QG_Relatorio .ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "GmD6zr96eKp7"
   },
   "source": [
    "QG Relatotio\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "id": "tUoQCkvmeQXQ"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "id": "3icKRCQjea_-"
   },
   "outputs": [],
   "source": [
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "id": "kRrKeESweg7z"
   },
   "outputs": [],
   "source": [
    "from pandas import DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "id": "oPD9cgz8sTr5"
   },
   "outputs": [],
   "source": [
    "file_path = '/content/report.json'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "id": "hO2PPzmFitM1"
   },
   "outputs": [],
   "source": [
    "#with open('report.json','r') as file:\n",
    "  #  qg = json.load(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "id": "O8MJthTNmArM"
   },
   "outputs": [],
   "source": [
    "qg = pd.read_json(file_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "lY1ujoE0OYDC"
   },
   "source": [
    "# Nova seção"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
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    },
    "id": "lM19ugBTpLui",
    "outputId": "0a15e54d-1735-4cc2-f124-019838e38103"
   },
   "outputs": [
    {
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      "text/plain": [
       "                        _id  NRORG NMORGANIZACAO  CDEMPRESA     NMEMPRESA  \\\n",
       "0  653badd1002c3610c054562f   1335       REDE QG          1  INDUSTRIA QG   \n",
       "1  653badd1002c3610c0545630   1335       REDE QG          1  INDUSTRIA QG   \n",
       "2  653badd1002c3610c0545631   1335       REDE QG          1  INDUSTRIA QG   \n",
       "3  653badd1002c3610c0545632   1335       REDE QG          1  INDUSTRIA QG   \n",
       "4  653badd1002c3610c0545633   1335       REDE QG          1  INDUSTRIA QG   \n",
       "\n",
       "   CDFILIAL               NMFILIAL  CDLOJA                 NMLOJA NMVENDEDOR  \\\n",
       "0         8  QG - GOIANIA SHOPPING       8  QG - GOIANIA SHOPPING     PADRÃO   \n",
       "1         8  QG - GOIANIA SHOPPING       8  QG - GOIANIA SHOPPING     PADRÃO   \n",
       "2         8  QG - GOIANIA SHOPPING       8  QG - GOIANIA SHOPPING     PADRÃO   \n",
       "3         8  QG - GOIANIA SHOPPING       8  QG - GOIANIA SHOPPING     PADRÃO   \n",
       "4         8  QG - GOIANIA SHOPPING       8  QG - GOIANIA SHOPPING     PADRÃO   \n",
       "\n",
       "   ...  VRACRITV VALORVENDA VRDESCON  VRREPIQUE NRPESMESA CUPOM NRPESMESREL  \\\n",
       "0  ...       0.0       0.01      0.0          0       0.5   0.5           1   \n",
       "1  ...       0.0      15.99      0.0          0       0.5   0.5           1   \n",
       "2  ...       0.0       0.01      0.0          0       0.5   0.5           1   \n",
       "3  ...       0.0      18.99      0.0          0       0.5   0.5           1   \n",
       "4  ...       0.0       7.00      0.0          0       0.5   0.5           1   \n",
       "\n",
       "  VRTXENTR VRGORJ CDVENDEDOR  \n",
       "0        0      0        NaN  \n",
       "1        0      0        NaN  \n",
       "2        0      0        NaN  \n",
       "3        0      0        NaN  \n",
       "4        0      0        NaN  \n",
       "\n",
       "[5 rows x 38 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qg.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "id": "_TljtUQbspbE"
   },
   "outputs": [],
   "source": [
    "valores_unicos = qg['CDVENDEDOR'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
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    },
    "id": "ZcyGiXB7uVsO",
    "outputId": "1af97372-0286-4dd9-bc50-32440b5b5376"
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7\n"
     ]
    }
   ],
   "source": [
    "print(valores_unicos)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
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    "id": "CKMBthRKuaaj",
    "outputId": "6a9e625f-001a-4c8a-d4e5-a8cd465236cd"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "_id               object\n",
       "NRORG              int64\n",
       "NMORGANIZACAO     object\n",
       "CDEMPRESA          int64\n",
       "NMEMPRESA         object\n",
       "CDFILIAL           int64\n",
       "NMFILIAL          object\n",
       "CDLOJA             int64\n",
       "NMLOJA            object\n",
       "NMVENDEDOR        object\n",
       "CDOPERADOR         int64\n",
       "NMOPERADOR        object\n",
       "SGESTADO          object\n",
       "NRSEQVENDA         int64\n",
       "TURNO             object\n",
       "NMGRUPPROD        object\n",
       "NMSUBGRPROD       object\n",
       "CDPRODUTO         object\n",
       "NMPRODUTO         object\n",
       "DTVENDA           object\n",
       "DIA               object\n",
       "SEMANA            object\n",
       "PERIO             object\n",
       "TRIMES            object\n",
       "HRPED              int64\n",
       "HRVEN              int64\n",
       "MODAL             object\n",
       "QTDPRODVEND        int64\n",
