{
 "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",
    "\n",
    "from datetime import datetime\n",
    "from openpyxl import load_workbook\n",
    "from openpyxl.styles import PatternFill, Font"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fa16d50c",
   "metadata": {},
   "outputs": [],
   "source": [
    "hoje = datetime.today().strftime('%Y-%m-%d')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9fcdc77a",
   "metadata": {},
   "outputs": [],
   "source": [
    "calendario = pd.read_excel(r\"..\\\\..\\\\SUPRIMENTOS\\BD_LANÇAMENTOS\\BOT\\arquivos usados por todos os lançamentos\\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) + 2).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": 11,
   "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>2507</th>\n",
       "      <td>C202517</td>\n",
       "      <td>2025-12-01</td>\n",
       "      <td>2025-12-25</td>\n",
       "      <td>25</td>\n",
       "      <td>BOTICARIO</td>\n",
       "      <td>2025-12-01</td>\n",
       "      <td>17</td>\n",
       "      <td>C2025</td>\n",
       "      <td>C202519</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Ciclo INICIO CICLO  FIM CICLO  DURAÇÃO      MARCA       Date  \\\n",
       "2507  C202517   2025-12-01 2025-12-25       25  BOTICARIO 2025-12-01   \n",
       "\n",
       "      NUM_CICLO ANO_CICLO CICLOMAIS2  dias_ate_inicio  match  \n",
       "2507         17     C2025    C202519               45      1  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_calendario"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0245ed28",
   "metadata": {},
   "outputs": [],
   "source": [
    "ciclo_lanc = filtered_calendario['Ciclo'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7a3c1e6f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C202517'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ciclo_lanc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "61ffc777",
   "metadata": {},
   "outputs": [],
   "source": [
    "#COLOCAR ARQUIVO SIMILAR AQUI (ALTERAR)\n",
    "\n",
    "arquivo_similares = r\"C:\\Users\\joao.herculano\\GRUPO GINSENG\\Assistência Suprimentos - 2025\\SUPRIMENTOS\\BD_LANÇAMENTOS\\BOT\\BOT - C17\\arquivos para geração da sugestão\\similar novo splash\\PRODUTOS SIMILARES - BOT(body splash).xlsx\"\n",
    "\n",
    "df_similares = pd.read_excel(arquivo_similares)\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": 16,
   "id": "7eaf9237",
   "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>MECANICA CONSUMIDOR</th>\n",
       "      <th>% REVENDEDOR</th>\n",
       "      <th>MECANICA REVENDEDOR</th>\n",
       "      <th>TIPO DE PRODUTO</th>\n",
       "      <th>MATCH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>86116</td>\n",
       "      <td>CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...</td>\n",
       "      <td>58363</td>\n",
       "      <td>Body Splash Desodrante Colônia Cuide-se Bem Nu...</td>\n",
       "      <td>C202506</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>-</td>\n",
       "      <td>-</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PRODUTO LANÇAMENTO                            DESCRIÇÃO DO LANÇAMENTO  \\\n",
       "0               86116  CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...   \n",
       "\n",
       "   PRODUTO SIMILAR                                  DESCRIÇÃO SIMILAR  \\\n",
       "0            58363  Body Splash Desodrante Colônia Cuide-se Bem Nu...   \n",
       "\n",
       "  CICLO SIMILAR FOCO  IAF   CATEGORIA         MARCA % CONSUMIDOR  \\\n",
       "0       C202506  Não  Não  PERFUMARIA  CUIDE-SE BEM            -   \n",
       "\n",
       "  MECANICA CONSUMIDOR % REVENDEDOR MECANICA REVENDEDOR TIPO DE PRODUTO  MATCH  \n",
       "0                   -            -                   -         REGULAR      1  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_similares.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ad836441",
   "metadata": {},
   "outputs": [],
   "source": [
    "#TRANSFORMA A COLUNA EM STRING\n",
    "df_similares['PRODUTO SIMILAR'] = df_similares['PRODUTO SIMILAR'].astype('str')\n",
    "# TIRA O '.0' DO FIM SE OCORRER\n",
    "df_similares['PRODUTO SIMILAR'] = df_similares['PRODUTO SIMILAR'].replace(r'\\.0$', '', regex=True)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "fe922f62",
   "metadata": {},
   "outputs": [],
   "source": [
    "# SEMPRE COLOCAR O DO USUARIO.(ALTERAR)\n",
    "df_tabela = pd.read_excel(r\"C:\\Users\\joao.herculano\\GRUPO GINSENG\\Assistência Suprimentos - 2025\\SUPRIMENTOS\\BD_LANÇAMENTOS\\BOT\\BOT - C17\\arquivos para geração da sugestão\\TABELA DE PEDIDO\\Pedidos Semanais Especiais - BOT - 202517.xlsx\")\n",
    "\n",
    "# FILTRA REGIÃO = NORDESTE\n",
    "df_tabela = df_tabela[df_tabela['Região'] == 'NNE'] \n",
    "# TIRA CANAL ECOMERCE DO PLANILHA\n",
    "df_tabela = df_tabela[(df_tabela['Canal'] != 'Ecomm') | (df_tabela['Canal'] != 'Ecomm | VD') | (df_tabela['Canal'] != 'Ecomm | Loja')] \n",
    "# UNIFICA DESCONTOS CANAL LOJA\n",
    "df_tabela['Canal'] = np.where((df_tabela['Canal'] == \"Loja\") | (df_tabela['Canal'] == \"Todos\") | (df_tabela['Canal'] == \"Loja | VD\"),\"TODOS\",\"VD\")\n",
    "# SÓ MANTÉM LANÇAMENTOS \n",
    "df_tabela = df_tabela[df_tabela['Tipo de promoção'].str.contains('Lançamentos', na=False)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e0c55962",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_pdv = pd.read_excel(r\"..\\\\..\\\\SUPRIMENTOS\\BD_LANÇAMENTOS\\BOT\\BOT - C16\\arquivos para geração da sugestão\\PDV\\PDV_ATT.xlsx\")\n",
    "# remove lojas QDB\n",
    "df_pdv = df_pdv[~df_pdv['PDV'].isin([910173, 910291])]\n",
    "\n",
    "#feito para retificar os UFS ao fim do script\n",
    "df_pdv_origi = pd.read_excel(r\"..\\\\..\\\\SUPRIMENTOS\\BD_LANÇAMENTOS\\BOT\\BOT - C16\\arquivos para geração da sugestão\\PDV\\PDV_ATT.xlsx\")\n",
    "df_pdv_origi = df_pdv_origi[~df_pdv_origi['PDV'].isin([910173, 910291])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a7b41ecb",
   "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",
       "      <th>ANALISTA EUD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>23156</td>\n",
       "      <td>LJ</td>\n",
       "      <td>SHOPPING CENTRO SUL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SERGIPE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inativa</td>\n",
       "      <td>Inativa</td>\n",
       "      <td>Inativa</td>\n",
       "      <td>INATIVO</td>\n",
       "      <td>LOJA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4494</td>\n",
       "      <td>MTZ</td>\n",
       "      <td>ESCRITORIO</td>\n",
       "      <td>4494-COMERCIO-PONTA VERDE-MACEIO</td>\n",
       "      <td>ND</td>\n",
       "      <td>ALAGOAS</td>\n",
       "      <td>MACEIÓ</td>\n",
       "      <td>AL</td>\n",
       "      <td>CP GINSENG</td>\n",
       "      <td>Inativa</td>\n",
       "      <td>Inativa</td>\n",
       "      <td>Inativa</td>\n",
       "      <td>INATIVO</td>\n",
       "      <td>INATIVO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1137</td>\n",
       "      <td>MTZ</td>\n",
       "      <td>AMG</td>\n",
       "      <td>1137-AMG SERRARIA</td>\n",
       "      <td>ND</td>\n",
       "      <td>ALAGOAS</td>\n",
       "      <td>MACEIÓ</td>\n",
       "      <td>AL</td>\n",
       "      <td>O BOTICARIO</td>\n",
       "      <td>Inativa</td>\n",
       "      <td>Inativa</td>\n",
       "      <td>Inativa</td>\n",
       "      <td>INATIVO</td>\n",
       "      <td>INATIVO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12522</td>\n",
       "      <td>LJ</td>\n",
       "      <td>MACEIO SHOP EXP</td>\n",
       "      <td>12522-COMERCIO -MACEIO SHOP EXPANSAO</td>\n",
       "      <td>MCZ BAIXA</td>\n",
       "      <td>ALAGOAS</td>\n",
       "      <td>MACEIÓ</td>\n",
       "      <td>AL</td>\n",
       "      <td>O BOTICARIO</td>\n",
       "      <td>LUAN</td>\n",
