{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6ad35669",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np \n",
    "import glob\n",
    "import os \n",
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fa16d50c",
   "metadata": {},
   "outputs": [],
   "source": [
    "hoje = datetime.today().strftime('%Y-%m-%d')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9fcdc77a",
   "metadata": {},
   "outputs": [],
   "source": [
    "calendario = pd.read_excel(r\"C:\\Users\\joao.herculano\\GRUPO GINSENG\\Assistência Suprimentos - 2025\\SUPRIMENTOS\\BD_LANÇAMENTOS\\BASE DE DADOS LANÇAMENTO\\BOT\\CICLO 9\\CALENDARIO_CICLO\\Ciclo_Expandido_com_Datas.xlsx\")\n",
    "\n",
    "calendario['Date'] = pd.to_datetime(calendario['Date'])\n",
    "\n",
    "# Get today (normalized to midnight)\n",
    "today = pd.Timestamp(\"today\").normalize()\n",
    "\n",
    "calendario['NUM_CICLO'] = calendario['Ciclo'].str[-2:].astype(int)\n",
    "\n",
    "calendario['ANO_CICLO'] = calendario['Ciclo'].str[0:5]\n",
    "\n",
    "calendario = calendario[calendario['MARCA'] == \"BOTICARIO\"]\n",
    "\n",
    "calendario['CICLOMAIS2'] = calendario['ANO_CICLO'].astype(str) + (calendario['NUM_CICLO'].astype(int) + 3).astype(str).str.zfill(2)       #<<< MUDAR O \"4\" (CICLO ATUAL + 4 PARA ACHAR O CICLO DA SUGESTÃO) EX: C202505 -> C202509\n",
    "ciclo_mais2 = calendario[calendario['Date'].dt.normalize() == today]['CICLOMAIS2'].iloc[0]\n",
    "\n",
    "# Filter rows where date matches today\n",
    "filtered_calendario = calendario[calendario['Ciclo'] == ciclo_mais2][:1]\n",
    "\n",
    "filtered_calendario['dias_ate_inicio'] = filtered_calendario['INICIO CICLO'].iloc[0] - today\n",
    "\n",
    "filtered_calendario['dias_ate_inicio'] = filtered_calendario['dias_ate_inicio'].dt.days.astype(int)\n",
    "\n",
    "filtered_calendario['match'] = 1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "bbec229d",
   "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>Ciclo</th>\n",
       "      <th>INICIO CICLO</th>\n",
       "      <th>FIM CICLO</th>\n",
       "      <th>DURAÇÃO</th>\n",
       "      <th>MARCA</th>\n",
       "      <th>Date</th>\n",
       "      <th>NUM_CICLO</th>\n",
       "      <th>ANO_CICLO</th>\n",
       "      <th>CICLOMAIS2</th>\n",
       "      <th>dias_ate_inicio</th>\n",
       "      <th>match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2451</th>\n",
       "      <td>C202516</td>\n",
       "      <td>2025-11-03</td>\n",
       "      <td>2025-11-30</td>\n",
       "      <td>28</td>\n",
       "      <td>BOTICARIO</td>\n",
       "      <td>2025-11-03</td>\n",
       "      <td>16</td>\n",
       "      <td>C2025</td>\n",
       "      <td>C202519</td>\n",
       "      <td>59</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Ciclo INICIO CICLO  FIM CICLO  DURAÇÃO      MARCA       Date  \\\n",
       "2451  C202516   2025-11-03 2025-11-30       28  BOTICARIO 2025-11-03   \n",
       "\n",
       "      NUM_CICLO ANO_CICLO CICLOMAIS2  dias_ate_inicio  match  \n",
       "2451         16     C2025    C202519               59      1  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_calendario"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0245ed28",
   "metadata": {},
   "outputs": [],
   "source": [
    "ciclo_lanc = filtered_calendario['Ciclo'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7a3c1e6f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C202516'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ciclo_lanc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "61ffc777",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_similares = pd.read_excel(r\"C:\\Users\\joao.herculano\\GRUPO GINSENG\\Assistência Suprimentos - 2025\\SUPRIMENTOS\\BD_LANÇAMENTOS\\BOT\\BOT - C16\\arquivos para geração da sugestão\\SIMILARES\\PRODUTOS SIMILARES - BOT.xlsx\")\n",
    "\n",
    "df_similares = pd.merge(left=df_similares,right=calendario[['Ciclo','INICIO CICLO','FIM CICLO','DURAÇÃO']], how= 'left', left_on = 'CICLO SIMILAR',right_on = 'Ciclo' )\n",
    "\n",
    "df_similares = df_similares.drop(columns=['Ciclo'])\n",
    "\n",
    "df_similares = df_similares.rename(columns={'INICIO CICLO':'INICIO CICLO SIMILAR','FIM CICLO':'FIM CICLO SIMILAR','DURAÇÃO':'DURAÇÃO CICLO SIMILAR'})\n",
    "df_similares.drop_duplicates(inplace=True)\n",
    "\n",
    "df_similares['MATCH'] = 1\n",
    "\n",
    "df_similares = df_similares.drop(columns=['INICIO DO CICLO', 'FIM DO CICLO', 'DURAÇÃO CICLO','INICIO CICLO SIMILAR','FIM CICLO SIMILAR','DURAÇÃO CICLO SIMILAR'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ad836441",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_similares['PRODUTO SIMILAR'] = df_similares['PRODUTO SIMILAR'].astype('str')\n",
    "\n",
    "df_similares['PRODUTO SIMILAR'] = df_similares['PRODUTO SIMILAR'].replace(r'\\.0$', '', regex=True)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "fe922f62",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tabela = pd.read_excel(r\"C:\\Users\\joao.herculano\\GRUPO GINSENG\\Assistência Suprimentos - 2025\\SUPRIMENTOS\\BD_LANÇAMENTOS\\BOT\\BOT - C16\\arquivos para geração da sugestão\\TABELA DE PEDIDO\\Pedidos Semanais Especiais - BOT - 202516.xlsx\")\n",
    "\n",
    "df_tabela = df_tabela[df_tabela['Região'] == 'NNE'] \n",
    "\n",
    "df_tabela = df_tabela[(df_tabela['Canal'] != 'Ecomm') | (df_tabela['Canal'] != 'Ecomm | VD') | (df_tabela['Canal'] != 'Ecomm | Loja')] \n",
    "\n",
    "df_tabela['Canal'] = np.where((df_tabela['Canal'] == \"Loja\") | (df_tabela['Canal'] == \"Todos\") | (df_tabela['Canal'] == \"Loja | VD\"),\"TODOS\",\"VD\")\n",
    "\n",
    "df_tabela = df_tabela[df_tabela['Tipo de promoção'].str.contains('Lançamentos', na=False)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e0c55962",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_pdv = pd.read_excel(r\"C:\\Users\\joao.herculano\\Documents\\PDV_ATT.xlsx\")\n",
    "df_pdv = df_pdv[~df_pdv['PDV'].isin([910173, 910291])]\n",
    "\n",
    "df_pdv_origi = pd.read_excel(r\"C:\\Users\\joao.herculano\\Documents\\PDV_ATT.xlsx\")\n",
    "df_pdv_origi = df_pdv_origi[~df_pdv_origi['PDV'].isin([910173, 910291])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f93735d1",
   "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>PDV</th>\n",
       "      <th>CANAL</th>\n",
       "      <th>DESCRIÇÃO</th>\n",
       "      <th>PDV DESC</th>\n",
       "      <th>REGIÃO</th>\n",
       "      <th>ESTADO</th>\n",
       "      <th>CIDADE</th>\n",
       "      <th>UF</th>\n",
       "      <th>MARCA</th>\n",
       "      <th>ANALISTA</th>\n",
       "      <th>GESTÃO</th>\n",
       "      <th>SUPERVISOR</th>\n",
       "      <th>STATUS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [PDV, CANAL, DESCRIÇÃO, PDV DESC, REGIÃO, ESTADO, CIDADE, UF, MARCA, ANALISTA, GESTÃO, SUPERVISOR, STATUS]\n",
       "Index: []"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_pdv[df_pdv['PDV']==910291]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a3a045d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "df_pdv = df_pdv.rename(columns={'DESCRIÇÃO':'DESCRIÇÃO PDV'})\n",
    "\n",
    "df_pdv = df_pdv.drop(columns=['REGIÃO', 'ESTADO','CIDADE','GESTÃO','MARCA'])\n",
    "\n",
    "df_pdv['UF'] = np.where(df_pdv['UF'] == 'VDC','BA',df_pdv['UF'])\n",
    "\n",
    "#ignorando a PDV que ainda não está online\n",
    "df_pdv = df_pdv[df_pdv['DESCRIÇÃO PDV'] != '23813-COMERCIO-HIB VALENTE']\n",
    "\n",
    "df_pdv = df_pdv[df_pdv['STATUS'] != \"INATIVO\"]\n",
    "\n",
    "df_pdv = df_pdv[df_pdv['STATUS'] != \"MATRIZ\"]\n",
    "\n",
    "df_pdv = df_pdv[df_pdv['SUPERVISOR'] != 'Inativa']\n",
    "\n",
    "df_pdv['MATCH'] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "df04a501",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_similares = pd.merge(left=df_similares,right=df_pdv,right_on=['MATCH'],left_on=['MATCH'],how='inner')\n",
    "\n",
    "df_similares = df_similares.drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0da911af",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joao.herculano\\AppData\\Local\\Temp\\ipykernel_31644\\1001187263.py:39: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
      "  dfi = pd.read_sql(query, conn)\n"
     ]
    }
   ],
   "source": [
    "import pyodbc\n",
    "import configparser\n",
    "\n",
    "#query de vendas por ciclo\n",
    "\n",
    "config = configparser.ConfigParser()\n",
    "config.read(r\"C:\\Users\\joao.herculano\\Documents\\Enviador de email\\credenciais.ini\")\n",
    "\n",
    "conn = pyodbc.connect(\n",
    "    f\"DRIVER={{SQL Server}};\"\n",
    "    f\"SERVER={config['banco']['host']},1433;\"\n",
    "    f\"DATABASE=GINSENG;\"\n",
    "    f\"UID={config['banco']['user']};\"\n",
    "    f\"PWD={config['banco']['password']}\"\n",
    ")\n",
    "\n",
    "query = f'''\n",
    "SELECT \n",
    "    B.PDV, \n",
    "    B.SKU,\n",
    "    bd.SKU2, \n",
    "    COALESCE(bd.SKU2, b.SKU) AS SKU_FINAL,\n",
    "    B.DESCRICAO,\n",
    "    SUM(CAST(b.VENDAS AS DECIMAL(18,2))) AS VENDAS_CICLO,\n",
    "    C.Ciclo\n",
    "FROM base_vendas_bi b\n",
    "INNER JOIN ciclos_data_2025 c \n",
    "    ON CAST(b.[DATA] AS DATE) = CONVERT(DATE, c.[Date], 103) AND C.MARCA = 'BOT'\n",
    "LEFT JOIN base_depara bd on b.SKU = bd.SKU \n",
    "WHERE CAST(b.[DATA] AS DATE) >= DATEADD(YEAR, -1, GETDATE())\n",
    "GROUP BY\n",
    "    B.PDV, \n",
    "    B.SKU,\n",
    "    bd.SKU2,\n",
    "    B.DESCRICAO,\n",
    "    C.Ciclo\n",
    "HAVING SUM(CAST(b.VENDAS AS DECIMAL(18,2))) > 0\n",
    "'''\n",
    "dfi = pd.read_sql(query, conn)\n",
    "conn.close()\n",
    "\n",
    "dfi['SKU2'] = dfi['SKU2'].fillna(\"-\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "20634105",
   "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>PDV</th>\n",
       "      <th>SKU_FINAL</th>\n",
       "      <th>DESCRICAO</th>\n",
       "      <th>C202413</th>\n",
       "      <th>C202414</th>\n",
       "      <th>C202415</th>\n",
       "      <th>C202416</th>\n",
       "      <th>C202417</th>\n",
       "      <th>C202501</th>\n",
       "      <th>C202502</th>\n",
       "      <th>...</th>\n",
       "      <th>C202504</th>\n",
       "      <th>C202505</th>\n",
       "      <th>C202506</th>\n",
       "      <th>C202507</th>\n",
       "      <th>C202508</th>\n",
       "      <th>C202509</th>\n",
       "      <th>C202510</th>\n",
       "      <th>C202511</th>\n",
       "      <th>C202512</th>\n",
       "      <th>C202513</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12522</td>\n",
       "      <td>1004</td>\n",
       "      <td>FLORATTA DES COL MY BLUE 75ml</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12522</td>\n",
       "      <td>1080</td>\n",
       "      <td>INTENSE GLOS LAB BUBBAL TUT/FRUT 5ml</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12522</td>\n",
       "      <td>1296</td>\n",
       "      <td>PMPCK THE BLEND DES ANTIT AER 2x75g</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12522</td>\n",
       "      <td>1302</td>\n",
       "      <td>PMPCK LILY DES ANTIT AER 2x75g</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12522</td>\n",
       "      <td>1314</td>\n",
       "      <td>PMPCK ZAAD DES ANTIT AER 2x75g</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     PDV  SKU_FINAL                             DESCRICAO  C202413  C202414  \\\n",
       "0  12522       1004         FLORATTA DES COL MY BLUE 75ml     15.0      2.0   \n",
       "1  12522       1080  INTENSE GLOS LAB BUBBAL TUT/FRUT 5ml      0.0      4.0   \n",
       "2  12522       1296   PMPCK THE BLEND DES ANTIT AER 2x75g      1.0      3.0   \n",
       "3  12522       1302        PMPCK LILY DES ANTIT AER 2x75g      2.0      3.0   \n",
       "4  12522       1314        PMPCK ZAAD DES ANTIT AER 2x75g      0.0      3.0   \n",
       "\n",
       "   C202415  C202416  C202417  C202501  C202502  ...  C202504  C202505  \\\n",
       "0      3.0     56.0      6.0      1.0     11.0  ...      5.0     12.0   \n",
       "1      0.0     10.0      2.0      2.0      1.0  ...      3.0      1.0   \n",
       "2      3.0      2.0      0.0      0.0      0.0  ...      0.0      0.0   \n",
       "3      5.0      6.0      0.0      0.0      0.0  ...      0.0      0.0   \n",
       "4      1.0      1.0      0.0      0.0      0.0  ...      0.0      0.0   \n",
       "\n",
       "   C202506  C202507  C202508  C202509  C202510  C202511  C202512  C202513  \n",
       "0      7.0      2.0      0.0      1.0      2.0      5.0      3.0      0.0  \n",
       "1      7.0     17.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "2      0.0      0.0      0.0      0.0      0.0      0.0      0.0      2.0  \n",
       "3      3.0      4.0      0.0      4.0      4.0      2.0      1.0      2.0  \n",
       "4      0.0      0.0      0.0      0.0      0.0      1.0      1.0      0.0  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# 1. Agrupamento\n",
    "df_agrupado = dfi.groupby(['PDV', 'SKU_FINAL', 'DESCRICAO', 'Ciclo'], as_index=False)['VENDAS_CICLO'].sum()\n",
    "\n",
    "# 2. Pivotar o DataFrame\n",
    "df_pivotado = df_agrupado.pivot_table(\n",
    "    index=['PDV', 'SKU_FINAL', 'DESCRICAO'],\n",
    "    columns='Ciclo',\n",
    "    values='VENDAS_CICLO',\n",
    "    fill_value=0  # Substitui NaN por 0\n",
    ")\n",
    "\n",
    "# 3. Resetar o índice para deixar como DataFrame normal (opcional)\n",
    "df_pivotadowawa = df_pivotado.reset_index()\n",
    "\n",
    "# 4. (Opcional) Renomear colunas com prefixo \"Ciclo_\"\n",
    "df_pivotadowawa.columns.name = None\n",
    "df_pivotadowawa = df_pivotadowawa.rename(columns=lambda x: f'Ciclo_{x}' if isinstance(x, (int, str)) and str(x).isdigit() else x)\n",
    "\n",
    "# Resultado final\n",
    "df_pivotadowawa.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8289d835",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joao.herculano\\AppData\\Local\\Temp\\ipykernel_31644\\268247862.py:25: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
      "  df_draft_ = pd.read_sql(query_est_draft, conn)\n"
     ]
    }
   ],
   "source": [
    "conn = pyodbc.connect(\n",
    "    f\"DRIVER={{SQL Server}};\"\n",
    "    f\"SERVER={config['banco']['host']},1433;\"\n",
    "    f\"DATABASE=GINSENG;\"\n",
    "    f\"UID={config['banco']['user']};\"\n",
    "    f\"PWD={config['banco']['password']}\"\n",
    ")\n",
    "\n",
    "query_est_draft = f'''\n",
    "select em.PDV ,\n",
    "COALESCE(em.SKU_PARA , em.SKU) as SKU,\n",
    "em.DESCRICAO,\n",
    "d.salescurve as curva,\n",
    "d.codcategory as categoria,\n",
    "d.nextcycleprojection as proj_mar\n",
    ",d.secondtonextcycleprojection as 'proj_mar+1',\n",
    "em.[ESTOQUE ATUAL],em.[ESTOQUE EM TRANSITO],\n",
    "em.[PEDIDO PENDENTE],\n",
    "em.[DDV PREVISTO] ,\n",
    "d.pricesellin as 'preço'\n",
    "from estoque_mar em \n",
    "left join draft d on d.code = COALESCE(em.SKU_PARA , em.SKU) and d.loja_id = em.PDV \n",
    "where em.ORIGEM = 'BOT'\n",
    "'''\n",
    "df_draft_ = pd.read_sql(query_est_draft, conn)\n",
    "conn.close()\n",
    "\n",
    "#FALTA ATUALIZAR QUERY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "dd49288f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_draft = df_draft_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "67dd3c27",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joao.herculano\\AppData\\Local\\Temp\\ipykernel_31644\\1474679865.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_draft['ESTOQUE ATUAL'] = df_draft['ESTOQUE ATUAL'].astype(float)\n",
      "C:\\Users\\joao.herculano\\AppData\\Local\\Temp\\ipykernel_31644\\1474679865.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_draft['ESTOQUE EM TRANSITO'] = df_draft['ESTOQUE EM TRANSITO'].astype(float)\n",
      "C:\\Users\\joao.herculano\\AppData\\Local\\Temp\\ipykernel_31644\\1474679865.py:7: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_draft['PEDIDO PENDENTE'] = df_draft['PEDIDO PENDENTE'].astype(float)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(356210, 12)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_draft = df_draft[~df_draft['DESCRICAO'].str.contains('OUI', na=False)]\n",
    "\n",
    "df_draft['ESTOQUE ATUAL'] = df_draft['ESTOQUE ATUAL'].astype(float)\n",
    "\n",
    "df_draft['ESTOQUE EM TRANSITO'] = df_draft['ESTOQUE EM TRANSITO'].astype(float)\n",
    "\n",
