From 9cdd0974aea247bc401e3e9fe31d9164d2539c74 Mon Sep 17 00:00:00 2001
From: RaulTavares332 <raul.melo.tavares@gmail.com>
Date: Tue, 16 Jun 2026 19:33:38 -0300
Subject: [PATCH] =?UTF-8?q?Resolu=C3=A7=C3=A3o=20do=20desafio=20t=C3=A9cni?=
 =?UTF-8?q?co=20-=20Raul?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 Challenge.ipynb | 798 ++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 798 insertions(+)
 create mode 100644 Challenge.ipynb

diff --git a/Challenge.ipynb b/Challenge.ipynb
new file mode 100644
index 0000000..0b7cf32
--- /dev/null
+++ b/Challenge.ipynb
@@ -0,0 +1,798 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "9a2be707-0bb4-484d-b837-d6aa1dd5173b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Imports e Conexão\n",
+    "import os\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "from matplotlib.patches import Patch\n",
+    "from sqlalchemy import create_engine\n",
+    "\n",
+    "engine = create_engine(\n",
+    "    f\"mysql+pymysql://{os.environ['DB_USER']}:{os.environ['DB_PASS']}@{os.environ['DB_HOST']}/{os.environ['DB_NAME']}\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "deba76a9-592c-46e7-af92-48cb073ae77c",
+   "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>PRODUCT_COD</th>\n",
+       "      <th>PRODUCT_NAME</th>\n",
+       "      <th>PRODUCT_VAL</th>\n",
+       "      <th>DEP_NAME</th>\n",
+       "      <th>DEP_COD</th>\n",
+       "      <th>SECTION_NAME</th>\n",
+       "      <th>SECTION_COD</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>301409</td>\n",
+       "      <td>Whisky Escoces THE MACALLAN Ruby Garrafa 700ml...</td>\n",
+       "      <td>741.99</td>\n",
+       "      <td>BEBIDAS</td>\n",
+       "      <td>2</td>\n",
+       "      <td>BEBIDAS</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>176185</td>\n",
+       "      <td>Whisky Escoces JOHNNIE WALKER Blue Label Garra...</td>\n",
+       "      <td>735.90</td>\n",
+       "      <td>BEBIDAS</td>\n",
+       "      <td>2</td>\n",
+       "      <td>BEBIDAS</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>315481</td>\n",
+       "      <td>Cafeteira Expresso 3 CORACOES Tres Modo Vermelho</td>\n",
+       "      <td>499.00</td>\n",
+       "      <td>BEBIDAS</td>\n",
+       "      <td>2</td>\n",
+       "      <td>BEBIDAS</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>100280</td>\n",
+       "      <td>Vinho Portugues Tinto Vintage QUINTA DO CRASTO...</td>\n",
+       "      <td>445.90</td>\n",
+       "      <td>BEBIDAS</td>\n",
+       "      <td>2</td>\n",
+       "      <td>VINHOS</td>\n",
+       "      <td>30</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>320046</td>\n",
+       "      <td>Escova Dental Eletrica ORAL B D34 Professional...</td>\n",
+       "      <td>399.90</td>\n",
+       "      <td>PERFUMARIA</td>\n",
+       "      <td>8</td>\n",
+       "      <td>HIGIENE BUCAL</td>\n",
+       "      <td>39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>190817</td>\n",
+       "      <td>Champagne Rose VEUVE CLICQUOT PONSARDIM Garraf...</td>\n",
+       "      <td>366.90</td>\n",
+       "      <td>MERCEARIA</td>\n",
+       "      <td>6</td>\n",
+       "      <td>ARTIGOS-PARA-O-LAR</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>153795</td>\n",
+       "      <td>Champagne Frances Brut Imperial MOET Rose Garr...</td>\n",
+       "      <td>359.90</td>\n",
+       "      <td>MERCEARIA</td>\n",
+       "      <td>6</td>\n",
+       "      <td>ARTIGOS-PARA-O-LAR</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>311397</td>\n",
+       "      <td>Conjunto de Panelas Allegra em Inox TRAMONTINA...</td>\n",
+       "      <td>359.00</td>\n",
+       "      <td>MERCEARIA</td>\n",