       "      <td>Betina Melo</td>\n",
       "      <td>Efigênia Herculano</td>\n",
       "      <td>ATIVO</td>\n",
       "      <td>LOJA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12817</td>\n",
       "      <td>LJ</td>\n",
       "      <td>SHOPPING PATIO</td>\n",
       "      <td>12817-COMERCIO -SHOPPING PATIO</td>\n",
       "      <td>MCZ ALTA</td>\n",
       "      <td>ALAGOAS</td>\n",
       "      <td>MACEIÓ</td>\n",
       "      <td>AL</td>\n",
       "      <td>O BOTICARIO</td>\n",
       "      <td>JEFFERSON</td>\n",
       "      <td>Pamella Barbosa</td>\n",
       "      <td>Maxwell Vieira</td>\n",
       "      <td>ATIVO</td>\n",
       "      <td>LOJA</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>24257</td>\n",
       "      <td>HIB</td>\n",
       "      <td>Miguel Calmon</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BA3</td>\n",
       "      <td>O BOTICARIO</td>\n",
       "      <td>THAYLLAN</td>\n",
       "      <td>Caio Luna</td>\n",
       "      <td>FERNANDA</td>\n",
       "      <td>ATIVO</td>\n",
       "      <td>HARY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>24268</td>\n",
       "      <td>LJ</td>\n",
       "      <td>COMERCIO-LJ JACOBINA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BA3</td>\n",
       "      <td>O BOTICARIO</td>\n",
       "      <td>THAYLLAN</td>\n",
       "      <td>Caio Luna</td>\n",
       "      <td>FERNANDA</td>\n",
       "      <td>ATIVO</td>\n",
       "      <td>LOJA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>24269</td>\n",
       "      <td>VD</td>\n",
       "      <td>COMERCIO-ER JACOBINA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BA3</td>\n",
       "      <td>O BOTICARIO</td>\n",
       "      <td>JEFFERSON</td>\n",
       "      <td>Caio Luna</td>\n",
       "      <td>FERNANDA</td>\n",
       "      <td>ATIVO</td>\n",
       "      <td>HARY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>24293</td>\n",
       "      <td>HIB</td>\n",
       "      <td>COMERCIO-HIB MORRO DO CHAPEU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BA3</td>\n",
       "      <td>O BOTICARIO</td>\n",
       "      <td>MARCYARA</td>\n",
       "      <td>Alysson</td>\n",
       "      <td>FERNANDA</td>\n",
       "      <td>ATIVO</td>\n",
       "      <td>DIELLY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>23813</td>\n",
       "      <td>HIB</td>\n",
       "      <td>VALENTE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BA</td>\n",
       "      <td>O BOTICARIO</td>\n",
       "      <td>MARCYARA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLÁUDIA</td>\n",
       "      <td>ATIVO</td>\n",
       "      <td>HARY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>84 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      PDV CANAL                     DESCRIÇÃO  \\\n",
       "0   23156    LJ           SHOPPING CENTRO SUL   \n",
       "1    4494   MTZ                    ESCRITORIO   \n",
       "2    1137   MTZ                           AMG   \n",
       "3   12522    LJ               MACEIO SHOP EXP   \n",
       "4   12817    LJ                SHOPPING PATIO   \n",
       "..    ...   ...                           ...   \n",
       "79  24257   HIB                 Miguel Calmon   \n",
       "80  24268    LJ          COMERCIO-LJ JACOBINA   \n",
       "81  24269    VD          COMERCIO-ER JACOBINA   \n",
       "82  24293   HIB  COMERCIO-HIB MORRO DO CHAPEU   \n",
       "85  23813   HIB                       VALENTE   \n",
       "\n",
       "                                PDV DESC     REGIÃO   ESTADO  CIDADE   UF  \\\n",
       "0                                    NaN        NaN  SERGIPE     NaN   SE   \n",
       "1       4494-COMERCIO-PONTA VERDE-MACEIO         ND  ALAGOAS  MACEIÓ   AL   \n",
       "2                      1137-AMG SERRARIA         ND  ALAGOAS  MACEIÓ   AL   \n",
       "3   12522-COMERCIO -MACEIO SHOP EXPANSAO  MCZ BAIXA  ALAGOAS  MACEIÓ   AL   \n",
       "4         12817-COMERCIO -SHOPPING PATIO   MCZ ALTA  ALAGOAS  MACEIÓ   AL   \n",
       "..                                   ...        ...      ...     ...  ...   \n",
       "79                                   NaN        NaN      NaN     NaN  BA3   \n",
       "80                                   NaN        NaN      NaN     NaN  BA3   \n",
       "81                                   NaN        NaN      NaN     NaN  BA3   \n",
       "82                                   NaN        NaN      NaN     NaN  BA3   \n",
       "85                                   NaN        NaN      NaN     NaN   BA   \n",
       "\n",
       "          MARCA   ANALISTA           GESTÃO          SUPERVISOR   STATUS  \\\n",
       "0           NaN    Inativa          Inativa             Inativa  INATIVO   \n",
       "1    CP GINSENG    Inativa          Inativa             Inativa  INATIVO   \n",
       "2   O BOTICARIO    Inativa          Inativa             Inativa  INATIVO   \n",
       "3   O BOTICARIO       LUAN      Betina Melo  Efigênia Herculano    ATIVO   \n",
       "4   O BOTICARIO  JEFFERSON  Pamella Barbosa      Maxwell Vieira    ATIVO   \n",
       "..          ...        ...              ...                 ...      ...   \n",
       "79  O BOTICARIO   THAYLLAN       Caio Luna             FERNANDA    ATIVO   \n",
       "80  O BOTICARIO   THAYLLAN       Caio Luna             FERNANDA    ATIVO   \n",
       "81  O BOTICARIO  JEFFERSON       Caio Luna             FERNANDA    ATIVO   \n",
       "82  O BOTICARIO   MARCYARA          Alysson            FERNANDA    ATIVO   \n",
       "85  O BOTICARIO   MARCYARA              NaN             CLÁUDIA    ATIVO   \n",
       "\n",
       "   ANALISTA EUD  \n",
       "0          LOJA  \n",
       "1       INATIVO  \n",
       "2       INATIVO  \n",
       "3          LOJA  \n",
       "4          LOJA  \n",
       "..          ...  \n",
       "79         HARY  \n",
       "80         LOJA  \n",
       "81         HARY  \n",
       "82       DIELLY  \n",
       "85         HARY  \n",
       "\n",
       "[84 rows x 14 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_pdv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a3a045d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "#trativa de dados\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') | (df_pdv['UF'] == 'BA3'),'BA',df_pdv['UF'])\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": 23,
   "id": "df04a501",
   "metadata": {},
   "outputs": [],
   "source": [
    "# DISTRIBUINDO OS PDVS PARA OS SIMILARES\n",
    "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": 24,
   "id": "f229ed0f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PRODUTO LANÇAMENTO\n",
       "86116    76\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#CHECAGEM DE QTD PDVS POR PRODUTO LANÇAMENTO.\n",
    "df_similares['PRODUTO LANÇAMENTO'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "0da911af",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joao.herculano\\AppData\\Local\\Temp\\ipykernel_28176\\3630339320.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(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\"../../SUPRIMENTOS/BD_LANÇAMENTOS/BOT/arquivos usados por todos os lançamentos/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(query, conn)\n",
    "conn.close()\n",
    "\n",
    "dfi['SKU2'] = dfi['SKU2'].fillna(\"-\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>C202415</th>\n",
       "      <th>C202416</th>\n",
       "      <th>C202417</th>\n",
       "      <th>C202501</th>\n",
       "      <th>C202502</th>\n",
       "      <th>C202503</th>\n",
       "      <th>C202504</th>\n",
       "      <th>...</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",
       "      <th>C202514</th>\n",
       "      <th>C202515</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</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>10.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</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",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12522</td>\n",