    "df_draft['PEDIDO PENDENTE'] = df_draft['PEDIDO PENDENTE'].astype(float)\n",
    "\n",
    "df_draft.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "355778d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joao.herculano\\AppData\\Local\\Temp\\ipykernel_31644\\1952797845.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_draft['DDV PREVISTO'] = df_draft['DDV PREVISTO'].str.replace(',','.')\n",
      "C:\\Users\\joao.herculano\\AppData\\Local\\Temp\\ipykernel_31644\\1952797845.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_draft['DDV PREVISTO'] = df_draft['DDV PREVISTO'].astype(float)\n",
      "C:\\Users\\joao.herculano\\AppData\\Local\\Temp\\ipykernel_31644\\1952797845.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_draft['DDV PREVISTO'] = df_draft['DDV PREVISTO'].fillna(0)\n"
     ]
    }
   ],
   "source": [
    "df_draft['DDV PREVISTO'] = df_draft['DDV PREVISTO'].str.replace(',','.')\n",
    "\n",
    "df_draft['DDV PREVISTO'] = df_draft['DDV PREVISTO'].astype(float)\n",
    "\n",
    "df_draft['DDV PREVISTO'] = df_draft['DDV PREVISTO'].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d891c575",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_draft = df_draft.groupby(['PDV','SKU','curva','categoria'])[['proj_mar','proj_mar+1','ESTOQUE ATUAL','ESTOQUE EM TRANSITO','PEDIDO PENDENTE','DDV PREVISTO','preço']].max().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "3d13ef4c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_draft['SKU'] = df_draft['SKU'].astype('Int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "5ca66c75",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_draft = pd.merge(df_draft,df_pivotadowawa,left_on=['PDV','SKU'],right_on=['PDV','SKU_FINAL'],how='inner')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "91298cde",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['C202413', 'C202414', 'C202415', 'C202416', 'C202417', 'C202501',\n",
       "       'C202502', 'C202503', 'C202504', 'C202505', 'C202506', 'C202507',\n",
       "       'C202508', 'C202509', 'C202510', 'C202511', 'C202512', 'C202513'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_draft.columns[13:31]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "ed859826",
   "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>PDV</th>\n",
       "      <th>SKU</th>\n",
       "      <th>curva</th>\n",
       "      <th>categoria</th>\n",
       "      <th>proj_mar</th>\n",
       "      <th>proj_mar+1</th>\n",
       "      <th>ESTOQUE ATUAL</th>\n",
       "      <th>ESTOQUE EM TRANSITO</th>\n",
       "      <th>PEDIDO PENDENTE</th>\n",
       "      <th>DDV PREVISTO</th>\n",
       "      <th>...</th>\n",
       "      <th>C202504</th>\n",
       "      <th>C202505</th>\n",
       "      <th>C202506</th>\n",
       "      <th>C202507</th>\n",
       "      <th>C202508</th>\n",
       "      <th>C202509</th>\n",
       "      <th>C202510</th>\n",
       "      <th>C202511</th>\n",
       "      <th>C202512</th>\n",
       "      <th>C202513</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>0 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [PDV, SKU, curva, categoria, proj_mar, proj_mar+1, ESTOQUE ATUAL, ESTOQUE EM TRANSITO, PEDIDO PENDENTE, DDV PREVISTO, preço, SKU_FINAL, DESCRICAO, C202413, C202414, C202415, C202416, C202417, C202501, C202502, C202503, C202504, C202505, C202506, C202507, C202508, C202509, C202510, C202511, C202512, C202513]\n",
       "Index: []\n",
       "\n",
       "[0 rows x 31 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_draft[df_draft['PDV']==24293]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "34e179cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joao.herculano\\AppData\\Local\\Temp\\ipykernel_31644\\1731143361.py:24: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
      "  crescimento_por_pdv = df_draft.groupby('PDV').apply(calcular_crescimento)\n"
     ]
    }
   ],
   "source": [
    "# Define as colunas mensais\n",
    "colunas_mensais = df_draft.columns[13:31]\n",
    "\n",
    "# Agrupa por PDV e calcula crescimento médio por PDV\n",
    "def calcular_crescimento(grupo):\n",
    "    soma_mensal = grupo[colunas_mensais].sum()             # soma por mês\n",
    "    variacao_mensal = soma_mensal.pct_change().dropna()    # variação percentual mês a mês\n",
    "    variacao_mensal = variacao_mensal[np.isfinite(variacao_mensal)]\n",
    "\n",
    "    if len(variacao_mensal) == 0:\n",
    "        return pd.Series({'CRESCIMENTO': np.nan})\n",
    "\n",
    "    media = variacao_mensal.mean()\n",
    "    desvio = variacao_mensal.std()\n",
    "\n",
    "    limite_sup = media + 2 * desvio\n",
    "    limite_inf = media - 2 * desvio\n",
    "\n",
    "    variacoes_filtradas = variacao_mensal[variacao_mensal.between(limite_inf, limite_sup)]\n",
    "    crescimento = round(variacoes_filtradas.mean(), 4)\n",
    "    return pd.Series({'CRESCIMENTO': crescimento})\n",
    "\n",
    "# Aplica a função por PDV\n",
    "crescimento_por_pdv = df_draft.groupby('PDV').apply(calcular_crescimento)\n",
    "\n",
    "# Merge do resultado de volta no dataframe original\n",
    "df_draft = df_draft.merge(crescimento_por_pdv, on='PDV', how='left')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "94aa432f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    57890\n",
       "1    57890\n",
       "2    57890\n",
       "3    57890\n",
       "4    57890\n",
       "Name: PRODUTO SIMILAR, dtype: Int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_similares['PRODUTO SIMILAR'] = df_similares['PRODUTO SIMILAR'].astype('Int64')\n",
    "df_similares['PRODUTO SIMILAR'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "38b0eb5d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PDV    object\n",
       "SKU     Int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_draft[['PDV', 'SKU']].dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "4bc8c2b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_draft['PDV'] = df_draft['PDV'].astype('Int64')\n",
    "\n",
    "df_final = pd.merge(left=df_similares,right=df_draft,right_on=['PDV', 'SKU'],left_on=['PDV','PRODUTO SIMILAR'],how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "2c9f011d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PRODUTO SIMILAR\n",
       "57211    154\n",
       "48999    154\n",
       "48997    154\n",
       "57890     77\n",
       "58987     77\n",
       "48685     77\n",
       "56530     77\n",
       "57871     77\n",
       "51869     77\n",
       "49418     77\n",
       "49943     77\n",
       "49893     77\n",
       "56402     77\n",
       "56385     77\n",
       "48780     77\n",
       "58132     77\n",
       "Name: count, dtype: Int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_similares= df_similares[df_similares['PRODUTO SIMILAR'].notna()]\n",
    "\n",
    "df_similares['PRODUTO SIMILAR'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "0ff66803",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SKU\n",
       "48997    154\n",
       "48999    154\n",
       "57211    140\n",
       "49943    121\n",
       "49893     91\n",
       "57871     77\n",
       "58987     77\n",
       "56402     77\n",
       "56385     77\n",
       "57890     76\n",
       "48780     75\n",
       "51869     73\n",
       "48685     72\n",
       "49418     71\n",
       "58132     66\n",
       "56530     31\n",
       "Name: count, dtype: Int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final['SKU'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "c1451562",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_venda_diaria = pd.read_excel(r\"C:\\Users\\joao.herculano\\GRUPO GINSENG\\Assistência Suprimentos - 2025\\SUPRIMENTOS\\BD_LANÇAMENTOS\\BOT\\BOT - C12\\LANÇAMENTOS\\arquivos para geração da sugestão\\VENDAS_DIARIAS\\FormFiltroConsultaVendaSintetica_17_06_2025_14_04_40.xls\")\n",
    "#df_venda_diaria.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "64bde00b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_venda_diaria = pd.read_csv(\n",
    "    r\"C:\\Users\\joao.herculano\\GRUPO GINSENG\\Assistência Suprimentos - 2025\\SUPRIMENTOS\\BD_LANÇAMENTOS\\BOT\\BOT - C15\\arquivos para geração da sugestão\\VENDAS_DIARIAS\\vendas 20250815.csv\",\n",
    "    sep=';',\n",
    "    dtype={'SKU_2': str},decimal=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "6ab155b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_venda_diaria['VENDAS_CICLO'] = df_venda_diaria['VENDAS_CICLO'].str.replace(r'\\.', '', regex=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "1d25e5df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PDV</th>\n",
       "      <th>SKU</th>\n",
       "      <th>DESCRICAO</th>\n",
       "      <th>VENDAS_CICLO</th>\n",
       "      <th>Ciclo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12522</td>\n",
       "      <td>51.944</td>\n",
       "      <td>COFFEE DES COL MAN SEDUC TCH PRM 10ml</td>\n",
       "      <td>11</td>\n",
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       "      <td>ZAAD EDP 95ml V6</td>\n",
       "      <td>12</td>\n",
       "      <td>C202406</td>\n",
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       "      <th>4</th>\n",
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       "      <td>2</td>\n",
       "      <td>C202416</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PDV     SKU                                 DESCRICAO VENDAS_CICLO  \\\n",
       "0  12522  51.944     COFFEE DES COL MAN SEDUC TCH PRM 10ml           11   \n",
       "1  20998  77.557  QDB BASE LIQ SUPERMAT COR 06 Q 30ml RPCK            1   \n",
       "2  20858  74.103            GLAMOUR DES COL SEC BL 75ml V4            5   \n",
       "3   5699  47.950                          ZAAD EDP 95ml V6           12   \n",
       "4  20993  50.297               ESTJ DEM LILY ESSENCE 4x4ml            2   \n",
       "\n",
       "     Ciclo  \n",
       "0  C202307  \n",
       "1  C202405  \n",
       "2  C202409  \n",
       "3  C202406  \n",
       "4  C202416  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_venda_diaria.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "5d0d79f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>PDV</th>\n",
       "      <th>SKU</th>\n",
       "      <th>DESCRICAO</th>\n",
       "      <th>Vendas_Total</th>\n",
       "      <th>Ciclo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12522</td>\n",
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       "      <td>2</td>\n",
       "      <td>C202416</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PDV     SKU                                 DESCRICAO Vendas_Total  \\\n",
       "0  12522  51.944     COFFEE DES COL MAN SEDUC TCH PRM 10ml           11   \n",
       "1  20998  77.557  QDB BASE LIQ SUPERMAT COR 06 Q 30ml RPCK            1   \n",
       "2  20858  74.103            GLAMOUR DES COL SEC BL 75ml V4            5   \n",
       "3   5699  47.950                          ZAAD EDP 95ml V6           12   \n",
       "4  20993  50.297               ESTJ DEM LILY ESSENCE 4x4ml            2   \n",
       "\n",
       "     Ciclo  \n",
       "0  C202307  \n",
       "1  C202405  \n",
       "2  C202409  \n",
       "3  C202406  \n",
       "4  C202416  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df_venda_diaria['Ciclo'] = df_venda_diaria['Ciclo'].str.replace(\"C\",\"C20\") \n",
    "\n",
    "df_venda_diaria = df_venda_diaria.rename(columns={'VENDAS_CICLO':'Vendas_Total'})\n",
    "\n",
    "df_venda_diaria.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "a93427da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PDV</th>\n",
       "      <th>SKU</th>\n",
       "      <th>DESCRICAO</th>\n",
       "      <th>Vendas_Total</th>\n",
       "      <th>Ciclo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>11</td>\n",
       "      <td>C202307</td>\n",
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       "      <th>1</th>\n",
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       "      <th>2</th>\n",
       "      <td>20858</td>\n",
       "      <td>74.103</td>\n",
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       "      <td>5</td>\n",
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       "      <th>3</th>\n",
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       "      <td>20993</td>\n",
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       "      <td>ESTJ DEM LILY ESSENCE 4x4ml</td>\n",
       "      <td>2</td>\n",
       "      <td>C202416</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PDV     SKU                                 DESCRICAO  Vendas_Total  \\\n",
       "0  12522  51.944     COFFEE DES COL MAN SEDUC TCH PRM 10ml            11   \n",
       "1  20998  77.557  QDB BASE LIQ SUPERMAT COR 06 Q 30ml RPCK             1   \n",
       "2  20858  74.103            GLAMOUR DES COL SEC BL 75ml V4             5   \n",
       "3   5699  47.950                          ZAAD EDP 95ml V6            12   \n",
       "4  20993  50.297               ESTJ DEM LILY ESSENCE 4x4ml             2   \n",
       "\n",
       "     Ciclo  \n",
       "0  C202307  \n",
       "1  C202405  \n",
       "2  C202409  \n",
       "3  C202406  \n",
       "4  C202416  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_venda_diaria['Vendas_Total'] = df_venda_diaria['Vendas_Total'].str.replace(',', '.', regex=False)\n",
    "\n",
    "df_venda_diaria['Vendas_Total'] = df_venda_diaria['Vendas_Total'].astype('float')\n",
    "\n",
    "df_venda_diaria['Vendas_Total'] = round(df_venda_diaria['Vendas_Total'],0)\n",
    "\n",
    "df_venda_diaria['Vendas_Total'] = df_venda_diaria['Vendas_Total'].astype(str)\n",
    "\n",
    "df_venda_diaria['Vendas_Total'] = (\n",
    "    df_venda_diaria['Vendas_Total']\n",
    "    .str.replace('.0', '', regex=False)\n",
    "    .str.replace('.', '', regex=False)\n",
    "    .astype('Int64')\n",
    ")\n",
    "\n",
    "\n",
    "df_venda_diaria.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "7d973983",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\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",
       "      <th>PDV</th>\n",
       "      <th>SKU</th>\n",
       "      <th>DESCRICAO</th>\n",
       "      <th>Vendas_Total</th>\n",
       "      <th>Ciclo</th>\n",
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       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [PDV, SKU, DESCRICAO, Vendas_Total, Ciclo]\n",
       "Index: []"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_venda_diaria[(df_venda_diaria['PDV']==14668) & (df_venda_diaria['SKU']=='85096')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "6ddec856",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>SKU</th>\n",
       "      <th>DESCRICAO</th>\n",
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       "      <th>Ciclo</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>20998</td>\n",
       "      <td>77.557</td>\n",
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       "      <td>1</td>\n",
       "      <td>C202405</td>\n",
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       "      <th>2</th>\n",
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       "      <th>3</th>\n",
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       "      <td>50.297</td>\n",
       "      <td>ESTJ DEM LILY ESSENCE 4x4ml</td>\n",
       "      <td>2</td>\n",
       "      <td>C202416</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PDV     SKU                                 DESCRICAO  Vendas_Total  \\\n",
       "0  12522  51.944     COFFEE DES COL MAN SEDUC TCH PRM 10ml            11   \n",
       "1  20998  77.557  QDB BASE LIQ SUPERMAT COR 06 Q 30ml RPCK             1   \n",
       "2  20858  74.103            GLAMOUR DES COL SEC BL 75ml V4             5   \n",
       "3   5699  47.950                          ZAAD EDP 95ml V6            12   \n",
       "4  20993  50.297               ESTJ DEM LILY ESSENCE 4x4ml             2   \n",
       "\n",
       "     Ciclo  \n",
       "0  C202307  \n",
       "1  C202405  \n",
       "2  C202409  \n",
       "3  C202406  \n",
       "4  C202416  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_venda_diaria2 = df_venda_diaria.pivot_table(\n",
    "    index=[\"PDV\", \"SKU\", \"DESCRICAO\"],\n",
    "    columns=\"Ciclo\",\n",
    "    values=\"Vendas_Total\",\n",