+       "      <td>6</td>\n",
+       "      <td>ARTIGOS-PARA-O-LAR</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>147706</td>\n",
+       "      <td>Whisky Escoces CHIVAS REGAL 18 Anos Garrafa 750ml</td>\n",
+       "      <td>329.90</td>\n",
+       "      <td>BEBIDAS</td>\n",
+       "      <td>2</td>\n",
+       "      <td>BEBIDAS</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>154431</td>\n",
+       "      <td>Champagne Frances Brut Imperial MOET &amp; CHANDON...</td>\n",
+       "      <td>315.90</td>\n",
+       "      <td>MERCEARIA</td>\n",
+       "      <td>6</td>\n",
+       "      <td>ARTIGOS-PARA-O-LAR</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   PRODUCT_COD                                       PRODUCT_NAME  \\\n",
+       "0       301409  Whisky Escoces THE MACALLAN Ruby Garrafa 700ml...   \n",
+       "1       176185  Whisky Escoces JOHNNIE WALKER Blue Label Garra...   \n",
+       "2       315481   Cafeteira Expresso 3 CORACOES Tres Modo Vermelho   \n",
+       "3       100280  Vinho Portugues Tinto Vintage QUINTA DO CRASTO...   \n",
+       "4       320046  Escova Dental Eletrica ORAL B D34 Professional...   \n",
+       "5       190817  Champagne Rose VEUVE CLICQUOT PONSARDIM Garraf...   \n",
+       "6       153795  Champagne Frances Brut Imperial MOET Rose Garr...   \n",
+       "7       311397  Conjunto de Panelas Allegra em Inox TRAMONTINA...   \n",
+       "8       147706  Whisky Escoces CHIVAS REGAL 18 Anos Garrafa 750ml   \n",
+       "9       154431  Champagne Frances Brut Imperial MOET & CHANDON...   \n",
+       "\n",
+       "   PRODUCT_VAL    DEP_NAME  DEP_COD        SECTION_NAME  SECTION_COD  \n",
+       "0       741.99     BEBIDAS        2             BEBIDAS            4  \n",
+       "1       735.90     BEBIDAS        2             BEBIDAS            4  \n",
+       "2       499.00     BEBIDAS        2             BEBIDAS            4  \n",
+       "3       445.90     BEBIDAS        2              VINHOS           30  \n",
+       "4       399.90  PERFUMARIA        8       HIGIENE BUCAL           39  \n",
+       "5       366.90   MERCEARIA        6  ARTIGOS-PARA-O-LAR            2  \n",
+       "6       359.90   MERCEARIA        6  ARTIGOS-PARA-O-LAR            2  \n",
+       "7       359.00   MERCEARIA        6  ARTIGOS-PARA-O-LAR            2  \n",
+       "8       329.90     BEBIDAS        2             BEBIDAS            4  \n",
+       "9       315.90   MERCEARIA        6  ARTIGOS-PARA-O-LAR            2  "
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Q1: Os 10 produtos mais caros ordenados por preço\n",
+    "pd.read_sql(\"\"\"\n",
+    "    SELECT *\n",
+    "    FROM data_product\n",
+    "    ORDER BY PRODUCT_VAL DESC\n",
+    "    LIMIT 10\n",
+    "\"\"\", engine)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "b3978805-db0c-46b7-a371-073998fc5115",
+   "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>SECTION_NAME</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>BEBIDAS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>VINHOS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>DOCES-E-SOBREMESAS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>QUEIJOS-E-FRIOS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>CERVEJAS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>PADARIA</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>REFRESCOS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>GESTANTE</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         SECTION_NAME\n",
+       "0             BEBIDAS\n",
+       "1              VINHOS\n",
+       "2  DOCES-E-SOBREMESAS\n",
+       "3     QUEIJOS-E-FRIOS\n",
+       "4            CERVEJAS\n",
+       "5             PADARIA\n",
