo-159109.psql_dcpublic.centers` c ON t.center_id = c.id\n",
|
||
" WHERE t.name = 'CCAL'\n",
|
||
" AND EXTRACT(YEAR FROM o.created_at) = 2025\n",
|
||
")\n",
|
||
"SELECT\n",
|
||
" co.centro,\n",
|
||
" COUNT(DISTINCT co.order_id) AS ccal_orders,\n",
|
||
" COUNT(DISTINCT so.id) AS supply_orders_asociados,\n",
|
||
" COUNTIF(so.service_request_id IS NOT NULL) AS con_service_request,\n",
|
||
" ROUND(SUM(co.total_cost), 0) AS total_cost_ccal\n",
|
||
"FROM ccal_orders co\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.supply_orders` so ON so.tpv_orders_order_id = co.order_id\n",
|
||
"GROUP BY co.centro\n",
|
||
"ORDER BY ccal_orders DESC\n",
|
||
"LIMIT 15\n",
|
||
"'''\n",
|
||
"df_ccal = run_sql(sql_ccal)\n",
|
||
"print('=== TERMINAL CCAL (2025) — cruzando con supply_orders ===')\n",
|
||
"print(df_ccal.to_string(index=False))\n",
|
||
"\n",
|
||
"# Y ver terminal_types\n",
|
||
"sql_types = '''\n",
|
||
"SELECT\n",
|
||
" t.terminal_type_id,\n",
|
||
" COUNT(DISTINCT t.id) AS terminales,\n",
|
||
" COUNT(DISTINCT o.id) AS orders_2025,\n",
|
||
" COUNTIF(o.is_precaweb) AS precaweb,\n",
|
||
" COUNT(DISTINCT CASE WHEN t.name = 'CCAL' THEN t.id END) AS ccal_count,\n",
|
||
" COUNT(DISTINCT CASE WHEN t.name = 'CAJA_WEB' THEN t.id END) AS caja_web_count\n",
|
||
"FROM `autingo-159109.psql_dcpublic.tpv_terminals` t\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.tpv_orders_order` o\n",
|
||
" ON o.terminal_id = t.id AND EXTRACT(YEAR FROM o.created_at) = 2025\n",
|
||
"GROUP BY t.terminal_type_id\n",
|
||
"ORDER BY terminales DESC\n",
|
||
"'''\n",
|
||
"df_types = run_sql(sql_types)\n",
|
||
"print()\n",
|
||
"print('=== Distribucion por terminal_type_id ===')\n",
|
||
"print(df_types.to_string(index=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "062f199b",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 13. Unión venta ↔ terminal TPV — verificación\n",
|
||
"\n",
|
||
"### 13.1 Caminos que SÍ funcionan\n",
|
||
"\n",
|
||
"```\n",
|
||
"tpv_orders_order.terminal_id → tpv_terminals.id → tpv_terminals.center_id → centers\n",
|
||
"tpv_orders_invoice.terminal_id → tpv_terminals.id\n",
|
||
"supply_orders.tpv_orders_order_id → tpv_orders_order.id\n",
|
||
"```\n",
|
||
"\n",
|
||
"Tanto el `order` como la `invoice` TPV cargan el `terminal_id`. La union funciona limpia.\n",
|
||
"\n",
|
||
"### 13.2 Flags que indican origen (señales directas)\n",
|
||
"\n",
|
||
"Campos en **`tpv_orders_order`**:\n",
|
||
"\n",
|
||
"| Campo | Qué indica | Utilidad |\n",
|
||
"|---|---|---|\n",
|
||
"| `is_precaweb` (Boolean) | Orden creada por flujo web (pre-caja web) | **Sí**: flag directo venta online |\n",
|
||
"| `has_service_request` (Boolean) | Ligada a service_request web | Poco usado (siempre 0 en 2025) |\n",
|
||
"| `appointment_id` | Venía de cita previa | Útil para C&C/cita |\n",
|
||
"| `source` (Text) | **NULL en todos los 2.5M orders 2025** | ❌ No usar |\n",
|
||
"\n",
|
||
"### 13.3 Terminales reales (muestreo 2025)\n",
|
||
"\n",
|
||
"| Nombre terminal | Nº terminales | Orders 2025 | is_precaweb | Qué es |\n",
|
||
"|---|---:|---:|---:|---|\n",
|
||
"| `CAJA_WEB` | 162 | 320.493 | **177.531** | Terminal web — en TODOS los centros (no solo digitales) |\n",
|
||
"| `CCAL` | 213 | 241.416 | 0 | **Call center de cristales/lunas** — siempre ligado a centros CRISTALES (Goya GLASS, Vallecas CRISTALES, Alcobendas CRISTALES, etc.) |\n",