    "    fill_value=0\n",
    ").reset_index()\n",
    "\n",
    "# Se quiser, reorganize as colunas colocando os ciclos ao final\n",
    "df_venda_diaria.columns.name = None\n",
    "\n",
    "df_venda_diaria.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "882e68aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['PDV', 'SKU', 'DESCRICAO', 'Vendas_Total', 'Ciclo'], dtype='object')"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_venda_diaria.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "0c288d75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PDV</th>\n",
       "      <th>SKU</th>\n",
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       "      <th>Ciclo</th>\n",
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       "      <th>0</th>\n",
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       "      <th>2</th>\n",
       "      <td>20858</td>\n",
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       "      <td>GLAMOUR DES COL SEC BL 75ml V4</td>\n",
       "      <td>5</td>\n",
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       "      <th>3</th>\n",
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       "    <tr>\n",
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       "      <td>20993</td>\n",
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       "      <td>2</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>1663315</th>\n",
       "      <td>20996</td>\n",
       "      <td>83.039</td>\n",
       "      <td>QUASAR DES COL RUSH 100ml</td>\n",
       "      <td>1</td>\n",
       "      <td>C202415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1663316</th>\n",
       "      <td>20970</td>\n",
       "      <td>52.025</td>\n",
       "      <td>BOTI BABY SAB LIQ GLIC V2 400ml</td>\n",
       "      <td>6</td>\n",
       "      <td>C202511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1663317</th>\n",
       "      <td>20996</td>\n",
       "      <td>93.069</td>\n",
       "      <td>LA PIEL D/COL SPR CP PER AMBR DOUR 200ml</td>\n",
       "      <td>10</td>\n",
       "      <td>C202414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1663318</th>\n",
       "      <td>13427</td>\n",
       "      <td>51.279</td>\n",
       "      <td>MAKE B BAS LIQ C/ GLYC TX 140 30g</td>\n",
       "      <td>1</td>\n",
       "      <td>C202309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1663319</th>\n",
       "      <td>21278</td>\n",
       "      <td>52.014</td>\n",
       "      <td>CJ FLAC OUI EDP ICONIQUE INTENSE 3x1ml</td>\n",
       "      <td>2</td>\n",
       "      <td>C202511</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1663320 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           PDV     SKU                                 DESCRICAO  \\\n",
       "0        12522  51.944     COFFEE DES COL MAN SEDUC TCH PRM 10ml   \n",
       "1        20998  77.557  QDB BASE LIQ SUPERMAT COR 06 Q 30ml RPCK   \n",
       "2        20858  74.103            GLAMOUR DES COL SEC BL 75ml V4   \n",
       "3         5699  47.950                          ZAAD EDP 95ml V6   \n",
       "4        20993  50.297               ESTJ DEM LILY ESSENCE 4x4ml   \n",
       "...        ...     ...                                       ...   \n",
       "1663315  20996  83.039                 QUASAR DES COL RUSH 100ml   \n",
       "1663316  20970  52.025           BOTI BABY SAB LIQ GLIC V2 400ml   \n",
       "1663317  20996  93.069  LA PIEL D/COL SPR CP PER AMBR DOUR 200ml   \n",
       "1663318  13427  51.279         MAKE B BAS LIQ C/ GLYC TX 140 30g   \n",
       "1663319  21278  52.014    CJ FLAC OUI EDP ICONIQUE INTENSE 3x1ml   \n",
       "\n",
       "         Vendas_Total    Ciclo  \n",
       "0                  11  C202307  \n",
       "1                   1  C202405  \n",
       "2                   5  C202409  \n",
       "3                  12  C202406  \n",
       "4                   2  C202416  \n",
       "...               ...      ...  \n",
       "1663315             1  C202415  \n",
       "1663316             6  C202511  \n",
       "1663317            10  C202414  \n",
       "1663318             1  C202309  \n",
       "1663319             2  C202511  \n",
       "\n",
       "[1663320 rows x 5 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_venda_diaria"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "c7ddaf20",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_venda_diaria['PDV'] = df_venda_diaria['Unidade de Negócio'].str.split(\"-\").str[0].str.strip()\n",
    "\n",
    "#df_venda_diaria['Dia'] = pd.to_datetime(df_venda_diaria['Dia'], format='%d/%m/%Y')\n",
    "\n",
    "#df_venda_diaria = pd.merge(left=df_venda_diaria,right=calendario[['Ciclo','Date']],left_on='Dia',right_on='Date',how='inner')\n",
    "\n",
    "#df_venda_diaria = df_venda_diaria.drop(columns='Date')\n",
    "\n",
    "#df_venda_diaria.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "7119556a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 'Dia' já está em formato datetime, então renomeamos para 'Data' diretamente\n",
    "# ou apenas usamos 'Dia' como referência de data\n",
    "\n",
    "# Ordena o DataFrame para garantir que a cumulativa funcione corretamente\n",
    "#df_venda_diaria = df_venda_diaria.sort_values(by=['Unidade de Negócio', 'Código do Produto', 'Dia'])\n",
    "\n",
    "# Calcula a quantidade acumulada até o dia para cada grupo\n",
    "#df_venda_diaria['Quantidade Acumulada'] = (df_venda_diaria.groupby(['Unidade de Negócio', 'Código do Produto'])['Quantidade'].cumsum())  # acumulado por grupo até a data da linha\n",
    "\n",
    "#df_venda_diaria.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "c707a1b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_venda_diaria = df_venda_diaria.drop_duplicates()\n",
    "\n",
    "#df_venda_agrupado = df_venda_diaria.fillna(0).groupby(['PDV', 'Código do Produto','Ciclo'])['Quantidade Acumulada'].max().reset_index()\n",
    "#df_venda_agrupado"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "083ff829",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_venda_agrupado[(df_venda_agrupado['Ciclo']=='C202213')&(df_venda_agrupado['Código do Produto']==81054)&(df_venda_agrupado['PDV']=='20994')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "59707396",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_venda_agrupado[['Ciclo','Código do Produto','PDV']].dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "bdf6abbb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CICLO SIMILAR      object\n",
       "PRODUTO SIMILAR     Int64\n",
       "PDV                 int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final[['CICLO SIMILAR','PRODUTO SIMILAR','PDV']].dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "dc452c72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1527, 60)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final = pd.merge(left=df_final, right=filtered_calendario[['Ciclo','INICIO CICLO','FIM CICLO','DURAÇÃO','match','dias_ate_inicio']], right_on='match',left_on='MATCH',how='left')\n",
    "df_final.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "c260e0e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_final = df_final.drop(columns=['PDV DESC','status','SKU','Descrição','Lançamento','Item analisado','Planograma','Quantidade por caixa'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "c9de258b",
   "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>PRODUTO LANÇAMENTO</th>\n",
       "      <th>DESCRIÇÃO DO LANÇAMENTO</th>\n",
       "      <th>PRODUTO SIMILAR</th>\n",
       "      <th>DESCRIÇÃO SIMILAR</th>\n",
       "      <th>CICLO SIMILAR</th>\n",
       "      <th>FOCO</th>\n",
       "      <th>IAF</th>\n",
       "      <th>CATEGORIA</th>\n",
       "      <th>MARCA</th>\n",
       "      <th>% CONSUMIDOR</th>\n",
       "      <th>...</th>\n",
       "      <th>C202511</th>\n",
       "      <th>C202512</th>\n",
       "      <th>C202513</th>\n",
       "      <th>CRESCIMENTO</th>\n",
       "      <th>Ciclo</th>\n",
       "      <th>INICIO CICLO</th>\n",
       "      <th>FIM CICLO</th>\n",
       "      <th>DURAÇÃO</th>\n",
       "      <th>match</th>\n",
       "      <th>dias_ate_inicio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0382</td>\n",
       "      <td>C202516</td>\n",
       "      <td>2025-11-03</td>\n",
       "      <td>2025-11-30</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.0456</td>\n",
       "      <td>C202516</td>\n",
       "      <td>2025-11-03</td>\n",
       "      <td>2025-11-30</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0433</td>\n",
       "      <td>C202516</td>\n",
       "      <td>2025-11-03</td>\n",
       "      <td>2025-11-30</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.0701</td>\n",
       "      <td>C202516</td>\n",
       "      <td>2025-11-03</td>\n",
       "      <td>2025-11-30</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0421</td>\n",
       "      <td>C202516</td>\n",
       "      <td>2025-11-03</td>\n",
       "      <td>2025-11-30</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 60 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   PRODUTO LANÇAMENTO                   DESCRIÇÃO DO LANÇAMENTO  \\\n",
       "0               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "1               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "2               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "3               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "4               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "\n",
       "   PRODUTO SIMILAR                         DESCRIÇÃO SIMILAR CICLO SIMILAR  \\\n",
       "0            57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "1            57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "2            57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "3            57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "4            57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "\n",
       "  FOCO  IAF            CATEGORIA MARCA % CONSUMIDOR  ... C202511 C202512  \\\n",
       "0  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...     2.0     0.0   \n",
       "1  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...    24.0     1.0   \n",
       "2  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...     7.0     1.0   \n",
       "3  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...     1.0     1.0   \n",
       "4  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...     0.0     2.0   \n",
       "\n",
       "  C202513 CRESCIMENTO    Ciclo  INICIO CICLO  FIM CICLO DURAÇÃO match  \\\n",
       "0     0.0      0.0382  C202516    2025-11-03 2025-11-30      28     1   \n",
       "1     0.0     -0.0456  C202516    2025-11-03 2025-11-30      28     1   \n",
       "2     0.0      0.0433  C202516    2025-11-03 2025-11-30      28     1   \n",
       "3     0.0     -0.0701  C202516    2025-11-03 2025-11-30      28     1   \n",
       "4     0.0      0.0421  C202516    2025-11-03 2025-11-30      28     1   \n",
       "\n",
       "  dias_ate_inicio  \n",
       "0              59  \n",
       "1              59  \n",
       "2              59  \n",
       "3              59  \n",
       "4              59  \n",
       "\n",
       "[5 rows x 60 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "8a05450c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final = pd.merge(left=df_final, right=calendario[['Ciclo','INICIO CICLO','FIM CICLO','DURAÇÃO']], right_on='Ciclo',left_on='CICLO SIMILAR',how='left')\n",
    "df_final.shape\n",
    "\n",
    "df_final = df_final.drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "cc65edab",
   "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>PDV</th>\n",
       "      <th>SKU</th>\n",
       "      <th>DESCRICAO</th>\n",
       "      <th>Vendas Ciclo Lançamento</th>\n",
       "      <th>Ciclo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12522</td>\n",
       "      <td>51.944</td>\n",
       "      <td>COFFEE DES COL MAN SEDUC TCH PRM 10ml</td>\n",
       "      <td>11</td>\n",
       "      <td>C202307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20998</td>\n",
       "      <td>77.557</td>\n",
       "      <td>QDB BASE LIQ SUPERMAT COR 06 Q 30ml RPCK</td>\n",
       "      <td>1</td>\n",
       "      <td>C202405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20858</td>\n",
       "      <td>74.103</td>\n",
       "      <td>GLAMOUR DES COL SEC BL 75ml V4</td>\n",
       "      <td>5</td>\n",
       "      <td>C202409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5699</td>\n",
       "      <td>47.950</td>\n",
       "      <td>ZAAD EDP 95ml V6</td>\n",
       "      <td>12</td>\n",
       "      <td>C202406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20993</td>\n",
       "      <td>50.297</td>\n",
       "      <td>ESTJ DEM LILY ESSENCE 4x4ml</td>\n",
       "      <td>2</td>\n",
       "      <td>C202416</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PDV     SKU                                 DESCRICAO  \\\n",
       "0  12522  51.944     COFFEE DES COL MAN SEDUC TCH PRM 10ml   \n",
       "1  20998  77.557  QDB BASE LIQ SUPERMAT COR 06 Q 30ml RPCK   \n",
       "2  20858  74.103            GLAMOUR DES COL SEC BL 75ml V4   \n",
       "3   5699  47.950                          ZAAD EDP 95ml V6   \n",
       "4  20993  50.297               ESTJ DEM LILY ESSENCE 4x4ml   \n",
       "\n",
       "   Vendas Ciclo Lançamento    Ciclo  \n",
       "0                       11  C202307  \n",
       "1                        1  C202405  \n",
       "2                        5  C202409  \n",
       "3                       12  C202406  \n",
       "4                        2  C202416  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "df_venda_diaria = df_venda_diaria.rename(columns={'Vendas_Total':'Vendas Ciclo Lançamento'})\n",
    "df_venda_diaria.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "6367ac21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        C202415\n",
       "21       C202415\n",
       "42       C202415\n",
       "63       C202415\n",
       "84       C202415\n",
       "          ...   \n",
       "25683          0\n",
       "25684          0\n",
       "25685          0\n",
       "25686          0\n",
       "25687          0\n",
       "Name: CICLO SIMILAR, Length: 1527, dtype: object"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final['CICLO SIMILAR'] = df_final['CICLO SIMILAR'].fillna('0')\n",
    "df_final['CICLO SIMILAR'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "b0af59cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CICLO SIMILAR</th>\n",
       "      <th>PRODUTO SIMILAR</th>\n",
       "      <th>PDV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>C202415</td>\n",
       "      <td>57890</td>\n",
       "      <td>12522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>C202415</td>\n",
       "      <td>57890</td>\n",
       "      <td>12817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>C202415</td>\n",
       "      <td>57890</td>\n",
       "      <td>12818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>C202415</td>\n",
       "      <td>57890</td>\n",
       "      <td>12820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>C202415</td>\n",
       "      <td>57890</td>\n",
       "      <td>12823</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   CICLO SIMILAR  PRODUTO SIMILAR    PDV\n",
       "0        C202415            57890  12522\n",
       "21       C202415            57890  12817\n",
       "42       C202415            57890  12818\n",
       "63       C202415            57890  12820\n",
       "84       C202415            57890  12823"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final[['CICLO SIMILAR','PRODUTO SIMILAR','PDV']].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "72925ca7",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "df_final['PRODUTO SIMILAR'] = df_final['PRODUTO SIMILAR'].astype('Int64')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "8b0bb174",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['PRODUTO LANÇAMENTO', 'DESCRIÇÃO DO LANÇAMENTO', 'PRODUTO SIMILAR',\n",
       "       'DESCRIÇÃO SIMILAR', 'CICLO SIMILAR', 'FOCO', 'IAF', 'CATEGORIA',\n",