+       "6           REFRESCOS\n",
+       "7            GESTANTE"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Q2: Seções únicas dos departamentos BEBIDAS e PADARIA\n",
+    "pd.read_sql(\"\"\"\n",
+    "    SELECT DISTINCT SECTION_NAME\n",
+    "    FROM data_product\n",
+    "    WHERE DEP_NAME IN ('BEBIDAS', 'PADARIA')\n",
+    "\"\"\", engine)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "60037849-ead0-4c2e-beba-4c70c61fa365",
+   "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>BUSINESS_NAME</th>\n",
+       "      <th>TOTAL_SALES</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Farma</td>\n",
+       "      <td>81776691.73</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Varejo</td>\n",
+       "      <td>81032347.65</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Atacado</td>\n",
+       "      <td>80384884.60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Proximidade</td>\n",
+       "      <td>80171122.80</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Posto</td>\n",
+       "      <td>32072326.40</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  BUSINESS_NAME  TOTAL_SALES\n",
+       "0         Farma  81776691.73\n",
+       "1        Varejo  81032347.65\n",
+       "2       Atacado  80384884.60\n",
+       "3   Proximidade  80171122.80\n",
+       "4         Posto  32072326.40"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Q3: Total de vendas agrupado por área de negócio no Q1 2019\n",
+    "pd.read_sql(\"\"\"\n",
+    "    SELECT BUSINESS_NAME,\n",
+    "    SUM(SALES_VALUE) AS TOTAL_SALES\n",
+    "    FROM data_store_sales s\n",
+    "    JOIN data_store_cad c\n",
+    "    ON s.STORE_CODE = c.STORE_CODE\n",
+    "    WHERE s.DATE BETWEEN '2019-01-01' AND '2019-03-31'\n",
+    "    GROUP BY BUSINESS_NAME\n",
+    "    ORDER BY TOTAL_SALES DESC\n",
+    "\"\"\", engine)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "f25ce554-6202-4d59-8ac0-287e9aac05ca",
+   "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>STORE_CODE</th>\n",
+       "      <th>PRODUCT_CODE</th>\n",
+       "      <th>DATE</th>\n",
+       "      <th>SALES_VALUE</th>\n",
+       "      <th>SALES_QTY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>18</td>\n",
+       "      <td>2019-01-01</td>\n",
+       "      <td>708.5</td>\n",
+       "      <td>65.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>18</td>\n",
+       "      <td>2019-01-02</td>\n",
+       "      <td>1297.1</td>\n",
+       "      <td>119.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>18</td>\n",
+       "      <td>2019-01-03</td>\n",
+       "      <td>1144.5</td>\n",
+       "      <td>105.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1</td>\n",
+       "      <td>18</td>\n",
+       "      <td>2019-01-04</td>\n",
+       "      <td>1090.0</td>\n",
+       "      <td>100.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1</td>\n",
+       "      <td>18</td>\n",
+       "      <td>2019-01-05</td>\n",
+       "      <td>893.8</td>\n",
+       "      <td>82.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  STORE_CODE  PRODUCT_CODE        DATE  SALES_VALUE  SALES_QTY\n",
+       "0          1            18  2019-01-01        708.5       65.0\n",
+       "1          1            18  2019-01-02       1297.1      119.0\n",
+       "2          1            18  2019-01-03       1144.5      105.0\n",
+       "3          1            18  2019-01-04       1090.0      100.0\n",
+       "4          1            18  2019-01-05        893.8       82.0"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Case 1: Função dinâmica que aceita filtros opcionais\n",
+    "def retrieve_data(product_code=None, store_code=None, date=None):\n",