       "      <td>1296</td>\n",
       "      <td>PMPCK THE BLEND DES ANTIT AER 2x75g</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>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>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12522</td>\n",
       "      <td>1302</td>\n",
       "      <td>PMPCK LILY DES ANTIT AER 2x75g</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</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>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12522</td>\n",
       "      <td>1314</td>\n",
       "      <td>PMPCK ZAAD DES ANTIT AER 2x75g</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>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>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12522</td>\n",
       "      <td>1317</td>\n",
       "      <td>PMPCK MALBEC DES ANTIT AER 2x75g</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</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  C202415  C202416  \\\n",
       "0  12522       1080  INTENSE GLOS LAB BUBBAL TUT/FRUT 5ml      0.0     10.0   \n",
       "1  12522       1296   PMPCK THE BLEND DES ANTIT AER 2x75g      3.0      2.0   \n",
       "2  12522       1302        PMPCK LILY DES ANTIT AER 2x75g      5.0      6.0   \n",
       "3  12522       1314        PMPCK ZAAD DES ANTIT AER 2x75g      1.0      1.0   \n",
       "4  12522       1317      PMPCK MALBEC DES ANTIT AER 2x75g      2.0      5.0   \n",
       "\n",
       "   C202417  C202501  C202502  C202503  C202504  ...  C202506  C202507  \\\n",
       "0      2.0      2.0      1.0      2.0      3.0  ...      7.0     17.0   \n",
       "1      0.0      0.0      0.0      0.0      0.0  ...      0.0      0.0   \n",
       "2      0.0      0.0      0.0      0.0      0.0  ...      3.0      4.0   \n",
       "3      0.0      0.0      0.0      0.0      0.0  ...      0.0      0.0   \n",
       "4      0.0      1.0      3.0      0.0      0.0  ...      1.0      1.0   \n",
       "\n",
       "   C202508  C202509  C202510  C202511  C202512  C202513  C202514  C202515  \n",
       "0      0.0      0.0      0.0      0.0      0.0      0.0      0.0      0.0  \n",
       "1      0.0      0.0      0.0      0.0      0.0      2.0      1.0      0.0  \n",
       "2      0.0      4.0      4.0      2.0      1.0      6.0      0.0      0.0  \n",
       "3      0.0      0.0      0.0      1.0      1.0      1.0      0.0      0.0  \n",
       "4      0.0      2.0      2.0      3.0      2.0      5.0      0.0      0.0  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# 1. Agrupamento horizontalizando as vendas por ciclo. transformando coluna de cilos em cada ciclo por coluna.\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": 27,
   "id": "82cdeaed",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.2.3\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "print(pd.__version__)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "8289d835",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joao.herculano\\AppData\\Local\\Temp\\ipykernel_28176\\3920982216.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(cast(em.SKU_PARA as int) , cast(em.SKU as int)) 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(cast(em.SKU_PARA as int) , cast(em.SKU as int)) 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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "dd49288f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_draft = df_draft_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "b110a12f",
   "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>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>preço</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20998</td>\n",
       "      <td>57438</td>\n",
       "      <td>MAKE B BAT GLOSS C/AC POLIGL CORAL 3,6g</td>\n",
       "      <td>E</td>\n",
       "      <td>MAQUIAGEM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0,04</td>\n",
       "      <td>18.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20998</td>\n",
       "      <td>81628</td>\n",
       "      <td>MAKE B BAT GLOSS C/AC POLIGL NUDE 3,6g</td>\n",
       "      <td>C</td>\n",
       "      <td>MAQUIAGEM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0,02</td>\n",
       "      <td>18.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20998</td>\n",
       "      <td>81621</td>\n",
       "      <td>MAKE B BAT MATE C/AC POLIG ORANGE FEV 4g</td>\n",
       "      <td>C</td>\n",
       "      <td>MAQUIAGEM</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>16.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20998</td>\n",
       "      <td>55984</td>\n",
       "      <td>MAKE B BAT ST/PREN HYAL CAND TOF V3 3,4g</td>\n",
       "      <td>C</td>\n",
       "      <td>MAQUIAGEM</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0,02</td>\n",
       "      <td>21.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20998</td>\n",
       "      <td>58566</td>\n",
       "      <td>MAKE B CORRET LIQ FAC EFFECT 10 5,7ml</td>\n",
       "      <td>C</td>\n",
       "      <td>MAQUIAGEM</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>15.30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PDV    SKU                                 DESCRICAO curva  categoria  \\\n",
       "0  20998  57438   MAKE B BAT GLOSS C/AC POLIGL CORAL 3,6g     E  MAQUIAGEM   \n",
       "1  20998  81628    MAKE B BAT GLOSS C/AC POLIGL NUDE 3,6g     C  MAQUIAGEM   \n",
       "2  20998  81621  MAKE B BAT MATE C/AC POLIG ORANGE FEV 4g     C  MAQUIAGEM   \n",
       "3  20998  55984  MAKE B BAT ST/PREN HYAL CAND TOF V3 3,4g     C  MAQUIAGEM   \n",
       "4  20998  58566     MAKE B CORRET LIQ FAC EFFECT 10 5,7ml     C  MAQUIAGEM   \n",
       "\n",
       "   proj_mar  proj_mar+1  ESTOQUE ATUAL  ESTOQUE EM TRANSITO  PEDIDO PENDENTE  \\\n",
       "0       1.0         3.0            0.0                  0.0              0.0   \n",
       "1       1.0         0.0            1.0                  0.0              0.0   \n",
       "2       0.0         0.0           10.0                  0.0              0.0   \n",
       "3       1.0         0.0            9.0                  0.0              0.0   \n",
       "4       2.0         1.0            0.0                  1.0              1.0   \n",
       "\n",
       "  DDV PREVISTO  preço  \n",
       "0         0,04  18.29  \n",
       "1         0,02  18.29  \n",
       "2            0  16.66  \n",
       "3         0,02  21.67  \n",
       "4         None  15.30  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_draft.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "67dd3c27",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joao.herculano\\AppData\\Local\\Temp\\ipykernel_28176\\2417376295.py:4: 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_28176\\2417376295.py:6: 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_28176\\2417376295.py:8: 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": [
       "(278761, 12)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# REMOVENDO OUI DOS PRODUTOS BOTI\n",
    "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": 32,
   "id": "355778d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joao.herculano\\AppData\\Local\\Temp\\ipykernel_28176\\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_28176\\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_28176\\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": 33,
   "id": "d891c575",
   "metadata": {},
   "outputs": [],
   "source": [
    "#agrupamento pra evitar duplicidade\n",
    "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": 34,
   "id": "3d13ef4c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_draft['SKU'] = df_draft['SKU'].astype('Int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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": 36,