       "       'MARCA', '% CONSUMIDOR', 'MECANICA CONSUMIDOR', '% REVENDEDOR',\n",
       "       'MECANICA REVENDEDOR', 'TIPO DE PRODUTO', 'MATCH', 'PDV', 'CANAL',\n",
       "       'DESCRIÇÃO PDV', 'PDV DESC', 'UF', 'ANALISTA', 'SUPERVISOR', 'STATUS',\n",
       "       'SKU', 'curva', 'categoria', 'proj_mar', 'proj_mar+1', 'ESTOQUE ATUAL',\n",
       "       'ESTOQUE EM TRANSITO', 'PEDIDO PENDENTE', 'DDV PREVISTO', 'preço',\n",
       "       'SKU_FINAL', 'DESCRICAO', 'C202413', 'C202414', 'C202415', 'C202416',\n",
       "       'C202417', 'C202501', 'C202502', 'C202503', 'C202504', 'C202505',\n",
       "       'C202506', 'C202507', 'C202508', 'C202509', 'C202510', 'C202511',\n",
       "       'C202512', 'C202513', 'CRESCIMENTO', 'Ciclo_x', 'INICIO CICLO_x',\n",
       "       'FIM CICLO_x', 'DURAÇÃO_x', 'match', 'dias_ate_inicio', 'Ciclo_y',\n",
       "       'INICIO CICLO_y', 'FIM CICLO_y', 'DURAÇÃO_y'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "3d924087",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        57890\n",
       "21       57890\n",
       "42       57890\n",
       "63       57890\n",
       "84       57890\n",
       "         ...  \n",
       "25683    58132\n",
       "25684    58132\n",
       "25685    58132\n",
       "25686    58132\n",
       "25687    58132\n",
       "Name: PRODUTO SIMILAR, Length: 1527, dtype: Int64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final['PRODUTO SIMILAR']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "c34b541a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PDV</th>\n",
       "      <th>SKU</th>\n",
       "      <th>DESCRICAO</th>\n",
       "      <th>Vendas Ciclo Lançamento</th>\n",
       "      <th>Ciclo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12522</td>\n",
       "      <td>51.944</td>\n",
       "      <td>COFFEE DES COL MAN SEDUC TCH PRM 10ml</td>\n",
       "      <td>11</td>\n",
       "      <td>C202307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20998</td>\n",
       "      <td>77.557</td>\n",
       "      <td>QDB BASE LIQ SUPERMAT COR 06 Q 30ml RPCK</td>\n",
       "      <td>1</td>\n",
       "      <td>C202405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20858</td>\n",
       "      <td>74.103</td>\n",
       "      <td>GLAMOUR DES COL SEC BL 75ml V4</td>\n",
       "      <td>5</td>\n",
       "      <td>C202409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5699</td>\n",
       "      <td>47.950</td>\n",
       "      <td>ZAAD EDP 95ml V6</td>\n",
       "      <td>12</td>\n",
       "      <td>C202406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20993</td>\n",
       "      <td>50.297</td>\n",
       "      <td>ESTJ DEM LILY ESSENCE 4x4ml</td>\n",
       "      <td>2</td>\n",
       "      <td>C202416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1663315</th>\n",
       "      <td>20996</td>\n",
       "      <td>83.039</td>\n",
       "      <td>QUASAR DES COL RUSH 100ml</td>\n",
       "      <td>1</td>\n",
       "      <td>C202415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1663316</th>\n",
       "      <td>20970</td>\n",
       "      <td>52.025</td>\n",
       "      <td>BOTI BABY SAB LIQ GLIC V2 400ml</td>\n",
       "      <td>6</td>\n",
       "      <td>C202511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1663317</th>\n",
       "      <td>20996</td>\n",
       "      <td>93.069</td>\n",
       "      <td>LA PIEL D/COL SPR CP PER AMBR DOUR 200ml</td>\n",
       "      <td>10</td>\n",
       "      <td>C202414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1663318</th>\n",
       "      <td>13427</td>\n",
       "      <td>51.279</td>\n",
       "      <td>MAKE B BAS LIQ C/ GLYC TX 140 30g</td>\n",
       "      <td>1</td>\n",
       "      <td>C202309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1663319</th>\n",
       "      <td>21278</td>\n",
       "      <td>52.014</td>\n",
       "      <td>CJ FLAC OUI EDP ICONIQUE INTENSE 3x1ml</td>\n",
       "      <td>2</td>\n",
       "      <td>C202511</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1663320 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           PDV     SKU                                 DESCRICAO  \\\n",
       "0        12522  51.944     COFFEE DES COL MAN SEDUC TCH PRM 10ml   \n",
       "1        20998  77.557  QDB BASE LIQ SUPERMAT COR 06 Q 30ml RPCK   \n",
       "2        20858  74.103            GLAMOUR DES COL SEC BL 75ml V4   \n",
       "3         5699  47.950                          ZAAD EDP 95ml V6   \n",
       "4        20993  50.297               ESTJ DEM LILY ESSENCE 4x4ml   \n",
       "...        ...     ...                                       ...   \n",
       "1663315  20996  83.039                 QUASAR DES COL RUSH 100ml   \n",
       "1663316  20970  52.025           BOTI BABY SAB LIQ GLIC V2 400ml   \n",
       "1663317  20996  93.069  LA PIEL D/COL SPR CP PER AMBR DOUR 200ml   \n",
       "1663318  13427  51.279         MAKE B BAS LIQ C/ GLYC TX 140 30g   \n",
       "1663319  21278  52.014    CJ FLAC OUI EDP ICONIQUE INTENSE 3x1ml   \n",
       "\n",
       "         Vendas Ciclo Lançamento    Ciclo  \n",
       "0                             11  C202307  \n",
       "1                              1  C202405  \n",
       "2                              5  C202409  \n",
       "3                             12  C202406  \n",
       "4                              2  C202416  \n",
       "...                          ...      ...  \n",
       "1663315                        1  C202415  \n",
       "1663316                        6  C202511  \n",
       "1663317                       10  C202414  \n",
       "1663318                        1  C202309  \n",
       "1663319                        2  C202511  \n",
       "\n",
       "[1663320 rows x 5 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_venda_diaria"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "1efff472",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PDV</th>\n",
       "      <th>SKU</th>\n",
       "      <th>DESCRICAO</th>\n",
       "      <th>Vendas Ciclo Lançamento</th>\n",
       "      <th>Ciclo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12522</td>\n",
       "      <td>51944</td>\n",
       "      <td>COFFEE DES COL MAN SEDUC TCH PRM 10ml</td>\n",
       "      <td>11</td>\n",
       "      <td>C202307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20998</td>\n",
       "      <td>77557</td>\n",
       "      <td>QDB BASE LIQ SUPERMAT COR 06 Q 30ml RPCK</td>\n",
       "      <td>1</td>\n",
       "      <td>C202405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20858</td>\n",
       "      <td>74103</td>\n",
       "      <td>GLAMOUR DES COL SEC BL 75ml V4</td>\n",
       "      <td>5</td>\n",
       "      <td>C202409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5699</td>\n",
       "      <td>47950</td>\n",
       "      <td>ZAAD EDP 95ml V6</td>\n",
       "      <td>12</td>\n",
       "      <td>C202406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20993</td>\n",
       "      <td>50297</td>\n",
       "      <td>ESTJ DEM LILY ESSENCE 4x4ml</td>\n",
       "      <td>2</td>\n",
       "      <td>C202416</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PDV    SKU                                 DESCRICAO  \\\n",
       "0  12522  51944     COFFEE DES COL MAN SEDUC TCH PRM 10ml   \n",
       "1  20998  77557  QDB BASE LIQ SUPERMAT COR 06 Q 30ml RPCK   \n",
       "2  20858  74103            GLAMOUR DES COL SEC BL 75ml V4   \n",
       "3   5699  47950                          ZAAD EDP 95ml V6   \n",
       "4  20993  50297               ESTJ DEM LILY ESSENCE 4x4ml   \n",
       "\n",
       "   Vendas Ciclo Lançamento    Ciclo  \n",
       "0                       11  C202307  \n",
       "1                        1  C202405  \n",
       "2                        5  C202409  \n",
       "3                       12  C202406  \n",
       "4                        2  C202416  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_venda_diaria['SKU'] = df_venda_diaria['SKU'].astype('str')\n",
    "\n",
    "df_venda_diaria['SKU'] = df_venda_diaria['SKU'].str.replace('.','')\n",
    "\n",
    "df_venda_diaria.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "62ea79f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final['PRODUTO SIMILAR'] = df_final['PRODUTO SIMILAR'].astype('str')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "c5383011",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th>PRODUTO LANÇAMENTO</th>\n",
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       "      <th>DESCRIÇÃO SIMILAR</th>\n",
       "      <th>CICLO SIMILAR</th>\n",
       "      <th>FOCO</th>\n",
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       "      <th>MARCA</th>\n",
       "      <th>% CONSUMIDOR</th>\n",
       "      <th>...</th>\n",
       "      <th>Ciclo_x</th>\n",
       "      <th>INICIO CICLO_x</th>\n",
       "      <th>FIM CICLO_x</th>\n",
       "      <th>DURAÇÃO_x</th>\n",
       "      <th>match</th>\n",
       "      <th>dias_ate_inicio</th>\n",
       "      <th>Ciclo_y</th>\n",
       "      <th>INICIO CICLO_y</th>\n",
       "      <th>FIM CICLO_y</th>\n",
       "      <th>DURAÇÃO_y</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>C202516</td>\n",
       "      <td>2025-11-03</td>\n",
       "      <td>2025-11-30</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2024-10-14</td>\n",
       "      <td>2024-11-03</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>C202516</td>\n",
       "      <td>2025-11-03</td>\n",
       "      <td>2025-11-30</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2024-10-14</td>\n",
       "      <td>2024-11-03</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>C202516</td>\n",
       "      <td>2025-11-03</td>\n",
       "      <td>2025-11-30</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2024-10-14</td>\n",
       "      <td>2024-11-03</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>C202516</td>\n",
       "      <td>2025-11-03</td>\n",
       "      <td>2025-11-30</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2024-10-14</td>\n",
       "      <td>2024-11-03</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>C202516</td>\n",
       "      <td>2025-11-03</td>\n",
       "      <td>2025-11-30</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2024-10-14</td>\n",
       "      <td>2024-11-03</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 64 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    PRODUTO LANÇAMENTO                   DESCRIÇÃO DO LANÇAMENTO  \\\n",
       "0                89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "21               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "42               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "63               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "84               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "\n",
       "   PRODUTO SIMILAR                         DESCRIÇÃO SIMILAR CICLO SIMILAR  \\\n",
       "0            57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "21           57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "42           57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "63           57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "84           57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "\n",
       "   FOCO  IAF            CATEGORIA MARCA % CONSUMIDOR  ...  Ciclo_x  \\\n",
       "0   Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...  C202516   \n",
       "21  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...  C202516   \n",
       "42  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...  C202516   \n",
       "63  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...  C202516   \n",
       "84  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...  C202516   \n",
       "\n",
       "   INICIO CICLO_x FIM CICLO_x DURAÇÃO_x  match  dias_ate_inicio  Ciclo_y  \\\n",
       "0      2025-11-03  2025-11-30        28      1               59  C202415   \n",
       "21     2025-11-03  2025-11-30        28      1               59  C202415   \n",
       "42     2025-11-03  2025-11-30        28      1               59  C202415   \n",
       "63     2025-11-03  2025-11-30        28      1               59  C202415   \n",
       "84     2025-11-03  2025-11-30        28      1               59  C202415   \n",
       "\n",
       "   INICIO CICLO_y FIM CICLO_y DURAÇÃO_y  \n",
       "0      2024-10-14  2024-11-03      21.0  \n",
       "21     2024-10-14  2024-11-03      21.0  \n",
       "42     2024-10-14  2024-11-03      21.0  \n",
       "63     2024-10-14  2024-11-03      21.0  \n",
       "84     2024-10-14  2024-11-03      21.0  \n",
       "\n",
       "[5 rows x 64 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "c5cd5f42",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final = pd.merge(left=df_final, right = df_venda_diaria[['PDV','SKU','Ciclo','Vendas Ciclo Lançamento']], right_on=['Ciclo','SKU','PDV'],left_on=['CICLO SIMILAR','PRODUTO SIMILAR','PDV'],how='left')\n",
    "\n",
    "df_final = df_final.drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "4f22b782",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
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       "        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>PRODUTO LANÇAMENTO</th>\n",
       "      <th>DESCRIÇÃO DO LANÇAMENTO</th>\n",
       "      <th>PRODUTO SIMILAR</th>\n",
       "      <th>DESCRIÇÃO SIMILAR</th>\n",
       "      <th>CICLO SIMILAR</th>\n",
       "      <th>FOCO</th>\n",
       "      <th>IAF</th>\n",
       "      <th>CATEGORIA</th>\n",
       "      <th>MARCA</th>\n",
       "      <th>% CONSUMIDOR</th>\n",
       "      <th>...</th>\n",
       "      <th>DURAÇÃO_x</th>\n",
       "      <th>match</th>\n",
       "      <th>dias_ate_inicio</th>\n",
       "      <th>Ciclo_y</th>\n",
       "      <th>INICIO CICLO_y</th>\n",
       "      <th>FIM CICLO_y</th>\n",
       "      <th>DURAÇÃO_y</th>\n",
       "      <th>SKU_y</th>\n",
       "      <th>Ciclo</th>\n",
       "      <th>Vendas Ciclo Lançamento</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2024-10-14</td>\n",
       "      <td>2024-11-03</td>\n",
       "      <td>21.0</td>\n",
       "      <td>57890</td>\n",
       "      <td>C202415</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2024-10-14</td>\n",
       "      <td>2024-11-03</td>\n",
       "      <td>21.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2024-10-14</td>\n",
       "      <td>2024-11-03</td>\n",
       "      <td>21.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2024-10-14</td>\n",
       "      <td>2024-11-03</td>\n",
       "      <td>21.0</td>\n",
       "      <td>57890</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2024-10-14</td>\n",
       "      <td>2024-11-03</td>\n",
       "      <td>21.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 67 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   PRODUTO LANÇAMENTO                   DESCRIÇÃO DO LANÇAMENTO  \\\n",
       "0               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "1               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "2               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "3               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "4               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "\n",
       "  PRODUTO SIMILAR                         DESCRIÇÃO SIMILAR CICLO SIMILAR  \\\n",
       "0           57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "1           57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "2           57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "3           57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "4           57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "\n",
       "  FOCO  IAF            CATEGORIA MARCA % CONSUMIDOR  ... DURAÇÃO_x match  \\\n",
       "0  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...        28     1   \n",
       "1  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...        28     1   \n",
       "2  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...        28     1   \n",
       "3  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...        28     1   \n",