+    "    query = \"SELECT * FROM data_product_sales WHERE 1=1\"\n",
+    "    if product_code is not None:\n",
+    "        query += f\" AND PRODUCT_CODE = {product_code}\"\n",
+    "    if store_code is not None:\n",
+    "        query += f\" AND STORE_CODE = '{store_code}'\"\n",
+    "    if date is not None:\n",
+    "        query += f\" AND DATE BETWEEN '{date[0]}' AND '{date[1]}'\"\n",
+    "    return pd.read_sql(query, engine)\n",
+    "\n",
+    "# Teste\n",
+    "my_data = retrieve_data(date=['2019-01-01', '2019-01-31'])\n",
+    "my_data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "7991ad27-0c1f-4b6d-9673-4fcccf71e088",
+   "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>Loja</th>\n",
+       "      <th>Categoria</th>\n",
+       "      <th>TM</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Bahia</td>\n",
+       "      <td>Atacado</td>\n",
+       "      <td>15.39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Bangkok</td>\n",
+       "      <td>Posto</td>\n",
+       "      <td>13.67</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Belem</td>\n",
+       "      <td>Proximidade</td>\n",
+       "      <td>15.37</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Berlin</td>\n",
+       "      <td>Proximidade</td>\n",
+       "      <td>15.39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Buenos Aires</td>\n",
+       "      <td>Atacado</td>\n",
+       "      <td>15.39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Chicago</td>\n",
+       "      <td>Varejo</td>\n",
+       "      <td>15.53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Dubai</td>\n",
+       "      <td>Atacado</td>\n",
+       "      <td>15.39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Hong Kong</td>\n",
+       "      <td>Farma</td>\n",
+       "      <td>26.35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>London</td>\n",
+       "      <td>Farma</td>\n",
+       "      <td>28.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Madri</td>\n",
+       "      <td>Farma</td>\n",
+       "      <td>29.03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>Miami</td>\n",
+       "      <td>Posto</td>\n",
+       "      <td>13.67</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>New York</td>\n",
+       "      <td>Proximidade</td>\n",
+       "      <td>15.39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>Paris</td>\n",
+       "      <td>Proximidade</td>\n",
+       "      <td>15.39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>Rio de Janeiro</td>\n",
+       "      <td>Farma</td>\n",
+       "      <td>29.59</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>Roma</td>\n",
+       "      <td>Varejo</td>\n",
+       "      <td>15.39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>Salvador</td>\n",
+       "      <td>Atacado</td>\n",
+       "      <td>15.39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>Sao Paulo</td>\n",
+       "      <td>Varejo</td>\n",
+       "      <td>15.39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>Sidney</td>\n",
+       "      <td>Posto</td>\n",
+       "      <td>13.67</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>Tokio</td>\n",
+       "      <td>Varejo</td>\n",
+       "      <td>15.39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>Vancouver</td>\n",
+       "      <td>Posto</td>\n",
+       "      <td>13.67</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              Loja    Categoria     TM\n",
+       "0            Bahia      Atacado  15.39\n",
+       "1          Bangkok        Posto  13.67\n",
+       "2            Belem  Proximidade  15.37\n",
+       "3           Berlin  Proximidade  15.39\n",
+       "4     Buenos Aires      Atacado  15.39\n",