   "id": "91298cde",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['C202415', 'C202416', 'C202417', 'C202501', 'C202502', 'C202503',\n",
       "       'C202504', 'C202505', 'C202506', 'C202507', 'C202508', 'C202509',\n",
       "       'C202510', 'C202511', 'C202512', 'C202513', 'C202514', 'C202515'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# OLHO COLUNAS DE VENDA\n",
    "df_draft.columns[13:31]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "34e179cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joao.herculano\\AppData\\Local\\Temp\\ipykernel_28176\\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": 38,
   "id": "94aa432f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    58363\n",
       "1    58363\n",
       "2    58363\n",
       "3    58363\n",
       "4    58363\n",
       "Name: PRODUTO SIMILAR, dtype: Int64"
      ]
     },
     "execution_count": 38,
     "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": 39,
   "id": "38b0eb5d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PDV    object\n",
       "SKU     Int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_draft[['PDV', 'SKU']].dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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": 41,
   "id": "2c9f011d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PRODUTO SIMILAR\n",
       "58363    76\n",
       "Name: count, dtype: Int64"
      ]
     },
     "execution_count": 41,
     "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": 42,
   "id": "0ff66803",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SKU\n",
       "58363    75\n",
       "Name: count, dtype: Int64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final['SKU'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "64bde00b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_venda_diaria = pd.read_csv(\n",
    "    r\"../../SUPRIMENTOS/BD_LANÇAMENTOS/BOT/arquivos usados por todos os lançamentos/vendas 20250815.csv\",\n",
    "    sep=';',\n",
    "    dtype={'SKU_2': str},decimal=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "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": 45,
   "id": "1d25e5df",
   "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</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 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": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_venda_diaria.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "5d0d79f2",
   "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>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>12</td>\n",
       "      <td>C202406</td>\n",
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       "      <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 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": 46,
     "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": 47,
   "id": "a93427da",
   "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_Total</th>\n",
       "      <th>Ciclo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>12522</td>\n",
       "      <td>51.944</td>\n",
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       "      <td>11</td>\n",
       "      <td>C202307</td>\n",
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       "      <td>77.557</td>\n",
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       "      <td>1</td>\n",
       "      <td>C202405</td>\n",
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       "    <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",
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       "    <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",
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       "      <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  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": 47,
     "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": 48,
   "id": "7d973983",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "\n",
       "    .dataframe 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_Total</th>\n",
       "      <th>Ciclo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [PDV, SKU, DESCRICAO, Vendas_Total, Ciclo]\n",
       "Index: []"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_venda_diaria[(df_venda_diaria['PDV']==14668) & (df_venda_diaria['SKU']=='85096')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "6ddec856",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
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       "      <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>11</td>\n",
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       "      <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",
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       "    <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",
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       "    <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  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": 49,
     "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": 50,
   "id": "882e68aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['PDV', 'SKU', 'DESCRICAO', 'Vendas_Total', 'Ciclo'], dtype='object')"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_venda_diaria.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "0c288d75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <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_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": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_venda_diaria"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "bdf6abbb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CICLO SIMILAR      object\n",
       "PRODUTO SIMILAR     Int64\n",
       "PDV                 int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final[['CICLO SIMILAR','PRODUTO SIMILAR','PDV']].dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "dc452c72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(76, 61)"
      ]
     },
     "execution_count": 53,
     "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": 54,
   "id": "c9de258b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\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>C202513</th>\n",
       "      <th>C202514</th>\n",
       "      <th>C202515</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>86116</td>\n",
       "      <td>CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...</td>\n",
       "      <td>58363</td>\n",
       "      <td>Body Splash Desodrante Colônia Cuide-se Bem Nu...</td>\n",
       "      <td>C202506</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>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.1178</td>\n",
       "      <td>C202517</td>\n",
       "      <td>2025-12-01</td>\n",
       "      <td>2025-12-25</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>86116</td>\n",
       "      <td>CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...</td>\n",
       "      <td>58363</td>\n",
       "      <td>Body Splash Desodrante Colônia Cuide-se Bem Nu...</td>\n",
       "      <td>C202506</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>12.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.1177</td>\n",
       "      <td>C202517</td>\n",
       "      <td>2025-12-01</td>\n",
       "      <td>2025-12-25</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86116</td>\n",
       "      <td>CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...</td>\n",
       "      <td>58363</td>\n",
       "      <td>Body Splash Desodrante Colônia Cuide-se Bem Nu...</td>\n",
       "      <td>C202506</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>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.0883</td>\n",
       "      <td>C202517</td>\n",
       "      <td>2025-12-01</td>\n",