       "4  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...        28     1   \n",
       "\n",
       "  dias_ate_inicio  Ciclo_y  INICIO CICLO_y  FIM CICLO_y DURAÇÃO_y  SKU_y  \\\n",
       "0              59  C202415      2024-10-14   2024-11-03      21.0  57890   \n",
       "1              59  C202415      2024-10-14   2024-11-03      21.0    NaN   \n",
       "2              59  C202415      2024-10-14   2024-11-03      21.0    NaN   \n",
       "3              59  C202415      2024-10-14   2024-11-03      21.0  57890   \n",
       "4              59  C202415      2024-10-14   2024-11-03      21.0    NaN   \n",
       "\n",
       "     Ciclo Vendas Ciclo Lançamento  \n",
       "0  C202415                       1  \n",
       "1      NaN                    <NA>  \n",
       "2      NaN                    <NA>  \n",
       "3  C202415                       2  \n",
       "4      NaN                    <NA>  \n",
       "\n",
       "[5 rows x 67 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "db516beb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final.to_excel(r'C:\\Users\\joao.herculano\\Documents\\teste.xlsx',index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "bde12ed6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final = df_final[df_final['PRODUTO LANÇAMENTO'].notna()]\n",
    "df_final['Vendas Ciclo Lançamento'] = df_final['Vendas Ciclo Lançamento'].fillna(0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "69c88d20",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.int64(19)"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final['PDV'].value_counts().min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "f5206f50",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ESTOQUE EM TRANSITO', 'PEDIDO PENDENTE', 'DDV PREVISTO', 'preço',\n",
       "       'SKU_FINAL', 'DESCRICAO', 'C202413', 'C202414', 'C202415', 'C202416',\n",
       "       'C202417', 'C202501', 'C202502', 'C202503', 'C202504', 'C202505',\n",
       "       'C202506'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.columns[29:46]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "5e33d293",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_jacobina = pd.read_excel(r\"C:\\Users\\joao.herculano\\GRUPO GINSENG\\Assistência Suprimentos - 2025\\REGIÃO JACOBINA\\draft unificado.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "4d23ff5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_jacobina = df_jacobina[['PDV', 'SKU','202408', '202409',\n",
    "       '202410', '202411', '202412', '202413', '202414', '202415', '202416',\n",
    "       '202417', '202501', '202502', '202503', '202504', '202505', '202506',\n",
    "       '202507']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "5adc5831",
   "metadata": {},
   "outputs": [],
   "source": [
    "ciclos = [\n",
    "    '202408', '202409', '202410', '202411', '202412', '202413',\n",
    "    '202414', '202415', '202416', '202417', '202501', '202502',\n",
    "    '202503', '202504', '202505', '202506', '202507']\n",
    "\n",
    "df_jacobina[ciclos] = df_jacobina[ciclos].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "d3dc8c38",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PDV</th>\n",
       "      <th>SKU</th>\n",
       "      <th>202408</th>\n",
       "      <th>202409</th>\n",
       "      <th>202410</th>\n",
       "      <th>202411</th>\n",
       "      <th>202412</th>\n",
       "      <th>202413</th>\n",
       "      <th>202414</th>\n",
       "      <th>202415</th>\n",
       "      <th>202416</th>\n",
       "      <th>202417</th>\n",
       "      <th>202501</th>\n",
       "      <th>202502</th>\n",
       "      <th>202503</th>\n",
       "      <th>202504</th>\n",
       "      <th>202505</th>\n",
       "      <th>202506</th>\n",
       "      <th>202507</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>24269</td>\n",
       "      <td>49014</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>24268</td>\n",
       "      <td>49014</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>24269</td>\n",
       "      <td>49016</td>\n",
       "      <td>36</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24268</td>\n",
       "      <td>49016</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24269</td>\n",
       "      <td>48141</td>\n",
       "      <td>32</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>95</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>41</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>67</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PDV    SKU  202408  202409  202410  202411  202412  202413  202414  \\\n",
       "0  24269  49014       1       0       5       1       1       1       2   \n",
       "1  24268  49014       1       0       4       4       2       5       1   \n",
       "2  24269  49016      36       3       1       1       1       0      14   \n",
       "3  24268  49016      12       3       1       2       2       2       0   \n",
       "4  24269  48141      32       2       3      95       3       2      41   \n",
       "\n",
       "   202415  202416  202417  202501  202502  202503  202504  202505  202506  \\\n",
       "0       2       1       1       3       0       4       0       2       1   \n",
       "1       3       4       4       3       0       2       4       2       0   \n",
       "2       2       2       1       1      19       1       2       2      10   \n",
       "3       0       3      11       4       3       0       4       2       1   \n",
       "4       3       3       1       1       1       0      67       4      10   \n",
       "\n",
       "   202507  \n",
       "0       0  \n",
       "1       1  \n",
       "2       0  \n",
       "3       0  \n",
       "4       2  "
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_jacobina.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "4169aba0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PRODUTO LANÇAMENTO</th>\n",
       "      <th>DESCRIÇÃO DO LANÇAMENTO</th>\n",
       "      <th>PRODUTO SIMILAR</th>\n",
       "      <th>DESCRIÇÃO SIMILAR</th>\n",
       "      <th>CICLO SIMILAR</th>\n",
       "      <th>FOCO</th>\n",
       "      <th>IAF</th>\n",
       "      <th>CATEGORIA</th>\n",
       "      <th>MARCA</th>\n",
       "      <th>% CONSUMIDOR</th>\n",
       "      <th>...</th>\n",
       "      <th>DURAÇÃO_x</th>\n",
       "      <th>match</th>\n",
       "      <th>dias_ate_inicio</th>\n",
       "      <th>Ciclo_y</th>\n",
       "      <th>INICIO CICLO_y</th>\n",
       "      <th>FIM CICLO_y</th>\n",
       "      <th>DURAÇÃO_y</th>\n",
       "      <th>SKU_y</th>\n",
       "      <th>Ciclo</th>\n",
       "      <th>Vendas Ciclo Lançamento</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2024-10-14</td>\n",
       "      <td>2024-11-03</td>\n",
       "      <td>21.0</td>\n",
       "      <td>57890</td>\n",
       "      <td>C202415</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2024-10-14</td>\n",
       "      <td>2024-11-03</td>\n",
       "      <td>21.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2024-10-14</td>\n",
       "      <td>2024-11-03</td>\n",
       "      <td>21.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2024-10-14</td>\n",
       "      <td>2024-11-03</td>\n",
       "      <td>21.0</td>\n",
       "      <td>57890</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>C202415</td>\n",
       "      <td>2024-10-14</td>\n",
       "      <td>2024-11-03</td>\n",
       "      <td>21.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 67 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   PRODUTO LANÇAMENTO                   DESCRIÇÃO DO LANÇAMENTO  \\\n",
       "0               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "1               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "2               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "3               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "4               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "\n",
       "   PRODUTO SIMILAR                         DESCRIÇÃO SIMILAR CICLO SIMILAR  \\\n",
       "0            57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "1            57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "2            57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "3            57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "4            57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "\n",
       "  FOCO  IAF            CATEGORIA MARCA % CONSUMIDOR  ... DURAÇÃO_x match  \\\n",
       "0  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...        28     1   \n",
       "1  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...        28     1   \n",
       "2  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...        28     1   \n",
       "3  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...        28     1   \n",
       "4  Não  Não  CUIDADOS COM A PELE  LILY        15.01  ...        28     1   \n",
       "\n",
       "  dias_ate_inicio  Ciclo_y  INICIO CICLO_y  FIM CICLO_y DURAÇÃO_y  SKU_y  \\\n",
       "0              59  C202415      2024-10-14   2024-11-03      21.0  57890   \n",
       "1              59  C202415      2024-10-14   2024-11-03      21.0    NaN   \n",
       "2              59  C202415      2024-10-14   2024-11-03      21.0    NaN   \n",
       "3              59  C202415      2024-10-14   2024-11-03      21.0  57890   \n",
       "4              59  C202415      2024-10-14   2024-11-03      21.0    NaN   \n",
       "\n",
       "     Ciclo Vendas Ciclo Lançamento  \n",
       "0  C202415                       1  \n",
       "1      NaN                       0  \n",
       "2      NaN                       0  \n",
       "3  C202415                       2  \n",
       "4      NaN                       0  \n",
       "\n",
       "[5 rows x 67 columns]"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final['PRODUTO SIMILAR'] = df_final['PRODUTO SIMILAR'].astype('Int64')\n",
    "\n",
    "df_final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "1c4f5d9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final = pd.merge(left=df_final,right=df_jacobina,left_on=['PRODUTO SIMILAR','PDV'],right_on=['SKU','PDV'],how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "2529e624",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Gera pares de colunas: coluna estática ↔ coluna de histórico\n",
    "pares_validos = [\n",
    "    (ciclo, f'Histórico de Vendas do Ciclo {ciclo}')\n",
    "    for ciclo in ciclos\n",
    "    if ciclo in df_final.columns and f'Histórico de Vendas do Ciclo {ciclo}' in df_final.columns\n",
    "]\n",
    "\n",
    "# Separa os nomes das colunas\n",
    "colunas_estaticas = [c[0] for c in pares_validos]\n",
    "colunas_historico = [c[1] for c in pares_validos]\n",
    "\n",
    "# Aplica a regra: se valor na coluna estática for maior, sobrescreve no histórico\n",
    "for col_estatica, col_hist in zip(colunas_estaticas, colunas_historico):\n",
    "    df_final[col_hist] = df_final[col_estatica].where(\n",
    "        df_final[col_estatica] > df_final[col_hist],\n",
    "        df_final[col_hist]\n",
    "    )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "fc094fae",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>PRODUTO LANÇAMENTO</th>\n",
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       "      <th>MARCA</th>\n",
       "      <th>% CONSUMIDOR</th>\n",
       "      <th>...</th>\n",
       "      <th>202415</th>\n",
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       "      <th>0</th>\n",
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       "      <th>1</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
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       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>89446</td>\n",
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       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>57890</td>\n",
       "      <td>LILY CREM ACET DES HID CPO GARDENIA 250g</td>\n",
       "      <td>C202415</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>LILY</td>\n",
       "      <td>15.01</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1522</th>\n",
       "      <td>58132</td>\n",
       "      <td>CUIDE-SE BEM DELEITE CHOCOLATUDO</td>\n",
       "      <td>58132</td>\n",
       "      <td>CUIDE-SE BEM DELEITE CHOCOLATUDO</td>\n",
       "      <td>0</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>PERFUMARIA</td>\n",
       "      <td>CUIDE-SE BEM</td>\n",
       "      <td>-</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1523</th>\n",
       "      <td>58132</td>\n",
       "      <td>CUIDE-SE BEM DELEITE CHOCOLATUDO</td>\n",
       "      <td>58132</td>\n",
       "      <td>CUIDE-SE BEM DELEITE CHOCOLATUDO</td>\n",
       "      <td>0</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>PERFUMARIA</td>\n",
       "      <td>CUIDE-SE BEM</td>\n",
       "      <td>-</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1524</th>\n",
       "      <td>58132</td>\n",
       "      <td>CUIDE-SE BEM DELEITE CHOCOLATUDO</td>\n",
       "      <td>58132</td>\n",
       "      <td>CUIDE-SE BEM DELEITE CHOCOLATUDO</td>\n",
       "      <td>0</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>PERFUMARIA</td>\n",
       "      <td>CUIDE-SE BEM</td>\n",
       "      <td>-</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1525</th>\n",
       "      <td>58132</td>\n",
       "      <td>CUIDE-SE BEM DELEITE CHOCOLATUDO</td>\n",
       "      <td>58132</td>\n",
       "      <td>CUIDE-SE BEM DELEITE CHOCOLATUDO</td>\n",
       "      <td>0</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>PERFUMARIA</td>\n",
       "      <td>CUIDE-SE BEM</td>\n",
       "      <td>-</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1526</th>\n",
       "      <td>58132</td>\n",
       "      <td>CUIDE-SE BEM DELEITE CHOCOLATUDO</td>\n",
       "      <td>58132</td>\n",
       "      <td>CUIDE-SE BEM DELEITE CHOCOLATUDO</td>\n",
       "      <td>0</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>PERFUMARIA</td>\n",
       "      <td>CUIDE-SE BEM</td>\n",
       "      <td>-</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1527 rows × 85 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      PRODUTO LANÇAMENTO                   DESCRIÇÃO DO LANÇAMENTO  \\\n",
       "0                  89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "1                  89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "2                  89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "3                  89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "4                  89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g   \n",
       "...                  ...                                       ...   \n",
       "1522               58132          CUIDE-SE BEM DELEITE CHOCOLATUDO   \n",
       "1523               58132          CUIDE-SE BEM DELEITE CHOCOLATUDO   \n",
       "1524               58132          CUIDE-SE BEM DELEITE CHOCOLATUDO   \n",
       "1525               58132          CUIDE-SE BEM DELEITE CHOCOLATUDO   \n",
       "1526               58132          CUIDE-SE BEM DELEITE CHOCOLATUDO   \n",
       "\n",
       "      PRODUTO SIMILAR                         DESCRIÇÃO SIMILAR CICLO SIMILAR  \\\n",
       "0               57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "1               57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "2               57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "3               57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "4               57890  LILY CREM ACET DES HID CPO GARDENIA 250g       C202415   \n",
       "...               ...                                       ...           ...   \n",
       "1522            58132          CUIDE-SE BEM DELEITE CHOCOLATUDO             0   \n",
       "1523            58132          CUIDE-SE BEM DELEITE CHOCOLATUDO             0   \n",
       "1524            58132          CUIDE-SE BEM DELEITE CHOCOLATUDO             0   \n",
       "1525            58132          CUIDE-SE BEM DELEITE CHOCOLATUDO             0   \n",
       "1526            58132          CUIDE-SE BEM DELEITE CHOCOLATUDO             0   \n",
       "\n",