       "VRACRITV         float64\n",
       "VALORVENDA       float64\n",
       "VRDESCON         float64\n",
       "VRREPIQUE          int64\n",
       "NRPESMESA        float64\n",
       "CUPOM            float64\n",
       "NRPESMESREL        int64\n",
       "VRTXENTR           int64\n",
       "VRGORJ             int64\n",
       "CDVENDEDOR       float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qg.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 0
    },
    "id": "nY7rQJ38uvyN",
    "outputId": "b0fe1abf-58ad-491f-dca3-62cd34c4f320"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       NaN\n",
       "1       NaN\n",
       "2       NaN\n",
       "3       NaN\n",
       "4       NaN\n",
       "         ..\n",
       "13208   NaN\n",
       "13209   NaN\n",
       "13210   NaN\n",
       "13211   NaN\n",
       "13212   NaN\n",
       "Name: CDVENDEDOR, Length: 13213, dtype: float64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qg['CDVENDEDOR']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "id": "c24CmyXPQOxP"
   },
   "outputs": [],
   "source": [
    "colunas = qg.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 0
    },
    "id": "uatV7mAQQTF4",
    "outputId": "4f5f53ab-fb37-4183-b14f-0ceb8f585520"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['_id', 'NRORG', 'NMORGANIZACAO', 'CDEMPRESA', 'NMEMPRESA', 'CDFILIAL',\n",
      "       'NMFILIAL', 'CDLOJA', 'NMLOJA', 'NMVENDEDOR', 'CDOPERADOR',\n",
      "       'NMOPERADOR', 'SGESTADO', 'NRSEQVENDA', 'TURNO', 'NMGRUPPROD',\n",
      "       'NMSUBGRPROD', 'CDPRODUTO', 'NMPRODUTO', 'DTVENDA', 'DIA', 'SEMANA',\n",
      "       'PERIO', 'TRIMES', 'HRPED', 'HRVEN', 'MODAL', 'QTDPRODVEND', 'VRACRITV',\n",
      "       'VALORVENDA', 'VRDESCON', 'VRREPIQUE', 'NRPESMESA', 'CUPOM',\n",
      "       'NRPESMESREL', 'VRTXENTR', 'VRGORJ', 'CDVENDEDOR'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(colunas)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 424
    },
    "id": "RD7S3tavUNMU",
    "outputId": "bf9e2053-efad-4024-99ba-ced4b2e14873"
   },
   "outputs": [
    {
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       "      <th>NMFILIAL</th>\n",
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       "      <th>DTVENDA</th>\n",
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       "      <th>0</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>SALADA VINAGRETE - UN</td>\n",
       "      <td>26/10/2023</td>\n",
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       "      <th>1</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
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       "      <th>3</th>\n",
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       "      <td>26/10/2023</td>\n",
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       "      <td>26/10/2023</td>\n",
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       "      <td>QG - PASSEIO DAS AGUAS</td>\n",
       "      <td>COCA COLA 300 ML - UN</td>\n",
       "      <td>26/10/2023</td>\n",
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       "      <th>13211</th>\n",
       "      <td>QG - PASSEIO DAS AGUAS</td>\n",
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       "      <td>6 PASTEIS + 3 REFRI - UN</td>\n",
       "      <td>26/10/2023</td>\n",
       "    </tr>\n",
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       "<p>13213 rows × 3 columns</p>\n",
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       "\n",
       "  <script>\n",
       "    async function quickchart(key) {\n",
       "      const quickchartButtonEl =\n",
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       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
       "      try {\n",
       "        const charts = await google.colab.kernel.invokeFunction(\n",
       "            'suggestCharts', [key], {});\n",
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       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
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       "    }\n",
       "    (() => {\n",
       "      let quickchartButtonEl =\n",
       "        document.querySelector('#df-231d5e08-040e-420d-919c-a781ce5f1507 button');\n",
       "      quickchartButtonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "    })();\n",
       "  </script>\n",
       "</div>\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "text/plain": [
       "                     NMFILIAL                     NMPRODUTO     DTVENDA\n",
       "0       QG - GOIANIA SHOPPING         SALADA VINAGRETE - UN  26/10/2023\n",
       "1       QG - GOIANIA SHOPPING             GALINHADA QG - UN  26/10/2023\n",
       "2       QG - GOIANIA SHOPPING         SALADA VINAGRETE - UN  26/10/2023\n",
       "3       QG - GOIANIA SHOPPING         ARROZ CARRETEIRO - UN  26/10/2023\n",
       "4       QG - GOIANIA SHOPPING               P DE CARNE - UN  26/10/2023\n",
       "...                       ...                           ...         ...\n",
       "13208  QG - PASSEIO DAS AGUAS  3 MINI BRIGADEIRO COMBO - UN  26/10/2023\n",