       "      <td>2025-12-25</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86116</td>\n",
       "      <td>CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...</td>\n",
       "      <td>58363</td>\n",
       "      <td>Body Splash Desodrante Colônia Cuide-se Bem Nu...</td>\n",
       "      <td>C202506</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>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.1160</td>\n",
       "      <td>C202517</td>\n",
       "      <td>2025-12-01</td>\n",
       "      <td>2025-12-25</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86116</td>\n",
       "      <td>CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...</td>\n",
       "      <td>58363</td>\n",
       "      <td>Body Splash Desodrante Colônia Cuide-se Bem Nu...</td>\n",
       "      <td>C202506</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>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.1009</td>\n",
       "      <td>C202517</td>\n",
       "      <td>2025-12-01</td>\n",
       "      <td>2025-12-25</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 61 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   PRODUTO LANÇAMENTO                            DESCRIÇÃO DO LANÇAMENTO  \\\n",
       "0               86116  CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...   \n",
       "1               86116  CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...   \n",
       "2               86116  CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...   \n",
       "3               86116  CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...   \n",
       "4               86116  CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...   \n",
       "\n",
       "   PRODUTO SIMILAR                                  DESCRIÇÃO SIMILAR  \\\n",
       "0            58363  Body Splash Desodrante Colônia Cuide-se Bem Nu...   \n",
       "1            58363  Body Splash Desodrante Colônia Cuide-se Bem Nu...   \n",
       "2            58363  Body Splash Desodrante Colônia Cuide-se Bem Nu...   \n",
       "3            58363  Body Splash Desodrante Colônia Cuide-se Bem Nu...   \n",
       "4            58363  Body Splash Desodrante Colônia Cuide-se Bem Nu...   \n",
       "\n",
       "  CICLO SIMILAR FOCO  IAF   CATEGORIA         MARCA % CONSUMIDOR  ... C202513  \\\n",
       "0       C202506  Não  Não  PERFUMARIA  CUIDE-SE BEM            -  ...     4.0   \n",
       "1       C202506  Não  Não  PERFUMARIA  CUIDE-SE BEM            -  ...    12.0   \n",
       "2       C202506  Não  Não  PERFUMARIA  CUIDE-SE BEM            -  ...     3.0   \n",
       "3       C202506  Não  Não  PERFUMARIA  CUIDE-SE BEM            -  ...     2.0   \n",
       "4       C202506  Não  Não  PERFUMARIA  CUIDE-SE BEM            -  ...     9.0   \n",
       "\n",
       "  C202514 C202515 CRESCIMENTO    Ciclo  INICIO CICLO  FIM CICLO DURAÇÃO match  \\\n",
       "0     0.0     0.0     -0.1178  C202517    2025-12-01 2025-12-25      25     1   \n",
       "1     3.0     0.0     -0.1177  C202517    2025-12-01 2025-12-25      25     1   \n",
       "2     1.0     0.0     -0.0883  C202517    2025-12-01 2025-12-25      25     1   \n",
       "3     0.0     0.0     -0.1160  C202517    2025-12-01 2025-12-25      25     1   \n",
       "4     0.0     0.0     -0.1009  C202517    2025-12-01 2025-12-25      25     1   \n",
       "\n",
       "  dias_ate_inicio  \n",
       "0              45  \n",
       "1              45  \n",
       "2              45  \n",
       "3              45  \n",
       "4              45  \n",
       "\n",
       "[5 rows x 61 columns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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": 56,
   "id": "cc65edab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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 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": 56,
     "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": 57,
   "id": "6367ac21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       C202506\n",
       "28      C202506\n",
       "56      C202506\n",
       "84      C202506\n",
       "112     C202506\n",
       "         ...   \n",
       "1988    C202506\n",
       "2016    C202506\n",
       "2044    C202506\n",
       "2072    C202506\n",
       "2100    C202506\n",
       "Name: CICLO SIMILAR, Length: 76, dtype: object"
      ]
     },
     "execution_count": 57,
     "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": 58,
   "id": "b0af59cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <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>C202506</td>\n",
       "      <td>58363</td>\n",
       "      <td>12522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>C202506</td>\n",
       "      <td>58363</td>\n",
       "      <td>12817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>C202506</td>\n",
       "      <td>58363</td>\n",
       "      <td>12818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>C202506</td>\n",
       "      <td>58363</td>\n",
       "      <td>12820</td>\n",
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       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>C202506</td>\n",
       "      <td>58363</td>\n",
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      ],
      "text/plain": [
       "    CICLO SIMILAR  PRODUTO SIMILAR    PDV\n",
       "0         C202506            58363  12522\n",
       "28        C202506            58363  12817\n",
       "56        C202506            58363  12818\n",
       "84        C202506            58363  12820\n",
       "112       C202506            58363  12823"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final[['CICLO SIMILAR','PRODUTO SIMILAR','PDV']].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "72925ca7",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "df_final['PRODUTO SIMILAR'] = df_final['PRODUTO SIMILAR'].astype('Int64')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "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",
       "       'ANALISTA EUD', 'SKU', 'curva', 'categoria', 'proj_mar', 'proj_mar+1',\n",
       "       'ESTOQUE ATUAL', 'ESTOQUE EM TRANSITO', 'PEDIDO PENDENTE',\n",
       "       'DDV PREVISTO', 'preço', 'SKU_FINAL', 'DESCRICAO', 'C202415', 'C202416',\n",
       "       'C202417', 'C202501', 'C202502', 'C202503', 'C202504', 'C202505',\n",
       "       'C202506', 'C202507', 'C202508', 'C202509', 'C202510', 'C202511',\n",
       "       'C202512', 'C202513', 'C202514', 'C202515', 'CRESCIMENTO', 'Ciclo_x',\n",
       "       'INICIO CICLO_x', 'FIM CICLO_x', 'DURAÇÃO_x', 'match',\n",
       "       'dias_ate_inicio', 'Ciclo_y', 'INICIO CICLO_y', 'FIM CICLO_y',\n",
       "       'DURAÇÃO_y'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "1efff472",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\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": 61,
     "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": 62,
   "id": "62ea79f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final['PRODUTO SIMILAR'] = df_final['PRODUTO SIMILAR'].astype('str')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "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": 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(1)"
      ]
     },
     "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 ATUAL', 'ESTOQUE EM TRANSITO', 'PEDIDO PENDENTE',\n",
       "       'DDV PREVISTO', 'preço', 'SKU_FINAL', 'DESCRICAO', 'C202415', 'C202416',\n",
       "       'C202417', 'C202501', 'C202502', 'C202503', 'C202504', 'C202505',\n",
       "       'C202506', 'C202507'],\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\"../../SUPRIMENTOS/BD_LANÇAMENTOS/BOT/arquivos usados por todos os lançamentos/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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       "\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>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",