       "     FOCO  IAF            CATEGORIA         MARCA % CONSUMIDOR  ... 202415  \\\n",
       "0     Não  Não  CUIDADOS COM A PELE          LILY        15.01  ...    NaN   \n",
       "1     Não  Não  CUIDADOS COM A PELE          LILY        15.01  ...    NaN   \n",
       "2     Não  Não  CUIDADOS COM A PELE          LILY        15.01  ...    NaN   \n",
       "3     Não  Não  CUIDADOS COM A PELE          LILY        15.01  ...    NaN   \n",
       "4     Não  Não  CUIDADOS COM A PELE          LILY        15.01  ...    NaN   \n",
       "...   ...  ...                  ...           ...          ...  ...    ...   \n",
       "1522  Não  Não           PERFUMARIA  CUIDE-SE BEM            -  ...    NaN   \n",
       "1523  Não  Não           PERFUMARIA  CUIDE-SE BEM            -  ...    0.0   \n",
       "1524  Não  Não           PERFUMARIA  CUIDE-SE BEM            -  ...    0.0   \n",
       "1525  Não  Não           PERFUMARIA  CUIDE-SE BEM            -  ...    NaN   \n",
       "1526  Não  Não           PERFUMARIA  CUIDE-SE BEM            -  ...    NaN   \n",
       "\n",
       "     202416 202417 202501  202502  202503 202504 202505 202506 202507  \n",
       "0       NaN    NaN    NaN     NaN     NaN    NaN    NaN    NaN    NaN  \n",
       "1       NaN    NaN    NaN     NaN     NaN    NaN    NaN    NaN    NaN  \n",
       "2       NaN    NaN    NaN     NaN     NaN    NaN    NaN    NaN    NaN  \n",
       "3       NaN    NaN    NaN     NaN     NaN    NaN    NaN    NaN    NaN  \n",
       "4       NaN    NaN    NaN     NaN     NaN    NaN    NaN    NaN    NaN  \n",
       "...     ...    ...    ...     ...     ...    ...    ...    ...    ...  \n",
       "1522    NaN    NaN    NaN     NaN     NaN    NaN    NaN    NaN    NaN  \n",
       "1523    0.0   24.0    0.0     0.0     0.0    0.0    0.0    0.0    0.0  \n",
       "1524    0.0   89.0    0.0     0.0     0.0    0.0    0.0    0.0    0.0  \n",
       "1525    NaN    NaN    NaN     NaN     NaN    NaN    NaN    NaN    NaN  \n",
       "1526    NaN    NaN    NaN     NaN     NaN    NaN    NaN    NaN    NaN  \n",
       "\n",
       "[1527 rows x 85 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "dcff1fcb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final = df_final.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "bebabb9f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['C202413', 'C202414', 'C202415', 'C202416', 'C202417', 'C202501',\n",
       "       'C202502', 'C202503', 'C202504', 'C202505', 'C202506', 'C202507',\n",
       "       'C202508', 'C202509', 'C202510', 'C202511', 'C202512', 'C202513'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.columns[35:53]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "0a1bb832",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.2"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Suponha que os meses estão nas colunas 10 a 26 (17 colunas = 17 meses)\n",
    "colunas_mensais = df_final.columns[35:53]\n",
    "# Passo 1: Soma todas as linhas (itens) por mês → resultado: total por mês\n",
    "soma_mensal = df_final[colunas_mensais].sum()\n",
    "\n",
    "# Passo 2: Calcula a variação percentual de um mês para o outro\n",
    "variacao_mensal = soma_mensal.pct_change()\n",
    "variacao_mensal = variacao_mensal.dropna()\n",
    "\n",
    "variacao_mensal = variacao_mensal[np.isfinite(variacao_mensal)]\n",
    "\n",
    "# Passo 3: Calcula a média da variação (ignorando o primeiro NaN)\n",
    "media_variacao = variacao_mensal[1:].mean()\n",
    "\n",
    "# Calcula média e desvio padrão\n",
    "media = variacao_mensal.mean()\n",
    "desvio = variacao_mensal.std()\n",
    "\n",
    "# Define limite (ex: 2 desvios padrão)\n",
    "limite_superior = media + 2 * desvio\n",
    "limite_inferior = media - 2 * desvio\n",
    "\n",
    "# Filtra dados dentro do limite\n",
    "filtro = variacao_mensal.between(limite_inferior, limite_superior)\n",
    "df_filtrado = variacao_mensal[filtro]\n",
    "CRESCIMENTO = round(df_filtrado.mean(),4)\n",
    "\n",
    "CRESCIMENTO = 0.2 if CRESCIMENTO < 0.2 else CRESCIMENTO\n",
    "\n",
    "df_final['CRESCIMENTO_GERAL'] = CRESCIMENTO\n",
    "\n",
    "CRESCIMENTO\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "a9647c32",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final = df_final.drop(columns='Ciclo_y')\n",
    "\n",
    "df_final = df_final.rename(columns={'Ciclo_x': 'Ciclo',\t'INICIO CICLO_x': 'INICIO CICLO',\t'FIM CICLO_x':'FIM CICLO' ,'DURAÇÃO_x':'DURAÇÃO',\n",
    "                                    \t'INICIO CICLO_y': 'INICIO CICLO SIMILAR' ,\t'FIM CICLO_y': 'FIM CICLO SIMILAR','DURAÇÃO_y':'DURAÇÃO CICLO SIMILAR'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "b107e519",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['C202507', 'C202508', 'C202509', 'C202510', 'C202511', 'C202512',\n",
       "       'C202513'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.columns[46:53]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "8290853c",
   "metadata": {},
   "outputs": [],
   "source": [
    "VENDA_SIMILAR_6_MESES= df_final.columns[46:53]\n",
    "df_final['Pico Vendas Similar Ultimos 6 ciclos'] = df_final[VENDA_SIMILAR_6_MESES].max(axis=1)\n",
    "\n",
    "df_final['Pico Vendas Similar Ultimos 6 ciclos'] = df_final['Pico Vendas Similar Ultimos 6 ciclos'].fillna(0)\n",
    "\n",
    "df_final['MEDIANA DO HISTÓRICO'] = df_final[colunas_mensais].median(axis=1, skipna=True)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "d8b30560",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       1.5\n",
       "1       3.5\n",
       "2       1.0\n",
       "3       1.0\n",
       "4       1.0\n",
       "       ... \n",
       "1522    0.0\n",
       "1523    0.0\n",
       "1524    0.0\n",
       "1525    0.0\n",
       "1526    0.0\n",
       "Length: 1527, dtype: float64"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final[colunas_mensais].median(axis=1, skipna=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "07f043f2",
   "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>CANAL</th>\n",
       "      <th>UF</th>\n",
       "      <th>PRODUTO LANÇAMENTO</th>\n",
       "      <th>med_por_canal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CD</td>\n",
       "      <td>AL</td>\n",
       "      <td>48780</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CD</td>\n",
       "      <td>AL</td>\n",
       "      <td>49154</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CD</td>\n",
       "      <td>AL</td>\n",
       "      <td>49193</td>\n",
       "      <td>19.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CD</td>\n",
       "      <td>AL</td>\n",
       "      <td>49893</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CD</td>\n",
       "      <td>AL</td>\n",
       "      <td>49943</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>VD</td>\n",
       "      <td>SE</td>\n",
       "      <td>88301</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>VD</td>\n",
       "      <td>SE</td>\n",
       "      <td>88730</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>VD</td>\n",
       "      <td>SE</td>\n",
       "      <td>88889</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>VD</td>\n",
       "      <td>SE</td>\n",
       "      <td>88911</td>\n",
       "      <td>5.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>VD</td>\n",
       "      <td>SE</td>\n",
       "      <td>89446</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>247 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    CANAL  UF  PRODUTO LANÇAMENTO  med_por_canal\n",
       "0      CD  AL               48780            3.5\n",
       "1      CD  AL               49154           29.0\n",
       "2      CD  AL               49193           19.5\n",
       "3      CD  AL               49893            0.0\n",
       "4      CD  AL               49943            0.0\n",
       "..    ...  ..                 ...            ...\n",
       "242    VD  SE               88301            2.0\n",
       "243    VD  SE               88730            0.0\n",
       "244    VD  SE               88889            0.0\n",
       "245    VD  SE               88911            5.5\n",
       "246    VD  SE               89446            4.5\n",
       "\n",
       "[247 rows x 4 columns]"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "medi = df_final.groupby(['CANAL','UF','PRODUTO LANÇAMENTO'])['MEDIANA DO HISTÓRICO'].max().reset_index()\n",
    "medi = medi.rename(columns={'MEDIANA DO HISTÓRICO':'med_por_canal'})\n",
    "medi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "94abddce",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_final = pd.merge(left=df_final, right=medi,on=['CANAL','UF'],how='inner')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "c4fbc613",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       EDICAO LIMITADA\n",
       "1       EDICAO LIMITADA\n",
       "2       EDICAO LIMITADA\n",
       "3       EDICAO LIMITADA\n",
       "4       EDICAO LIMITADA\n",
       "             ...       \n",
       "1522            REGULAR\n",
       "1523            REGULAR\n",
       "1524            REGULAR\n",
       "1525            REGULAR\n",
       "1526            REGULAR\n",
       "Name: TIPO DE PRODUTO, Length: 1527, dtype: object"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final['TIPO DE PRODUTO']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "df26720c",
   "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>PDV</th>\n",
       "      <th>SKU</th>\n",
       "      <th>DESCRICAO</th>\n",
       "      <th>Vendas Ciclo Lançamento</th>\n",
       "      <th>Ciclo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12522</td>\n",
       "      <td>51944</td>\n",
       "      <td>COFFEE DES COL MAN SEDUC TCH PRM 10ml</td>\n",
       "      <td>11</td>\n",
       "      <td>C202307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20998</td>\n",
       "      <td>77557</td>\n",
       "      <td>QDB BASE LIQ SUPERMAT COR 06 Q 30ml RPCK</td>\n",
       "      <td>1</td>\n",
       "      <td>C202405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20858</td>\n",
       "      <td>74103</td>\n",
       "      <td>GLAMOUR DES COL SEC BL 75ml V4</td>\n",
       "      <td>5</td>\n",
       "      <td>C202409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5699</td>\n",
       "      <td>47950</td>\n",
       "      <td>ZAAD EDP 95ml V6</td>\n",
       "      <td>12</td>\n",
       "      <td>C202406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20993</td>\n",
       "      <td>50297</td>\n",
       "      <td>ESTJ DEM LILY ESSENCE 4x4ml</td>\n",
       "      <td>2</td>\n",
       "      <td>C202416</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PDV    SKU                                 DESCRICAO  \\\n",
       "0  12522  51944     COFFEE DES COL MAN SEDUC TCH PRM 10ml   \n",
       "1  20998  77557  QDB BASE LIQ SUPERMAT COR 06 Q 30ml RPCK   \n",
       "2  20858  74103            GLAMOUR DES COL SEC BL 75ml V4   \n",
       "3   5699  47950                          ZAAD EDP 95ml V6   \n",
       "4  20993  50297               ESTJ DEM LILY ESSENCE 4x4ml   \n",
       "\n",
       "   Vendas Ciclo Lançamento    Ciclo  \n",
       "0                       11  C202307  \n",
       "1                        1  C202405  \n",
       "2                        5  C202409  \n",
       "3                       12  C202406  \n",
       "4                        2  C202416  "
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_venda_diaria.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "ef979be5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_dourado = pd.read_excel(r\"C:\\Users\\joao.herculano\\GRUPO GINSENG\\Assistência Suprimentos - 2025\\DADOS DOURADO\\VENDA\\compilado de vendas.xlsx\")\n",
    "\n",
    "df_dourado['Data de venda'] = pd.to_datetime(df_dourado['Data de venda'], dayfirst=True)\n",
    "\n",
    "df_dourado['de para pdv'] = df_dourado['de para pdv'].astype(str)\n",
    "\n",
    "df_dourado['de para pdv'] = df_dourado['de para pdv'].str.replace(r'\\.0$', '', regex=True)\n",
    "\n",
    "# 'Dia' já está em formato datetime, então renomeamos para 'Data' diretamente\n",
    "# ou apenas usamos 'Dia' como referência de data\n",
    "\n",
    "# Ordena o DataFrame para garantir que a cumulativa funcione corretamente\n",
    "df_venda_diaria = df_venda_diaria.sort_values(by=['PDV', 'SKU', 'Ciclo'])\n",
    "\n",
    "# Calcula a quantidade acumulada até o dia para cada grupo\n",
    "df_dourado['Quantidade Acumulada dourado'] = (\n",
    "    df_dourado\n",
    "    .groupby(['de para pdv', 'sku'])['Quantidade Vendida']\n",
    "    .cumsum()\n",
    ")  # acumulado por grupo até a data da linha\n",
    "\n",
    "df_dourado = pd.merge(left=df_dourado,right=calendario[['Date','Ciclo']],left_on='Data de venda',right_on='Date',how='inner')\n",
    "\n",
    "\n",
    "\n",
    "df_dourado_agrupado = df_dourado.groupby(['de para pdv','sku','Ciclo'])['Quantidade Acumulada dourado'].max().reset_index()\n",
    "\n",
    "df_dourado_agrupado = df_dourado_agrupado.rename(columns={'Ciclo':'Ciclo dourado'})\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "41eb7ebf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    12522\n",
       "1    12817\n",
       "2    12818\n",
       "3    12820\n",
       "4    12823\n",
       "Name: PDV, dtype: object"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final['PDV'] = df_final['PDV'].astype(str)\n",
    "df_final['PDV'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "6dbe67bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final = pd.merge(left=df_final, right = df_dourado_agrupado, right_on=['Ciclo dourado','sku','de para pdv'],left_on=['CICLO SIMILAR','PRODUTO SIMILAR','PDV'],how='left')\n",
    "\n",
    "df_final['Quantidade Acumulada dourado'] = df_final['Quantidade Acumulada dourado'].fillna(0)\n",
    "\n",
    "\n",
    "df_final['Vendas Ciclo Lançamento'] = np.where(df_final['Quantidade Acumulada dourado'] > 0, df_final['Quantidade Acumulada dourado'], df_final['Vendas Ciclo Lançamento'])\n",
    "\n",
    "df_final = df_final.drop(columns='Quantidade Acumulada dourado')\n",
    "\n",
    "\n",
    "df_final = df_final.drop(columns='Ciclo dourado')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "7986b8fa",
   "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>CP VIVA BEM</th>\n",
       "      <th>Protheus</th>\n",
       "      <th>PDVDEPARA.Practico</th>\n",
       "      <th>Canal</th>\n",
       "      <th>Endereço</th>\n",
       "      <th>CNPJ</th>\n",
       "      <th>CNPJ Locação</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3559</td>\n",
       "      <td>70101.0</td>\n",
       "      <td>23713.0</td>\n",
       "      <td>MATRIZ - LJ</td>\n",
       "      <td>Rua Zeferino Correia, nº 17, Centro, CEP 45.00...</td>\n",
       "      <td>14.378.160/0001-83</td>\n",
       "      <td>14.378.160/0001-83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7292</td>\n",
       "      <td>70103.0</td>\n",
       "      <td>23712.0</td>\n",
       "      <td>LOJA</td>\n",
       "      <td>Al. Rio Branco, nº 373, Centro, Cândido Sales ...</td>\n",
       "      <td>14.378.160/0006-98</td>\n",
       "      <td>14.378.160/0006-98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8708</td>\n",
       "      <td>70102.0</td>\n",
       "      <td>23711.0</td>\n",
       "      <td>VD</td>\n",
       "      <td>Al. Lima Guerra, nº 04, Centro, Vitória da Con...</td>\n",
       "      <td>14.378.160/0005-07</td>\n",
       "      <td>14.378.160/0001-83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8931</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23710.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Avenida Rosa Cruz, nº 80, Hiper B Preço Loja B...</td>\n",
       "      <td>14.378.160/0008-50</td>\n",
       "      <td>14.378.160/0008-50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11191</td>\n",
       "      <td>70108.0</td>\n",
       "      <td>23709.0</td>\n",
       "      <td>LOJA</td>\n",
       "      <td>Av. Juracy Magalhães, nº 3340, Shopping Conqui...</td>\n",
       "      <td>14.378.160/0009-30</td>\n",
       "      <td>14.378.160/0001-83</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   CP VIVA BEM  Protheus  PDVDEPARA.Practico        Canal  \\\n",