       "13209  QG - PASSEIO DAS AGUAS     3 MINI CHURROS COMBO - UN  26/10/2023\n",
       "13210  QG - PASSEIO DAS AGUAS         COCA COLA 300 ML - UN  26/10/2023\n",
       "13211  QG - PASSEIO DAS AGUAS             FANTA 300 ML - UN  26/10/2023\n",
       "13212  QG - PASSEIO DAS AGUAS      6 PASTEIS + 3 REFRI - UN  26/10/2023\n",
       "\n",
       "[13213 rows x 3 columns]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qg[['NMFILIAL','NMPRODUTO','DTVENDA']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "id": "AMpK-y75QVJs"
   },
   "outputs": [],
   "source": [
    "qg_novaTabela = qg[['NMFILIAL','NMLOJA','DTVENDA','NMPRODUTO','VALORVENDA','CUPOM']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 833
    },
    "id": "_2xzKEA0sZY6",
    "outputId": "cd6314ff-60b0-4c72-fad7-c0cbf6f6ed9d"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
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       "      <th>NMFILIAL</th>\n",
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       "      <td>26/10/2023</td>\n",
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       "      <td>QG - GOIANIA SHOPPING</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>ARROZ CARRETEIRO - UN</td>\n",
       "      <td>18.99</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>P DE CARNE - UN</td>\n",
       "      <td>7.00</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>COCA COLA 300 ML - UN</td>\n",
       "      <td>7.00</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>ARROZ - UN</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>FEIJAO CALDO - UN</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>SALADA TRIVIAL - UN</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>PICADINHO DE FRANGO - UN</td>\n",
       "      <td>18.97</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>PURE DE BATATA - UN</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>SALADA TRIVIAL - UN</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>ARROZ CARRETEIRO - UN</td>\n",
       "      <td>22.98</td>\n",
       "      <td>0.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>ARROZ - UN</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>FEIJAO CALDO - UN</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>SALADA TRIVIAL - UN</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>CROC CASEIRINHO - UN</td>\n",
       "      <td>12.97</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>ARROZ - UN</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>FEIJAO CALDO - UN</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>SALADA TRIVIAL - UN</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>GALINHADA QG - UN</td>\n",
       "      <td>15.99</td>\n",
       "      <td>0.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>CROC CASEIRINHO - UN</td>\n",
       "      <td>12.97</td>\n",
       "      <td>0.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>FANTA GUARANA 400 ML - UN</td>\n",
       "      <td>8.00</td>\n",
       "      <td>0.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>SUCO PRATS LARANJA 300ml - UN</td>\n",
       "      <td>9.00</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>QG - GOIANIA SHOPPING</td>\n",
       "      <td>26/10/2023</td>\n",
       "      <td>ARROZ - UN</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>\n",
       "    <div class=\"colab-df-buttons\">\n",
       "\n",
       "  <div class=\"colab-df-container\">\n",
       "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e85fce67-10be-4d83-8259-2da1829787a9')\"\n",
       "            title=\"Convert this dataframe to an interactive table.\"\n",
       "            style=\"display:none;\">\n",
       "\n",
       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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       "  </svg>\n",
       "    </button>\n",
       "\n",
       "  <style>\n",
       "    .colab-df-container {\n",
       "      display:flex;\n",
       "      gap: 12px;\n",
       "    }\n",
       "\n",
       "    .colab-df-convert {\n",
       "      background-color: #E8F0FE;\n",
       "      border: none;\n",
       "      border-radius: 50%;\n",
       "      cursor: pointer;\n",
       "      display: none;\n",
       "      fill: #1967D2;\n",
       "      height: 32px;\n",
       "      padding: 0 0 0 0;\n",
       "      width: 32px;\n",
       "    }\n",
       "\n",
       "    .colab-df-convert:hover {\n",
       "      background-color: #E2EBFA;\n",
       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
       "      fill: #174EA6;\n",
       "    }\n",
       "\n",
       "    .colab-df-buttons div {\n",
       "      margin-bottom: 4px;\n",
       "    }\n",
       "\n",
       "    [theme=dark] .colab-df-convert {\n",
       "      background-color: #3B4455;\n",
       "      fill: #D2E3FC;\n",
       "    }\n",
       "\n",
       "    [theme=dark] .colab-df-convert:hover {\n",
       "      background-color: #434B5C;\n",
       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