|
||
"| `{codcentro}CAJA01..04` | ~800 | millones | 0 | Cajas físicas del centro — venta presencial pura |\n",
|
||
"| `{codcentro}TALLER01` / `OFICINA01` | variable | variable | 0 | Terminales de taller/oficina |\n",
|
||
"| `FICHAJE` | variable | 0 | 0 | Terminal de fichar (no venta) |\n",
|
||
"\n",
|
||
"**Aviso importante**: `CCAL` NO es Click & Collect. Es el **call center de cristales** — operadores que toman pedidos telefónicos y los registran en una terminal dedicada. Tiene total_cost de 2.4M€/año solo en Goya GLASS. Es una línea de negocio aparte.\n",
|
||
"\n",
|
||
"### 13.4 Clasificación operativa del origen de venta\n",
|
||
"\n",
|
||
"Combinando terminal + flag:\n",
|
||
"\n",
|
||
"```sql\n",
|
||
"CASE\n",
|
||
" -- Venta web pura\n",
|
||
" WHEN o.is_precaweb = TRUE THEN 'web_online'\n",
|
||
" -- Call center cristales (detectar por terminal + centro)\n",
|
||
" WHEN t.name = 'CCAL' AND c.name LIKE '%CRISTAL%' THEN 'call_center_cristales'\n",
|
||
" WHEN t.name = 'CCAL' THEN 'call_center'\n",
|
||
" -- Venta presencial tienda\n",
|
||
" WHEN t.name LIKE '%CAJA0%' OR t.name LIKE '%TALLER%' OR t.name LIKE '%OFICINA%' THEN 'presencial_tienda'\n",
|
||
" -- CAJA_WEB con precaweb=FALSE: raro pero lo ves en centros digitales (5 orders en 2025)\n",
|
||
" WHEN t.name = 'CAJA_WEB' AND o.is_precaweb = FALSE THEN 'web_legacy_no_flag'\n",
|
||
" ELSE 'otro'\n",
|
||
"END AS origen_venta\n",
|
||
"```\n",
|
||
"\n",
|
||
"**Con este campo podemos**:\n",
|
||
"- Segmentar los ~2.5M orders/año por origen sin depender del nombre de terminal\n",
|
||
"- Cruzar cada origen con NAV invoice (vía `tpv_orders_invoice.nav_id` o `supply_orders.tpv_orders_order_id`)\n",
|
||
"- Añadir canal marketplace cuando origen = web_online (via `supply_orders → service_requests → channels`)\n",
|
||
"\n",
|
||
"### 13.5 Vista canónica v2 (incorporando TPV)\n",
|
||
"\n",
|
||
"La view `v_venta_web_unificada` propuesta en la sección 12.3 se enriquece con terminal + origen:\n",
|
||
"\n",
|
||
"```sql\n",
|
||
"-- Añadir JOINs a tpv_orders_order / terminals y campo origen_venta\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.tpv_orders_order` tpv_o ON so.tpv_orders_order_id = tpv_o.id\n",
|
||
"LEFT JOIN `autingo-159109.psql_dcpublic.tpv_terminals` tpv_t ON tpv_o.terminal_id = tpv_t.id\n",
|
||
"```\n",
|
||
"\n",
|
||
"Esto permite:\n",
|
||
"- Saber en qué terminal se imputó (tienda + caja específica)\n",
|
||
"- Distinguir web / call center / presencial / C&C sin heurísticas frágiles\n",
|
||
"- Seguir la cadena hasta la factura NAV\n",
|
||
"\n",
|
||
"### 13.6 Limitaciones detectadas\n",
|
||
"\n",
|
||
"- El campo `source` está vacío → no confiar en él\n",
|
||
"- `has_service_request=FALSE` incluso para orders claramente web → flag no mantenido, usar `is_precaweb` en su lugar\n",
|
||
"- `CCAL` sin flag alguno → hay que identificarlo por nombre + contexto del centro\n",
|
||
"- Nombres de terminal no son estándar estricto (variantes `CAJA_WEB`, `CCAL`, `{cod}CAJA01`...) — conviene crear un catálogo `tpv_terminal_clasificacion` en `anjana_bi_datamart` para mantener la clasificación actualizada"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3 (ipykernel)",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.13.5"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
|
||
}
|