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       "      <td>5</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
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       "      <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": {
      "text/html": [
       "<div>\n",
       "<style scoped>\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>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",
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       "      <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>86116</td>\n",
       "      <td>CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...</td>\n",
       "      <td>58363</td>\n",
       "      <td>Body Splash Desodrante Colônia Cuide-se Bem Nu...</td>\n",
       "      <td>C202506</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>25</td>\n",
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       "      <td>45</td>\n",
       "      <td>C202506</td>\n",
       "      <td>2025-04-14</td>\n",
       "      <td>2025-05-11</td>\n",
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       "      <td>58363</td>\n",
       "      <td>C202506</td>\n",
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       "      <td>CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...</td>\n",
       "      <td>58363</td>\n",
       "      <td>Body Splash Desodrante Colônia Cuide-se Bem Nu...</td>\n",
       "      <td>C202506</td>\n",
       "      <td>Não</td>\n",
       "      <td>Não</td>\n",
       "      <td>PERFUMARIA</td>\n",
       "      <td>CUIDE-SE BEM</td>\n",
       "      <td>-</td>\n",
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       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>C202506</td>\n",
       "      <td>2025-04-14</td>\n",
       "      <td>2025-05-11</td>\n",
       "      <td>28</td>\n",
       "      <td>58363</td>\n",
       "      <td>C202506</td>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86116</td>\n",
       "      <td>CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...</td>\n",
       "      <td>58363</td>\n",
       "      <td>Body Splash Desodrante Colônia Cuide-se Bem Nu...</td>\n",
       "      <td>C202506</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>25</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>C202506</td>\n",
       "      <td>2025-04-14</td>\n",
       "      <td>2025-05-11</td>\n",
       "      <td>28</td>\n",
       "      <td>58363</td>\n",
       "      <td>C202506</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86116</td>\n",
       "      <td>CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...</td>\n",
       "      <td>58363</td>\n",
       "      <td>Body Splash Desodrante Colônia Cuide-se Bem Nu...</td>\n",
       "      <td>C202506</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>25</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>C202506</td>\n",
       "      <td>2025-04-14</td>\n",
       "      <td>2025-05-11</td>\n",
       "      <td>28</td>\n",
       "      <td>58363</td>\n",
       "      <td>C202506</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86116</td>\n",
       "      <td>CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...</td>\n",
       "      <td>58363</td>\n",
       "      <td>Body Splash Desodrante Colônia Cuide-se Bem Nu...</td>\n",
       "      <td>C202506</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>25</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>C202506</td>\n",
       "      <td>2025-04-14</td>\n",
       "      <td>2025-05-11</td>\n",
       "      <td>28</td>\n",
       "      <td>58363</td>\n",
       "      <td>C202506</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 68 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   PRODUTO LANÇAMENTO                            DESCRIÇÃO DO LANÇAMENTO  \\\n",
       "0               86116  CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...   \n",
       "1               86116  CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...   \n",
       "2               86116  CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...   \n",
       "3               86116  CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...   \n",
       "4               86116  CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...   \n",
       "\n",
       "   PRODUTO SIMILAR                                  DESCRIÇÃO SIMILAR  \\\n",
       "0            58363  Body Splash Desodrante Colônia Cuide-se Bem Nu...   \n",
       "1            58363  Body Splash Desodrante Colônia Cuide-se Bem Nu...   \n",
       "2            58363  Body Splash Desodrante Colônia Cuide-se Bem Nu...   \n",
       "3            58363  Body Splash Desodrante Colônia Cuide-se Bem Nu...   \n",
       "4            58363  Body Splash Desodrante Colônia Cuide-se Bem Nu...   \n",
       "\n",
       "  CICLO SIMILAR FOCO  IAF   CATEGORIA         MARCA % CONSUMIDOR  ...  \\\n",
       "0       C202506  Não  Não  PERFUMARIA  CUIDE-SE BEM            -  ...   \n",
       "1       C202506  Não  Não  PERFUMARIA  CUIDE-SE BEM            -  ...   \n",
       "2       C202506  Não  Não  PERFUMARIA  CUIDE-SE BEM            -  ...   \n",
       "3       C202506  Não  Não  PERFUMARIA  CUIDE-SE BEM            -  ...   \n",
       "4       C202506  Não  Não  PERFUMARIA  CUIDE-SE BEM            -  ...   \n",
       "\n",
       "  DURAÇÃO_x match dias_ate_inicio  Ciclo_y  INICIO CICLO_y  FIM CICLO_y  \\\n",
       "0        25     1              45  C202506      2025-04-14   2025-05-11   \n",
       "1        25     1              45  C202506      2025-04-14   2025-05-11   \n",
       "2        25     1              45  C202506      2025-04-14   2025-05-11   \n",
       "3        25     1              45  C202506      2025-04-14   2025-05-11   \n",
       "4        25     1              45  C202506      2025-04-14   2025-05-11   \n",
       "\n",
       "  DURAÇÃO_y  SKU_y    Ciclo Vendas Ciclo Lançamento  \n",
       "0        28  58363  C202506                      40  \n",
       "1        28  58363  C202506                     102  \n",
       "2        28  58363  C202506                      15  \n",
       "3        28  58363  C202506                      13  \n",
       "4        28  58363  C202506                      24  \n",
       "\n",
       "[5 rows x 68 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": "dcff1fcb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final = df_final.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "bebabb9f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['C202415', 'C202416', 'C202417', 'C202501', 'C202502', 'C202503',\n",
       "       'C202504', 'C202505', 'C202506', 'C202507', 'C202508', 'C202509',\n",
       "       'C202510', 'C202511', 'C202512', 'C202513', 'C202514', 'C202515'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# VERIFICAR SE TEM OS 17 CICLOS DE VENDA\n",
    "df_final.columns[36:54]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "0a1bb832",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.2"
      ]
     },
     "execution_count": 76,
     "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[36:54]\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": 77,
   "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": 78,
   "id": "b107e519",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['C202509', 'C202510', 'C202511', 'C202512', 'C202513', 'C202514',\n",
       "       'C202515'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# VERIFICAR SE AS 6 ULTIMAS COLUNAS SÃO DE VENDA CICLO\n",
    "df_final.columns[47:54]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "8290853c",
   "metadata": {},
   "outputs": [],
   "source": [
    "VENDA_SIMILAR_6_MESES= df_final.columns[47:54]\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": 80,
   "id": "d8b30560",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     0.0\n",