       "      fill: #FFFFFF;\n",
       "    }\n",
       "  </style>\n",
       "\n",
       "    <script>\n",
       "      const buttonEl =\n",
       "        document.querySelector('#df-e85fce67-10be-4d83-8259-2da1829787a9 button.colab-df-convert');\n",
       "      buttonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "\n",
       "      async function convertToInteractive(key) {\n",
       "        const element = document.querySelector('#df-e85fce67-10be-4d83-8259-2da1829787a9');\n",
       "        const dataTable =\n",
       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
       "                                                    [key], {});\n",
       "        if (!dataTable) return;\n",
       "\n",
       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
       "          + ' to learn more about interactive tables.';\n",
       "        element.innerHTML = '';\n",
       "        dataTable['output_type'] = 'display_data';\n",
       "        await google.colab.output.renderOutput(dataTable, element);\n",
       "        const docLink = document.createElement('div');\n",
       "        docLink.innerHTML = docLinkHtml;\n",
       "        element.appendChild(docLink);\n",
       "      }\n",
       "    </script>\n",
       "  </div>\n",
       "\n",
       "\n",
       "<div id=\"df-76ad00a2-1ce8-4e50-87c7-487f5ea56ed0\">\n",
       "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-76ad00a2-1ce8-4e50-87c7-487f5ea56ed0')\"\n",
       "            title=\"Suggest charts.\"\n",
       "            style=\"display:none;\">\n",
       "\n",
       "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
       "     width=\"24px\">\n",
       "    <g>\n",
       "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
       "    </g>\n",
       "</svg>\n",
       "  </button>\n",
       "\n",
       "<style>\n",
       "  .colab-df-quickchart {\n",
       "      --bg-color: #E8F0FE;\n",
       "      --fill-color: #1967D2;\n",
       "      --hover-bg-color: #E2EBFA;\n",
       "      --hover-fill-color: #174EA6;\n",
       "      --disabled-fill-color: #AAA;\n",
       "      --disabled-bg-color: #DDD;\n",
       "  }\n",
       "\n",
       "  [theme=dark] .colab-df-quickchart {\n",
       "      --bg-color: #3B4455;\n",
       "      --fill-color: #D2E3FC;\n",
       "      --hover-bg-color: #434B5C;\n",
       "      --hover-fill-color: #FFFFFF;\n",
       "      --disabled-bg-color: #3B4455;\n",
       "      --disabled-fill-color: #666;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart {\n",
       "    background-color: var(--bg-color);\n",
       "    border: none;\n",
       "    border-radius: 50%;\n",
       "    cursor: pointer;\n",
       "    display: none;\n",
       "    fill: var(--fill-color);\n",
       "    height: 32px;\n",
       "    padding: 0;\n",
       "    width: 32px;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart:hover {\n",
       "    background-color: var(--hover-bg-color);\n",
       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
       "    fill: var(--button-hover-fill-color);\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart-complete:disabled,\n",
       "  .colab-df-quickchart-complete:disabled:hover {\n",
       "    background-color: var(--disabled-bg-color);\n",
       "    fill: var(--disabled-fill-color);\n",
       "    box-shadow: none;\n",
       "  }\n",
       "\n",
       "  .colab-df-spinner {\n",
       "    border: 2px solid var(--fill-color);\n",
       "    border-color: transparent;\n",
       "    border-bottom-color: var(--fill-color);\n",
       "    animation:\n",
       "      spin 1s steps(1) infinite;\n",
       "  }\n",
       "\n",
       "  @keyframes spin {\n",
       "    0% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "      border-left-color: var(--fill-color);\n",
       "    }\n",
       "    20% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    30% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    40% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    60% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    80% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "    90% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "  }\n",
       "</style>\n",
       "\n",
       "  <script>\n",
       "    async function quickchart(key) {\n",
       "      const quickchartButtonEl =\n",
       "        document.querySelector('#' + key + ' button');\n",
       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
       "      try {\n",
       "        const charts = await google.colab.kernel.invokeFunction(\n",
       "            'suggestCharts', [key], {});\n",
       "      } catch (error) {\n",
       "        console.error('Error during call to suggestCharts:', error);\n",
       "      }\n",
       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
       "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
       "    }\n",
       "    (() => {\n",
       "      let quickchartButtonEl =\n",
       "        document.querySelector('#df-76ad00a2-1ce8-4e50-87c7-487f5ea56ed0 button');\n",