       "0         3559   70101.0             23713.0  MATRIZ - LJ   \n",
       "1         7292   70103.0             23712.0         LOJA   \n",
       "2         8708   70102.0             23711.0           VD   \n",
       "3         8931       NaN             23710.0          NaN   \n",
       "4        11191   70108.0             23709.0         LOJA   \n",
       "\n",
       "                                            Endereço                CNPJ  \\\n",
       "0  Rua Zeferino Correia, nº 17, Centro, CEP 45.00...  14.378.160/0001-83   \n",
       "1  Al. Rio Branco, nº 373, Centro, Cândido Sales ...  14.378.160/0006-98   \n",
       "2  Al. Lima Guerra, nº 04, Centro, Vitória da Con...  14.378.160/0005-07   \n",
       "3  Avenida Rosa Cruz, nº 80, Hiper B Preço Loja B...  14.378.160/0008-50   \n",
       "4  Av. Juracy Magalhães, nº 3340, Shopping Conqui...  14.378.160/0009-30   \n",
       "\n",
       "         CNPJ Locação  \n",
       "0  14.378.160/0001-83  \n",
       "1  14.378.160/0006-98  \n",
       "2  14.378.160/0001-83  \n",
       "3  14.378.160/0008-50  \n",
       "4  14.378.160/0001-83  "
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_depara_vdc = pd.read_excel(r\"C:\\Users\\joao.herculano\\GRUPO GINSENG\\Assistência Suprimentos - 2025\\SUPRIMENTOS\\Vitoria da Conquista\\HISTORICO VENDAS VITORIA DA CONQUISTA\\Filiais - Vitoria da Conquista 4.xlsx\")\n",
    "\n",
    "df_depara_vdc.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "09efe938",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'df_vdc = pd.read_parquet(r\"C:\\\\Users\\\\joao.herculano\\\\GRUPO GINSENG\\\\Assistência Suprimentos - 2025\\\\SUPRIMENTOS\\\\Vitoria da Conquista\\\\HISTORICO VENDAS VITORIA DA CONQUISTA\\\\VENDAS VITORIA DA CONQUISTA\\\\concatenado.parquet\")\\n\\ndf_vdc[\\'PDV\\'] = df_vdc[\\'Quebra\\'].str.split(\" -\").str[0]\\n\\ndf_vdc[\\'PDV\\'] = df_vdc[\\'PDV\\'].astype(\\'int64\\')\\n\\ndf_vdc = df_vdc.rename(columns={\\'Quebra2\\':\\'DATA VENDA\\'})\\n\\ndf_vdc[\\'DATA VENDA\\'] = pd.to_datetime(df_vdc[\\'DATA VENDA\\'], format=\\'%d/%m/%Y\\')'"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r'''df_vdc = pd.read_parquet(r\"C:\\Users\\joao.herculano\\GRUPO GINSENG\\Assistência Suprimentos - 2025\\SUPRIMENTOS\\Vitoria da Conquista\\HISTORICO VENDAS VITORIA DA CONQUISTA\\VENDAS VITORIA DA CONQUISTA\\concatenado.parquet\")\n",
    "\n",
    "df_vdc['PDV'] = df_vdc['Quebra'].str.split(\" -\").str[0]\n",
    "\n",
    "df_vdc['PDV'] = df_vdc['PDV'].astype('int64')\n",
    "\n",
    "df_vdc = df_vdc.rename(columns={'Quebra2':'DATA VENDA'})\n",
    "\n",
    "df_vdc['DATA VENDA'] = pd.to_datetime(df_vdc['DATA VENDA'], format='%d/%m/%Y')'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "330154b2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"df_vdc = pd.merge(df_vdc,df_depara_vdc[['CP VIVA BEM','PDVDEPARA.Practico']],left_on='PDV',right_on='CP VIVA BEM',how='inner')\\n\\ndf_vdc['Quantidade'] = df_vdc['Quantidade'].str.replace(r',000$','',regex=True)\\n\\ndf_vdc['Quantidade'] = df_vdc['Quantidade'].astype('Int64') \""
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''df_vdc = pd.merge(df_vdc,df_depara_vdc[['CP VIVA BEM','PDVDEPARA.Practico']],left_on='PDV',right_on='CP VIVA BEM',how='inner')\n",
    "\n",
    "df_vdc['Quantidade'] = df_vdc['Quantidade'].str.replace(r',000$','',regex=True)\n",
    "\n",
    "df_vdc['Quantidade'] = df_vdc['Quantidade'].astype('Int64') '''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "09cc2f82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"df_vdc['Quantidade Acumulada vdc'] = (\\n    df_vdc\\n    .groupby(['PDVDEPARA.Practico', 'Código'])['Quantidade']\\n    .cumsum()\\n)  # acumulado por grupo até a data da linha\""
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "\n",
    "\n",
    "\n",
    "# 'Dia' já está em formato datetime, então renomeamos para 'Data' diretamente\n",
    "# ou apenas usamos 'Dia' como referência de data\n",
    "\n",
    "# Ordena o DataFrame para garantir que a cumulativa funcione corretamente\n",
    "#df_venda_diaria = df_venda_diaria.sort_values(by=['PDV', 'SKU', 'Ciclo'])\n",
    "\n",
    "# Calcula a quantidade acumulada até o dia para cada grupo\n",
    "r'''df_vdc['Quantidade Acumulada vdc'] = (\n",
    "    df_vdc\n",
    "    .groupby(['PDVDEPARA.Practico', 'Código'])['Quantidade']\n",
    "    .cumsum()\n",
    ")  # acumulado por grupo até a data da linha'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "5a827c08",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"df_vdc = pd.merge(left=df_vdc,right=calendario[['Date','Ciclo']],left_on='DATA VENDA',right_on='Date',how='inner')\\n\\ndf_vdc_agrupado = df_vdc.groupby(['PDVDEPARA.Practico',\\t'Código','Ciclo'])['Quantidade Acumulada vdc'].max().reset_index()\\n\\ndf_vdc_agrupado = df_vdc_agrupado.rename(columns={'Ciclo':'Ciclo vdc'})\\n\\n\\ndf_vdc_agrupado['PDVDEPARA.Practico'] = df_vdc_agrupado['PDVDEPARA.Practico'].astype(str).str.replace(r'\\\\.0$', '', regex=True)\\ndf_vdc_agrupado.head()\""
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r'''df_vdc = pd.merge(left=df_vdc,right=calendario[['Date','Ciclo']],left_on='DATA VENDA',right_on='Date',how='inner')\n",
    "\n",
    "df_vdc_agrupado = df_vdc.groupby(['PDVDEPARA.Practico',\t'Código','Ciclo'])['Quantidade Acumulada vdc'].max().reset_index()\n",
    "\n",
    "df_vdc_agrupado = df_vdc_agrupado.rename(columns={'Ciclo':'Ciclo vdc'})\n",
    "\n",
    "\n",
    "df_vdc_agrupado['PDVDEPARA.Practico'] = df_vdc_agrupado['PDVDEPARA.Practico'].astype(str).str.replace(r'\\.0$', '', regex=True)\n",
    "df_vdc_agrupado.head()'''\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "4933b6d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'df_vdc_agrupado = df_vdc_agrupado.astype(str)\\n\\ndf_vdc_agrupado = df_vdc_agrupado.replace()'"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r'''df_vdc_agrupado = df_vdc_agrupado.astype(str)\n",
    "\n",
    "df_vdc_agrupado = df_vdc_agrupado.replace()'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "8d5f2c33",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_vdc.to_excel(r\"C:\\Users\\joao.herculano\\Documents\\df_vdc.xlsx\",index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "63fea2ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"df_vdc_agrupado['PDVDEPARA.Practico'] = df_vdc_agrupado['PDVDEPARA.Practico'].astype(str)\\n\\ndf_vdc_agrupado['PDVDEPARA.Practico'].head()\""
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r'''df_vdc_agrupado['PDVDEPARA.Practico'] = df_vdc_agrupado['PDVDEPARA.Practico'].astype(str)\n",
    "\n",
    "df_vdc_agrupado['PDVDEPARA.Practico'].head()'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "84b5917c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final['PRODUTO SIMILAR'] = df_final['PRODUTO SIMILAR'].astype('Int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "ca911bd1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_vdc_agrupado['Código'] = df_vdc_agrupado['Código'].astype('Int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "8ec14143",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"df_final = pd.merge(left=df_final, right = df_vdc_agrupado, right_on=['Ciclo vdc','Código','PDVDEPARA.Practico'],left_on=['CICLO SIMILAR','PRODUTO SIMILAR','PDV'],how='left')\\n\\ndf_final['Quantidade Acumulada vdc'] = pd.to_numeric(\\n    df_final['Quantidade Acumulada vdc'],\\n    errors='coerce'  # valores inválidos viram NaN\\n).fillna(0).astype('Int64')\\n\\n\\ndf_final['Vendas Ciclo Lançamento'] = np.where(df_final['Quantidade Acumulada vdc'] > 0, df_final['Quantidade Acumulada vdc'], df_final['Vendas Ciclo Lançamento'])\\n\\ndf_final = df_final.drop(columns='Quantidade Acumulada vdc')\\n\\n\\ndf_final = df_final.drop(columns='Ciclo vdc')\""
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r'''df_final = pd.merge(left=df_final, right = df_vdc_agrupado, right_on=['Ciclo vdc','Código','PDVDEPARA.Practico'],left_on=['CICLO SIMILAR','PRODUTO SIMILAR','PDV'],how='left')\n",
    "\n",
    "df_final['Quantidade Acumulada vdc'] = pd.to_numeric(\n",
    "    df_final['Quantidade Acumulada vdc'],\n",
    "    errors='coerce'  # valores inválidos viram NaN\n",
    ").fillna(0).astype('Int64')\n",
    "\n",
    "\n",
    "df_final['Vendas Ciclo Lançamento'] = np.where(df_final['Quantidade Acumulada vdc'] > 0, df_final['Quantidade Acumulada vdc'], df_final['Vendas Ciclo Lançamento'])\n",
    "\n",
    "df_final = df_final.drop(columns='Quantidade Acumulada vdc')\n",
    "\n",
    "\n",
    "df_final = df_final.drop(columns='Ciclo vdc')'''\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "1a625e69",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1527, 91)"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# Cálculo do crescimento\n",
    "crescimento_final = df_final['CRESCIMENTO_GERAL'] + df_final['CRESCIMENTO']\n",
    "crescimento_final = crescimento_final.clip(lower=0.2, upper=0.8)  # limita entre 0 e 0.8\n",
    "df_final['CRESCIMENTO_FINAL'] = crescimento_final\n",
    "\n",
    "df_final['CRESCIMENTO_FINAL'] = np.where(df_final['CRESCIMENTO_FINAL'].isna(),df_final['CRESCIMENTO_GERAL'],df_final['CRESCIMENTO_FINAL'])\n",
    "\n",
    "df_final['CRESCIMENTO_FINAL'] = df_final['CRESCIMENTO_FINAL'].fillna(0)\n",
    "\n",
    "df_final['MEDIANA DO HISTÓRICO'] = df_final['MEDIANA DO HISTÓRICO'].fillna(0)\n",
    "\n",
    "# Corrige mediana do histórico onde for zero\n",
    "df_final['MEDIANA DO HISTÓRICO'] = np.where(\n",
    "    df_final['MEDIANA DO HISTÓRICO'] == 0,\n",
    "    0,\n",
    "    df_final['MEDIANA DO HISTÓRICO']\n",
    ")\n",
    "\n",
    "df_final['MEDIANA DO HISTÓRICO'] = df_final['MEDIANA DO HISTÓRICO'].fillna(0)\n",
    "\n",
    "\n",
    "\n",
    "# Cálculo do PV GINSENG\n",
    "pv_crescimento = (df_final['CRESCIMENTO_FINAL']+1) * df_final['Vendas Ciclo Lançamento']\n",
    "pv_mediana = (df_final['CRESCIMENTO_FINAL'] + 1) * df_final['MEDIANA DO HISTÓRICO']\n",
    "\n",
    "df_final['PV GINSENG'] = np.where(\n",
    "    pv_crescimento < df_final['MEDIANA DO HISTÓRICO'],\n",
    "    pv_mediana.round(0),\n",
    "    pv_crescimento.round(0)\n",
    ")\n",
    "\n",
    "# Se PV GINSENG for NA, substitui pela média por canal\n",
    "df_final['PV GINSENG'] = df_final['PV GINSENG'].fillna(0)\n",
    "\n",
    "df_final['PV GINSENG'] = df_final['PV GINSENG'].round(0).astype(int)\n",
    "\n",
    "df_final.shape\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "cfdae71d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_final.to_excel(r\"C:\\Users\\joao.herculano\\GRUPO GINSENG\\Assistência Suprimentos - 2025\\SUPRIMENTOS\\BD_LANÇAMENTOS\\BOT\\BOT - C12\\LANÇAMENTOS\\validação.xlsx\",index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "30c1d83d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['202409', '202410', '202411', '202412', '202413', '202414', '202415',\n",
      "       '202416', '202417', '202501', '202502', '202503', '202504', '202505',\n",
      "       '202506', '202507', 'CRESCIMENTO_GERAL'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(df_final.columns[68:85])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "62b7f9d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['PRODUTO LANÇAMENTO', 'DESCRIÇÃO DO LANÇAMENTO', 'PRODUTO SIMILAR',\n",
       "       'DESCRIÇÃO SIMILAR', 'CICLO SIMILAR', 'FOCO', 'IAF', 'CATEGORIA',\n",
       "       'MARCA', '% CONSUMIDOR', 'MECANICA CONSUMIDOR', '% REVENDEDOR',\n",
       "       'MECANICA REVENDEDOR', 'TIPO DE PRODUTO', 'MATCH', 'PDV', 'CANAL',\n",
       "       'DESCRIÇÃO PDV', 'PDV DESC', 'UF', 'ANALISTA', 'SUPERVISOR', 'STATUS',\n",
       "       'SKU_x', 'curva', 'categoria', 'proj_mar', 'proj_mar+1',\n",
       "       'ESTOQUE ATUAL', 'ESTOQUE EM TRANSITO', 'PEDIDO PENDENTE',\n",
       "       'DDV PREVISTO', 'preço', 'SKU_FINAL', 'DESCRICAO', 'C202413', 'C202414',\n",
       "       'C202415', 'C202416', 'C202417', 'C202501', 'C202502', 'C202503',\n",
       "       'C202504', 'C202505', 'C202506', 'C202507', 'C202508', 'C202509',\n",
       "       'C202510', 'C202511', 'C202512', 'C202513', 'CRESCIMENTO', 'Ciclo',\n",
       "       'INICIO CICLO', 'FIM CICLO', 'DURAÇÃO', 'match', 'dias_ate_inicio',\n",
       "       'INICIO CICLO SIMILAR', 'FIM CICLO SIMILAR', 'DURAÇÃO CICLO SIMILAR',\n",
       "       'SKU_y', 'Ciclo', 'Vendas Ciclo Lançamento', 'SKU', '202408',\n",
       "       'Pico Vendas Similar Ultimos 6 ciclos', 'MEDIANA DO HISTÓRICO',\n",
       "       'de para pdv', 'sku', 'CRESCIMENTO_FINAL', 'PV GINSENG'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re\n",
    "\n",
    "# identificar colunas de ciclo puro (ex: '202407')\n",
    "colunas_ciclo_puro = [col for col in df_final.columns[68:85]]\n",
    "\n",
    "for col in colunas_ciclo_puro:\n",
    "    col_hist = f'C{col}'\n",
    "    if col_hist in df_final.columns:\n",
    "        # mantém o maior valor entre a coluna histórica e a pura\n",
    "        df_final[col_hist] = df_final[[col_hist, col]].max(axis=1)\n",
    "\n",
    "# remove as colunas puras\n",
    "if colunas_ciclo_puro:\n",
    "    df_final.drop(columns=colunas_ciclo_puro, inplace=True)\n",
    "\n",
    "df_final.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "ad10c069",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'print(df_final.columns[30:43])\\n\\ndf_final.drop(columns=df_final.columns[30:43],inplace=True)'"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r'''print(df_final.columns[30:43])\n",
    "\n",
    "df_final.drop(columns=df_final.columns[30:43],inplace=True)'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "3b7f3a82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C202513'"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.columns[52]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "d63e55c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final['Pico Vendas Similar Ultimos 6 ciclos'] = df_final[VENDA_SIMILAR_6_MESES].max(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "15b7149f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final = df_final.rename(columns={df_final.columns[48]: \"C-4\", df_final.columns[49]: \"C-3\",df_final.columns[50]: \"C-2\",df_final.columns[51]: \"C-1\",df_final.columns[52]:'VENDAS CICLO ATUAL'})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "9333bc77",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['PRODUTO LANÇAMENTO', 'DESCRIÇÃO DO LANÇAMENTO', 'PRODUTO SIMILAR',\n",
       "       'DESCRIÇÃO SIMILAR', 'CICLO SIMILAR', 'FOCO', 'IAF', 'CATEGORIA',\n",
       "       'MARCA', '% CONSUMIDOR', 'MECANICA CONSUMIDOR', '% REVENDEDOR',\n",
       "       'MECANICA REVENDEDOR', 'TIPO DE PRODUTO', 'MATCH', 'PDV', 'CANAL',\n",
       "       'DESCRIÇÃO PDV', 'PDV DESC', 'UF', 'ANALISTA', 'SUPERVISOR', 'STATUS',\n",
       "       'SKU_X', 'CURVA', 'CATEGORIA', 'PROJ_MAR', 'PROJ_MAR+1',\n",
       "       'ESTOQUE ATUAL', 'ESTOQUE EM TRANSITO', 'PEDIDO PENDENTE',\n",
       "       'DDV PREVISTO', 'PREÇO', 'SKU_FINAL', 'DESCRICAO', 'C202413', 'C202414',\n",
       "       'C202415', 'C202416', 'C202417', 'C202501', 'C202502', 'C202503',\n",
       "       'C202504', 'C202505', 'C202506', 'C202507', 'C202508', 'C-4', 'C-3',\n",
       "       'C-2', 'C-1', 'VENDAS CICLO ATUAL', 'CRESCIMENTO', 'CICLO',\n",
       "       'INICIO CICLO', 'FIM CICLO', 'DURAÇÃO', 'MATCH', 'DIAS_ATE_INICIO',\n",
       "       'INICIO CICLO SIMILAR', 'FIM CICLO SIMILAR', 'DURAÇÃO CICLO SIMILAR',\n",
       "       'CICLO', 'VENDAS CICLO LANÇAMENTO', 'SKU', '202408',\n",
       "       'PICO VENDAS SIMILAR ULTIMOS 6 CICLOS', 'MEDIANA DO HISTÓRICO',\n",
       "       'DE PARA PDV', 'SKU', 'CRESCIMENTO_FINAL', 'PV GINSENG'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.columns = df_final.columns.str.upper()\n",
    "\n",
    "df_final.drop(columns=df_final.filter(regex='_Y').columns, inplace=True)\n",
    "\n",
    "df_final.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "dceebd16",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final = df_final.rename(columns={'MARCA_X':'MARCA'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "62ce5c62",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1527, 73)"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "cecca116",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final[['C-4', 'C-3', 'C-2', 'C-1', 'VENDAS CICLO ATUAL']] = df_final[['C-4', 'C-3', 'C-2', 'C-1', 'VENDAS CICLO ATUAL']].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "8ad318b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final = df_final.loc[:, ~df_final.columns.duplicated()]\n",