       "1     1.0\n",
       "2     0.0\n",
       "3     0.0\n",
       "4     0.0\n",
       "     ... \n",
       "71    0.0\n",
       "72    0.0\n",
       "73    0.0\n",
       "74    0.0\n",
       "75    0.0\n",
       "Length: 76, dtype: float64"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final[colunas_mensais].median(axis=1, skipna=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "07f043f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>86116</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>HIB</td>\n",
       "      <td>AL</td>\n",
       "      <td>86116</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HIB</td>\n",
       "      <td>BA</td>\n",
       "      <td>86116</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HIB</td>\n",
       "      <td>SE</td>\n",
       "      <td>86116</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LJ</td>\n",
       "      <td>AL</td>\n",
       "      <td>86116</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>LJ</td>\n",
       "      <td>BA</td>\n",
       "      <td>86116</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>LJ</td>\n",
       "      <td>SE</td>\n",
       "      <td>86116</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>VD</td>\n",
       "      <td>AL</td>\n",
       "      <td>86116</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>VD</td>\n",
       "      <td>BA</td>\n",
       "      <td>86116</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>VD</td>\n",
       "      <td>SE</td>\n",
       "      <td>86116</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  CANAL  UF  PRODUTO LANÇAMENTO  med_por_canal\n",
       "0    CD  AL               86116            0.0\n",
       "1   HIB  AL               86116            1.0\n",
       "2   HIB  BA               86116            1.0\n",
       "3   HIB  SE               86116            0.5\n",
       "4    LJ  AL               86116            1.0\n",
       "5    LJ  BA               86116            0.5\n",
       "6    LJ  SE               86116            0.5\n",
       "7    VD  AL               86116            4.5\n",
       "8    VD  BA               86116            2.0\n",
       "9    VD  SE               86116            4.0"
      ]
     },
     "execution_count": 81,
     "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": 82,
   "id": "ef979be5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_dourado = pd.read_excel(r\"../../SUPRIMENTOS/BD_LANÇAMENTOS/BOT/arquivos usados por todos os lançamentos/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": 83,
   "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": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final['PDV'] = df_final['PDV'].astype(str)\n",
    "df_final['PDV'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "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": 85,
   "id": "7986b8fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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",
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       "  <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",
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       "      <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",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <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",
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       "      <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": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_depara_vdc = pd.read_excel(r\"../../SUPRIMENTOS/BD_LANÇAMENTOS/BOT/arquivos usados por todos os lançamentos/Filiais - Vitoria da Conquista 4.xlsx\")\n",
    "\n",
    "df_depara_vdc.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "84b5917c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final['PRODUTO SIMILAR'] = df_final['PRODUTO SIMILAR'].astype('Int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "1a625e69",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(76, 92)"
      ]
     },
     "execution_count": 87,
     "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": 88,
   "id": "30c1d83d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['202408', '202409', '202410', '202411', '202412', '202413', '202414',\n",
      "       '202415', '202416', '202417', '202501', '202502', '202503', '202504',\n",
      "       '202505', '202506', '202507'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "# verificar as vendas dos ciclos\n",
    "print(df_final.columns[68:85])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "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",
       "       'ANALISTA EUD', 'SKU_x', 'curva', 'categoria', 'proj_mar', 'proj_mar+1',\n",
       "       'ESTOQUE ATUAL', 'ESTOQUE EM TRANSITO', 'PEDIDO PENDENTE',\n",
       "       'DDV PREVISTO', 'preço', 'SKU_FINAL', 'DESCRICAO', 'C202415', 'C202416',\n",
       "       'C202417', 'C202501', 'C202502', 'C202503', 'C202504', 'C202505',\n",
       "       'C202506', 'C202507', 'C202508', 'C202509', 'C202510', 'C202511',\n",
       "       'C202512', 'C202513', 'C202514', 'C202515', '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', 'CRESCIMENTO_GERAL',\n",
       "       'Pico Vendas Similar Ultimos 6 ciclos', 'MEDIANA DO HISTÓRICO',\n",
       "       'de para pdv', 'sku', 'CRESCIMENTO_FINAL', 'PV GINSENG'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 89,
     "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": 90,
   "id": "3b7f3a82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['C202511', 'C202512', 'C202513', 'C202514', 'C202515'], dtype='object')"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.columns[49:54]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "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": 92,
   "id": "15b7149f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final = df_final.rename(columns={df_final.columns[49]: \"C-4\", df_final.columns[50]: \"C-3\",df_final.columns[51]: \"C-2\",df_final.columns[52]: \"C-1\",df_final.columns[53]:'VENDAS CICLO ATUAL'})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "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",
       "       'ANALISTA EUD', 'SKU_X', 'CURVA', 'CATEGORIA', 'PROJ_MAR', 'PROJ_MAR+1',\n",
       "       'ESTOQUE ATUAL', 'ESTOQUE EM TRANSITO', 'PEDIDO PENDENTE',\n",
       "       'DDV PREVISTO', 'PREÇO', 'SKU_FINAL', 'DESCRICAO', 'C202415', 'C202416',\n",
       "       'C202417', 'C202501', 'C202502', 'C202503', 'C202504', 'C202505',\n",
       "       'C202506', 'C202507', 'C202508', 'C202509', 'C202510', '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', 'CRESCIMENTO_GERAL',\n",
       "       'PICO VENDAS SIMILAR ULTIMOS 6 CICLOS', 'MEDIANA DO HISTÓRICO',\n",
       "       'DE PARA PDV', 'SKU', 'CRESCIMENTO_FINAL', 'PV GINSENG'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 93,
     "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": 94,
   "id": "dceebd16",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final = df_final.rename(columns={'MARCA_X':'MARCA'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "62ce5c62",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(76, 74)"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "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": 97,
   "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",
    "    'CURVA',\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": 98,
   "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": 99,
   "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": 100,
   "id": "df9f0130",
   "metadata": {},
   "outputs": [],
   "source": [
    "#adicionando o UF correto ao fim do script\n",
    "df_final= pd.merge(df_final,df_pdv_origi[['UF_CERTO','PDV']],on='PDV',how='inner')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "f8cd886a",