+       "5          Chicago       Varejo  15.53\n",
+       "6            Dubai      Atacado  15.39\n",
+       "7        Hong Kong        Farma  26.35\n",
+       "8           London        Farma  28.99\n",
+       "9            Madri        Farma  29.03\n",
+       "10           Miami        Posto  13.67\n",
+       "11        New York  Proximidade  15.39\n",
+       "12           Paris  Proximidade  15.39\n",
+       "13  Rio de Janeiro        Farma  29.59\n",
+       "14            Roma       Varejo  15.39\n",
+       "15        Salvador      Atacado  15.39\n",
+       "16       Sao Paulo       Varejo  15.39\n",
+       "17          Sidney        Posto  13.67\n",
+       "18           Tokio       Varejo  15.39\n",
+       "19       Vancouver        Posto  13.67"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Case 2: JOIN no Python + Ticket Médio por loja no Q4 2019\n",
+    "query1 = pd.read_sql(\"\"\"\n",
+    "    SELECT STORE_CODE, STORE_NAME, START_DATE, END_DATE, BUSINESS_NAME, BUSINESS_CODE\n",
+    "    FROM data_store_cad\n",
+    "\"\"\", engine)\n",
+    "\n",
+    "query2 = pd.read_sql(\"\"\"\n",
+    "    SELECT STORE_CODE, DATE, SALES_VALUE, SALES_QTY\n",
+    "    FROM data_store_sales\n",
+    "    WHERE DATE BETWEEN '2019-01-01' AND '2019-12-31'\n",
+    "\"\"\", engine)\n",
+    "\n",
+    "merged = query1.merge(query2, on='STORE_CODE')\n",
+    "merged['DATE'] = pd.to_datetime(merged['DATE'])\n",
+    "filtered = merged[(merged['DATE'] >= '2019-10-01') & (merged['DATE'] <= '2019-12-31')]\n",
+    "\n",
+    "resultado = filtered.groupby(['STORE_NAME', 'BUSINESS_NAME']).apply(\n",
+    "    lambda x: (x['SALES_VALUE'].sum() / x['SALES_QTY'].sum()), include_groups=False\n",
+    ").reset_index()\n",
+    "\n",
+    "resultado.columns = ['Loja', 'Categoria', 'TM']\n",
+    "resultado['TM'] = resultado['TM'].round(2)\n",
+    "resultado = resultado.sort_values('Loja').reset_index(drop=True)\n",
+    "\n",
+    "display(resultado)\n",
+    "\n",
+    "# Gráfico\n",
+    "fig, ax = plt.subplots(figsize=(10, 8))\n",
+    "colors = {'Varejo': 'steelblue', 'Farma': 'green', 'Atacado': 'orange', \n",
+    "          'Proximidade': 'purple', 'Posto': 'red'}\n",
+    "ax.barh(resultado['Loja'], resultado['TM'], \n",
+    "        color=[colors[cat] for cat in resultado['Categoria']])\n",
+    "ax.set_xlabel('Ticket Médio (TM)')\n",
+    "ax.set_title('Ticket Médio por Loja - Q4 2019')\n",
+    "legend = [Patch(color=v, label=k) for k, v in colors.items()]\n",
+    "ax.legend(handles=legend)\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "445cfd7d-17d7-4756-b68e-028991a49edb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Case 3: Rating médio por ano mostra queda na qualidade dos filmes ao longo do tempo\n",
+    "df_imdb = pd.read_sql(\"SELECT Year, Rating FROM IMDB_movies WHERE Year IS NOT NULL AND Rating IS NOT NULL\", engine)\n",
+    "\n",
+    "rating_por_ano = df_imdb.groupby('Year')['Rating'].mean().reset_index()\n",
+    "rating_por_ano.columns = ['Ano', 'Rating Médio']\n",
+    "rating_por_ano['Rating Médio'] = rating_por_ano['Rating Médio'].round(2)\n",
+    "\n",
+    "fig, ax = plt.subplots(figsize=(12, 6))\n",
+    "ax.plot(rating_por_ano['Ano'], rating_por_ano['Rating Médio'], \n",
+    "        marker='o', color='steelblue', linewidth=2)\n",
+    "ax.set_title('Rating Médio dos Filmes por Ano (IMDB)', fontsize=14)\n",
+    "ax.set_xlabel('Ano')\n",
+    "ax.set_ylabel('Rating Médio')\n",
+    "ax.grid(True, alpha=0.3)\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b86eb0c3-1033-4717-ab52-74d30af011dc",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.12.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}