    "\n",
    "colunas_desejadas = [\n",
    "    'SUPERVISOR',\n",
    "    'ANALISTA',\n",
    "    'CANAL',\n",
    "    'UF',\n",
    "    'PDV',\n",
    "    'DESCRIÇÃO PDV',\n",
    "    'PRODUTO LANÇAMENTO',\n",
    "    'DESCRIÇÃO DO LANÇAMENTO',\n",
    "    'MARCA',\n",
    "    'CATEGORIA',\n",
    "    '% CONSUMIDOR',\n",
    "    'MECANICA CONSUMIDOR',\n",
    "    '% REVENDEDOR',\n",
    "    'MECANICA REVENDEDOR',\n",
    "    'TIPO DE PRODUTO',\n",
    "    'IAF',\n",
    "    'FOCO',\n",
    "    'PRODUTO SIMILAR',\n",
    "    'DESCRIÇÃO SIMILAR',\n",
    "    'CICLO SIMILAR',\n",
    "    'VENDAS CICLO LANÇAMENTO',\n",
    "    'C-4',\n",
    "    'C-3',\n",
    "    'C-2',\n",
    "    'C-1',\n",
    "    'VENDAS CICLO ATUAL',\n",
    "    'PICO VENDAS SIMILAR ULTIMOS 6 CICLOS',\n",
    "    'PV GINSENG'\n",
    "]\n",
    "\n",
    "df_final = df_final.reindex(columns=colunas_desejadas)\n",
    "\n",
    "colunas_filtradas = [col for col in colunas_desejadas if col in df_final.columns]\n",
    "df_final = df_final[colunas_filtradas]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "25cbff26",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"df_final = df_final.reindex(columns=[\\n    'SUPERVISOR',\\n    'ANALISTA',\\n    'CANAL',\\n    'UF',\\n    'PDV',\\n    'DESCRIÇÃO PDV',\\n    'PRODUTO LANÇAMENTO',\\n    'DESCRIÇÃO DO LANÇAMENTO',\\n    'MARCA',\\n    'CATEGORIA',\\n    'MECANICA CONSUMIDOR',\\n    '% CONSUMIDOR',\\n    'MECANICA REVENDEDOR',\\n    '% REVENDEDOR',\\n    'TIPO DE PRODUTO',\\n    'IAF',\\n    'FOCO',\\n    'PRODUTO SIMILAR',\\n    'DESCRIÇÃO SIMILAR',\\n    'CICLO SIMILAR',\\n    'VENDAS CICLO LANÇAMENTO',\\n    'C-4',\\n    'C-3',\\n    'C-2',\\n    'C-1',\\n    'VENDAS CICLO ATUAL',\\n    'PICO VENDAS SIMILAR ULTIMOS 6 CICLOS',\\n    'PV GINSENG'])\\n\""
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''df_final = df_final.reindex(columns=[\n",
    "    'SUPERVISOR',\n",
    "    'ANALISTA',\n",
    "    'CANAL',\n",
    "    'UF',\n",
    "    'PDV',\n",
    "    'DESCRIÇÃO PDV',\n",
    "    'PRODUTO LANÇAMENTO',\n",
    "    'DESCRIÇÃO DO LANÇAMENTO',\n",
    "    'MARCA',\n",
    "    'CATEGORIA',\n",
    "    'MECANICA CONSUMIDOR',\n",
    "    '% CONSUMIDOR',\n",
    "    'MECANICA REVENDEDOR',\n",
    "    '% REVENDEDOR',\n",
    "    'TIPO DE PRODUTO',\n",
    "    'IAF',\n",
    "    'FOCO',\n",
    "    'PRODUTO SIMILAR',\n",
    "    'DESCRIÇÃO SIMILAR',\n",
    "    'CICLO SIMILAR',\n",
    "    'VENDAS CICLO LANÇAMENTO',\n",
    "    'C-4',\n",
    "    'C-3',\n",
    "    'C-2',\n",
    "    'C-1',\n",
    "    'VENDAS CICLO ATUAL',\n",
    "    'PICO VENDAS SIMILAR ULTIMOS 6 CICLOS',\n",
    "    'PV GINSENG'])\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "a3e80cb4",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final['SUGESTÃO METASELLIN'] = ''\n",
    "df_final['SUGESTÃO ABASTECIMENTO'] = ''\n",
    "df_final['SUGESTÃO COMERCIAL'] = ''\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "cc9c6ee6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_pdv_origi['PDV'] = df_pdv_origi['PDV'].astype(str)\n",
    "\n",
    "df_pdv_origi['PDV'].head()\n",
    "\n",
    "df_pdv_origi = df_pdv_origi.rename(columns={'UF':'UF_CERTO'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "df9f0130",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final= pd.merge(df_final,df_pdv_origi[['UF_CERTO','PDV']],on='PDV',how='inner')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "7778d82f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['SUPERVISOR', 'ANALISTA', 'CANAL', 'UF', 'PDV', 'DESCRIÇÃO PDV',\n",
       "       'PRODUTO LANÇAMENTO', 'DESCRIÇÃO DO LANÇAMENTO', 'MARCA', 'CATEGORIA',\n",
       "       '% CONSUMIDOR', 'MECANICA CONSUMIDOR', '% REVENDEDOR',\n",
       "       'MECANICA REVENDEDOR', 'TIPO DE PRODUTO', 'IAF', 'FOCO',\n",
       "       'PRODUTO SIMILAR', 'DESCRIÇÃO SIMILAR', 'CICLO SIMILAR',\n",
       "       'VENDAS CICLO LANÇAMENTO', 'C-4', 'C-3', 'C-2', 'C-1',\n",
       "       'VENDAS CICLO ATUAL', 'PICO VENDAS SIMILAR ULTIMOS 6 CICLOS',\n",
       "       'PV GINSENG', 'SUGESTÃO METASELLIN', 'SUGESTÃO ABASTECIMENTO',\n",
       "       'SUGESTÃO COMERCIAL', 'UF_CERTO'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "f8cd886a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SUPERVISOR</th>\n",
       "      <th>ANALISTA</th>\n",
       "      <th>CANAL</th>\n",
       "      <th>UF</th>\n",
       "      <th>PDV</th>\n",
       "      <th>DESCRIÇÃO PDV</th>\n",
       "      <th>PRODUTO LANÇAMENTO</th>\n",
       "      <th>DESCRIÇÃO DO LANÇAMENTO</th>\n",
       "      <th>MARCA</th>\n",
       "      <th>CATEGORIA</th>\n",
       "      <th>...</th>\n",
       "      <th>C-4</th>\n",
       "      <th>C-3</th>\n",
       "      <th>C-2</th>\n",
       "      <th>C-1</th>\n",
       "      <th>VENDAS CICLO ATUAL</th>\n",
       "      <th>PICO VENDAS SIMILAR ULTIMOS 6 CICLOS</th>\n",
       "      <th>PV GINSENG</th>\n",
       "      <th>SUGESTÃO METASELLIN</th>\n",
       "      <th>SUGESTÃO ABASTECIMENTO</th>\n",
       "      <th>SUGESTÃO COMERCIAL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Efigênia Herculano</td>\n",
       "      <td>LUAN</td>\n",
       "      <td>LJ</td>\n",
       "      <td>AL</td>\n",
       "      <td>12522</td>\n",
       "      <td>MACEIO SHOP EXP</td>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>LILY</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Maxwell Vieira</td>\n",
       "      <td>JEFFERSON</td>\n",
       "      <td>LJ</td>\n",
       "      <td>AL</td>\n",
       "      <td>12817</td>\n",
       "      <td>SHOPPING PATIO</td>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>LILY</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>4</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Maxwell Vieira</td>\n",
       "      <td>VINICIUS</td>\n",
       "      <td>LJ</td>\n",
       "      <td>AL</td>\n",
       "      <td>12818</td>\n",
       "      <td>GB SERRARIA</td>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>LILY</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Maxwell Vieira</td>\n",
       "      <td>THAYLLAN</td>\n",
       "      <td>LJ</td>\n",
       "      <td>AL</td>\n",
       "      <td>12820</td>\n",
       "      <td>ATACADÃO</td>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>LILY</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Efigênia Herculano</td>\n",
       "      <td>MARCYARA</td>\n",
       "      <td>LJ</td>\n",
       "      <td>AL</td>\n",
       "      <td>12823</td>\n",
       "      <td>PONTA VERDE</td>\n",
       "      <td>89446</td>\n",
       "      <td>LILY CR AC DES HID CP LEAU/LILY SOL 200g</td>\n",
       "      <td>LILY</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           SUPERVISOR   ANALISTA CANAL  UF    PDV    DESCRIÇÃO PDV  \\\n",
       "0  Efigênia Herculano       LUAN    LJ  AL  12522  MACEIO SHOP EXP   \n",
       "1      Maxwell Vieira  JEFFERSON    LJ  AL  12817   SHOPPING PATIO   \n",
       "2      Maxwell Vieira   VINICIUS    LJ  AL  12818      GB SERRARIA   \n",
       "3      Maxwell Vieira   THAYLLAN    LJ  AL  12820         ATACADÃO   \n",
       "4  Efigênia Herculano   MARCYARA    LJ  AL  12823      PONTA VERDE   \n",
       "\n",
       "   PRODUTO LANÇAMENTO                   DESCRIÇÃO DO LANÇAMENTO MARCA  \\\n",
       "0               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g  LILY   \n",
       "1               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g  LILY   \n",
       "2               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g  LILY   \n",
       "3               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g  LILY   \n",
       "4               89446  LILY CR AC DES HID CP LEAU/LILY SOL 200g  LILY   \n",
       "\n",
       "             CATEGORIA  ...  C-4  C-3   C-2  C-1 VENDAS CICLO ATUAL  \\\n",
       "0  CUIDADOS COM A PELE  ...  0.0  2.0   2.0  0.0                0.0   \n",
       "1  CUIDADOS COM A PELE  ...  8.0  1.0  24.0  1.0                0.0   \n",
       "2  CUIDADOS COM A PELE  ...  0.0  2.0   7.0  1.0                0.0   \n",
       "3  CUIDADOS COM A PELE  ...  4.0  1.0   1.0  1.0                0.0   \n",
       "4  CUIDADOS COM A PELE  ...  1.0  0.0   0.0  2.0                0.0   \n",
       "\n",
       "  PICO VENDAS SIMILAR ULTIMOS 6 CICLOS PV GINSENG  SUGESTÃO METASELLIN  \\\n",
       "0                                  2.0          2                        \n",
       "1                                 24.0          4                        \n",
       "2                                  7.0          1                        \n",
       "3                                  4.0          2                        \n",
       "4                                  2.0          1                        \n",
       "\n",
       "  SUGESTÃO ABASTECIMENTO SUGESTÃO COMERCIAL  \n",
       "0                                            \n",
       "1                                            \n",
       "2                                            \n",
       "3                                            \n",
       "4                                            \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final['UF']= df_final['UF_CERTO']\n",
    "\n",
    "df_final = df_final.drop(columns=['UF_CERTO'])\n",
    "\n",
    "df_final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "eaf25e4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['SUPERVISOR', 'ANALISTA', 'CANAL', 'UF', 'PDV', 'DESCRIÇÃO PDV',\n",
       "       'PRODUTO LANÇAMENTO', 'DESCRIÇÃO DO LANÇAMENTO', 'MARCA', 'CATEGORIA',\n",
       "       '% CONSUMIDOR', 'MECANICA CONSUMIDOR', '% REVENDEDOR',\n",
       "       'MECANICA REVENDEDOR', 'TIPO DE PRODUTO', 'IAF', 'FOCO',\n",
       "       'PRODUTO SIMILAR', 'DESCRIÇÃO SIMILAR', 'CICLO SIMILAR',\n",
       "       'VENDAS CICLO LANÇAMENTO', 'C-4', 'C-3', 'C-2', 'C-1',\n",
       "       'VENDAS CICLO ATUAL', 'PICO VENDAS SIMILAR ULTIMOS 6 CICLOS',\n",
       "       'PV GINSENG', 'SUGESTÃO METASELLIN', 'SUGESTÃO ABASTECIMENTO',\n",
       "       'SUGESTÃO COMERCIAL'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "9b866c74",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# lista de colunas numéricas\n",
    "numeric_cols = [\n",
    "    'VENDAS CICLO LANÇAMENTO', 'C-4', 'C-3', 'C-2', 'C-1',\n",
    "    'VENDAS CICLO ATUAL', 'PICO VENDAS SIMILAR ULTIMOS 6 CICLOS',\n",
    "    'PV GINSENG', 'SUGESTÃO METASELLIN', 'SUGESTÃO ABASTECIMENTO',\n",
    "    'SUGESTÃO COMERCIAL'\n",
    "]\n",
    "\n",
    "# colunas não numéricas = todas menos as numéricas\n",
    "non_numeric_cols = [col for col in df_final.columns if col not in numeric_cols]\n",
    "\n",
    "# agrupar por todas as não numéricas, pegando o máximo das numéricas\n",
    "df_final_sem_dupli = (\n",
    "    df_final\n",
    "    .groupby(non_numeric_cols, as_index=False)[numeric_cols]\n",
    "    .sum()\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "f491d15f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>SUPERVISOR</th>\n",
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       "      <th>UF</th>\n",
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       "      <th>C-4</th>\n",
       "      <th>C-3</th>\n",
       "      <th>C-2</th>\n",
       "      <th>C-1</th>\n",
       "      <th>VENDAS CICLO ATUAL</th>\n",
       "      <th>PICO VENDAS SIMILAR ULTIMOS 6 CICLOS</th>\n",
       "      <th>PV GINSENG</th>\n",
       "      <th>SUGESTÃO METASELLIN</th>\n",
       "      <th>SUGESTÃO ABASTECIMENTO</th>\n",
       "      <th>SUGESTÃO COMERCIAL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>COFFEE DES ANTIT AER WOMAN SEDUC 75g V4</td>\n",
       "      <td>COFFEE</td>\n",
       "      <td>DESODORANTES</td>\n",
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       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>JEFFERSON</td>\n",
       "      <td>LJ</td>\n",
       "      <td>BA3</td>\n",
       "      <td>24253</td>\n",
       "      <td>Matriz Centro</td>\n",
       "      <td>49154</td>\n",
       "      <td>COFFEE DES COL UNIQ WOM FL/GOURM 100ml</td>\n",
       "      <td>CUIDE-SE BEM</td>\n",
       "      <td>PERFUMARIA</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>28</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>JEFFERSON</td>\n",
       "      <td>LJ</td>\n",
       "      <td>BA3</td>\n",
       "      <td>24253</td>\n",
       "      <td>Matriz Centro</td>\n",
       "      <td>49193</td>\n",
       "      <td>COFFEE DES COL UNIQ MAN FOUG/OR 100ml</td>\n",
       "      <td>COFFEE</td>\n",
       "      <td>PERFUMARIA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>28</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>JEFFERSON</td>\n",
       "      <td>LJ</td>\n",
       "      <td>BA3</td>\n",
       "      <td>24253</td>\n",
       "      <td>Matriz Centro</td>\n",
       "      <td>49893</td>\n",
       "      <td>CBEM LOC DES HID CPO ROS/ALG V3 400ml</td>\n",
       "      <td>FLORATTA</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>JEFFERSON</td>\n",
       "      <td>LJ</td>\n",
       "      <td>BA3</td>\n",
       "      <td>24253</td>\n",
       "      <td>Matriz Centro</td>\n",
       "      <td>49943</td>\n",
       "      <td>CBEM LOC DES HID CPO PESSEGURA V2 400ml</td>\n",
       "      <td>CUIDE-SE BEM</td>\n",
       "      <td>CUIDADOS COM A PELE</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  SUPERVISOR   ANALISTA CANAL   UF    PDV  DESCRIÇÃO PDV  PRODUTO LANÇAMENTO  \\\n",
       "0          0  JEFFERSON    LJ  BA3  24253  Matriz Centro               48780   \n",
       "1          0  JEFFERSON    LJ  BA3  24253  Matriz Centro               49154   \n",
       "2          0  JEFFERSON    LJ  BA3  24253  Matriz Centro               49193   \n",
       "3          0  JEFFERSON    LJ  BA3  24253  Matriz Centro               49893   \n",
       "4          0  JEFFERSON    LJ  BA3  24253  Matriz Centro               49943   \n",
       "\n",
       "                   DESCRIÇÃO DO LANÇAMENTO         MARCA            CATEGORIA  \\\n",
       "0  COFFEE DES ANTIT AER WOMAN SEDUC 75g V4        COFFEE         DESODORANTES   \n",
       "1   COFFEE DES COL UNIQ WOM FL/GOURM 100ml  CUIDE-SE BEM           PERFUMARIA   \n",
       "2    COFFEE DES COL UNIQ MAN FOUG/OR 100ml        COFFEE           PERFUMARIA   \n",
       "3    CBEM LOC DES HID CPO ROS/ALG V3 400ml      FLORATTA  CUIDADOS COM A PELE   \n",
       "4  CBEM LOC DES HID CPO PESSEGURA V2 400ml  CUIDE-SE BEM  CUIDADOS COM A PELE   \n",
       "\n",
       "   ...  C-4  C-3  C-2  C-1 VENDAS CICLO ATUAL  \\\n",
       "0  ...  1.0  0.0  2.0  2.0                0.0   \n",
       "1  ...  1.0  0.0  0.0  1.0                0.0   \n",
       "2  ...  0.0  1.0  0.0  1.0                0.0   \n",
       "3  ...  4.0  2.0  2.0  1.0                1.0   \n",
       "4  ...  2.0  1.0  1.0  1.0                0.0   \n",
       "\n",
       "  PICO VENDAS SIMILAR ULTIMOS 6 CICLOS PV GINSENG  SUGESTÃO METASELLIN  \\\n",
       "0                                  2.0          0                        \n",
       "1                                  1.0         28                        \n",
       "2                                  1.0         28                        \n",
       "3                                  4.0          2                        \n",
       "4                                  2.0          0                        \n",
       "\n",
       "  SUGESTÃO ABASTECIMENTO SUGESTÃO COMERCIAL  \n",
       "0                                            \n",
       "1                                            \n",
       "2                                            \n",
       "3                                            \n",
       "4                                            \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final_sem_dupli.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "2df3e2e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final_sem_dupli.to_excel(f'C:/Users/joao.herculano/Documents/Lançamento{hoje}{ciclo_lanc}!!2.xlsx',index=False)"
   ]
  }
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