   "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>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>CURVA</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>86116</td>\n",
       "      <td>CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...</td>\n",
       "      <td>CUIDE-SE BEM</td>\n",
       "      <td>A</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>48</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>86116</td>\n",
       "      <td>CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...</td>\n",
       "      <td>CUIDE-SE BEM</td>\n",
       "      <td>B</td>\n",
       "      <td>...</td>\n",
       "      <td>39.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>122</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>86116</td>\n",
       "      <td>CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...</td>\n",
       "      <td>CUIDE-SE BEM</td>\n",
       "      <td>B</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>18</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>ADRIELY</td>\n",
       "      <td>LJ</td>\n",
       "      <td>AL</td>\n",
       "      <td>12820</td>\n",
       "      <td>ATACADÃO</td>\n",
       "      <td>86116</td>\n",
       "      <td>CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...</td>\n",
       "      <td>CUIDE-SE BEM</td>\n",
       "      <td>B</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>16</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>ADRIELY</td>\n",
       "      <td>LJ</td>\n",
       "      <td>AL</td>\n",
       "      <td>12823</td>\n",
       "      <td>PONTA VERDE</td>\n",
       "      <td>86116</td>\n",
       "      <td>CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...</td>\n",
       "      <td>CUIDE-SE BEM</td>\n",
       "      <td>A</td>\n",
       "      <td>...</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>29</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 32 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    ADRIELY    LJ  AL  12820         ATACADÃO   \n",
       "4  Efigênia Herculano    ADRIELY    LJ  AL  12823      PONTA VERDE   \n",
       "\n",
       "   PRODUTO LANÇAMENTO                            DESCRIÇÃO DO LANÇAMENTO  \\\n",
       "0               86116  CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...   \n",
       "1               86116  CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...   \n",
       "2               86116  CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...   \n",
       "3               86116  CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...   \n",
       "4               86116  CUIDE-SE BEM DOCES DELÍRIOS ALGODÃO DOCE BODY ...   \n",
       "\n",
       "          MARCA CURVA  ...   C-4   C-3   C-2  C-1 VENDAS CICLO ATUAL  \\\n",
       "0  CUIDE-SE BEM     A  ...   7.0   5.0   4.0  0.0                0.0   \n",
       "1  CUIDE-SE BEM     B  ...  39.0   7.0  12.0  3.0                0.0   \n",
       "2  CUIDE-SE BEM     B  ...   5.0   1.0   3.0  1.0                0.0   \n",
       "3  CUIDE-SE BEM     B  ...   8.0   0.0   2.0  0.0                0.0   \n",
       "4  CUIDE-SE BEM     A  ...  14.0  11.0   9.0  0.0                0.0   \n",
       "\n",
       "  PICO VENDAS SIMILAR ULTIMOS 6 CICLOS PV GINSENG SUGESTÃO METASELLIN  \\\n",
       "0                                  8.0         48                       \n",
       "1                                 39.0        122                       \n",
       "2                                  5.0         18                       \n",
       "3                                  8.0         16                       \n",
       "4                                 14.0         29                       \n",
       "\n",
       "   SUGESTÃO ABASTECIMENTO SUGESTÃO COMERCIAL  \n",
       "0                                             \n",
       "1                                             \n",
       "2                                             \n",
       "3                                             \n",
       "4                                             \n",
       "\n",
       "[5 rows x 32 columns]"
      ]
     },
     "execution_count": 101,
     "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": 102,
   "id": "eaf25e4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['SUPERVISOR', 'ANALISTA', 'CANAL', 'UF', 'PDV', 'DESCRIÇÃO PDV',\n",
       "       'PRODUTO LANÇAMENTO', 'DESCRIÇÃO DO LANÇAMENTO', 'MARCA', 'CURVA',\n",
       "       'CATEGORIA', '% 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": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "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": 104,
   "id": "88d0d6de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['C:',\n",
       " 'Users',\n",
       " 'joao.herculano',\n",
       " 'GRUPO GINSENG',\n",
       " 'Assistência Suprimentos - 2025',\n",
       " 'SUPRIMENTOS',\n",
       " 'BD_LANÇAMENTOS',\n",
       " 'BOT',\n",
       " 'BOT - C17',\n",
       " 'arquivos para geração da sugestão']"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arquivo_similares.split('\\\\')[0:-2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "03af489b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\joao.herculano\\\\GRUPO GINSENG\\\\Assistência Suprimentos - 2025\\\\SUPRIMENTOS\\\\BD_LANÇAMENTOS\\\\BOT\\\\BOT - C17\\\\arquivos para geração da sugestão'"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "caminho_out =arquivo_similares.split('\\\\')[0:-2]\n",
    "\n",
    "resultado_out = \"\\\\\".join(caminho_out)\n",
    "resultado_out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "8fdb44f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CURVA\n",
       "B    63\n",
       "A    10\n",
       "C     2\n",
       "0     1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final_sem_dupli['CURVA'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "c69f7a57",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final_sem_dupli['CURVA'] = df_final_sem_dupli['CURVA'].astype('str')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "56d7ec83",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final_sem_dupli['CURVA'] = df_final_sem_dupli['CURVA'].str.replace('0','E')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "231f00a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CURVA\n",
       "B    63\n",
       "A    10\n",
       "C     2\n",
       "E     1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final_sem_dupli['CURVA'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "2df3e2e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_final_sem_dupli.to_excel(f'{resultado_out}\\\\LANCAMENTO_{hoje}.xlsx',index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "b1566a14",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Export to Excel\n",
    "output_file = f'{resultado_out}\\\\LANCAMENTO_{hoje}.xlsx'\n",
    "with pd.ExcelWriter(output_file, engine='openpyxl') as writer:\n",
    "    df_final_sem_dupli.to_excel(writer, index=False)\n",
    "\n",
    "# Apply styles\n",
    "wb = load_workbook(output_file)\n",
    "ws = wb['Sheet1']\n",
    "\n",
    "# Style header\n",
    "header_fill = PatternFill(start_color='366092', end_color='366092', fill_type='solid')  # Light Blue\n",
    "header_font = Font(color='FFFFFF', bold=True)  # White & Bold\n",
    "\n",
    "for cell in ws[1]:\n",
    "    cell.fill = header_fill\n",
    "    cell.font = header_font\n",
    "\n",
    "# Style rows: gray/white alternating\n",
    "gray_fill = PatternFill(start_color='DDDDDD', end_color='DDDDDD', fill_type='solid')  # Light gray\n",
    "\n",
    "for i, row in enumerate(ws.iter_rows(min_row=2, max_row=ws.max_row), start=2):\n",
    "    if i % 2 == 0:\n",
    "        for cell in row:\n",
    "            cell.fill = gray_fill\n",
    "\n",
    "# Save styled workbook\n",
    "wb.save(output_file)"
   ]
  }
 ],
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