       "      quickchartButtonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "    })();\n",
       "  </script>\n",
       "</div>\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "text/plain": [
       "                 NMFILIAL                 NMLOJA     DTVENDA  \\\n",
       "0   QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "1   QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "2   QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "3   QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "4   QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "5   QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "6   QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "7   QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "8   QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "9   QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "10  QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "11  QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "12  QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "13  QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "14  QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "15  QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "16  QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "17  QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "18  QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "19  QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "20  QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "21  QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "22  QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "23  QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "24  QG - GOIANIA SHOPPING  QG - GOIANIA SHOPPING  26/10/2023   \n",
       "\n",
       "                        NMPRODUTO  VALORVENDA     CUPOM  \n",
       "0           SALADA VINAGRETE - UN        0.01  0.500000  \n",
       "1               GALINHADA QG - UN       15.99  0.500000  \n",
       "2           SALADA VINAGRETE - UN        0.01  0.500000  \n",
       "3           ARROZ CARRETEIRO - UN       18.99  0.500000  \n",
       "4                 P DE CARNE - UN        7.00  0.500000  \n",
       "5           COCA COLA 300 ML - UN        7.00  0.500000  \n",
       "6                      ARROZ - UN        0.01  0.250000  \n",
       "7               FEIJAO CALDO - UN        0.01  0.250000  \n",
       "8             SALADA TRIVIAL - UN        0.01  0.250000  \n",
       "9        PICADINHO DE FRANGO - UN       18.97  0.250000  \n",
       "10            PURE DE BATATA - UN        0.01  0.333333  \n",
       "11            SALADA TRIVIAL - UN        0.01  0.333333  \n",
       "12          ARROZ CARRETEIRO - UN       22.98  0.333333  \n",
       "13                     ARROZ - UN        0.01  0.250000  \n",
       "14              FEIJAO CALDO - UN        0.01  0.250000  \n",
       "15            SALADA TRIVIAL - UN        0.01  0.250000  \n",
       "16           CROC CASEIRINHO - UN       12.97  0.250000  \n",
       "17                     ARROZ - UN        0.01  0.166667  \n",
       "18              FEIJAO CALDO - UN        0.01  0.166667  \n",
       "19            SALADA TRIVIAL - UN        0.01  0.166667  \n",
       "20              GALINHADA QG - UN       15.99  0.166667  \n",
       "21           CROC CASEIRINHO - UN       12.97  0.166667  \n",
       "22      FANTA GUARANA 400 ML - UN        8.00  0.166667  \n",
       "23  SUCO PRATS LARANJA 300ml - UN        9.00  1.000000  \n",
       "24                     ARROZ - UN        0.01  0.250000  "
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qg_novaTabela.head(25)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 0
    },
    "id": "03iHAjKpX6o9",
    "outputId": "53a9cd37-bbde-4b28-9bb6-c58b917814c5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     NMFILIAL                         NMLOJA     DTVENDA  \\\n",
      "0       QG - GOIANIA SHOPPING          QG - GOIANIA SHOPPING  26/10/2023   \n",
      "1       QG - GOIANIA SHOPPING          QG - GOIANIA SHOPPING  26/10/2023   \n",
      "2       QG - GOIANIA SHOPPING          QG - GOIANIA SHOPPING  26/10/2023   \n",
      "3       QG - GOIANIA SHOPPING          QG - GOIANIA SHOPPING  26/10/2023   \n",
      "4       QG - GOIANIA SHOPPING          QG - GOIANIA SHOPPING  26/10/2023   \n",
      "...                       ...                            ...         ...   \n",
      "13208  QG - PASSEIO DAS AGUAS  QG JEITINHO CASEIRO - GO PASH  26/10/2023   \n",
      "13209  QG - PASSEIO DAS AGUAS  QG JEITINHO CASEIRO - GO PASH  26/10/2023   \n",
      "13210  QG - PASSEIO DAS AGUAS  QG JEITINHO CASEIRO - GO PASH  26/10/2023   \n",
      "13211  QG - PASSEIO DAS AGUAS  QG JEITINHO CASEIRO - GO PASH  26/10/2023   \n",
      "13212  QG - PASSEIO DAS AGUAS  QG JEITINHO CASEIRO - GO PASH  26/10/2023   \n",
      "\n",
      "                          NMPRODUTO  VALORVENDA     CUPOM  \n",
      "0             SALADA VINAGRETE - UN        0.01  0.500000  \n",
      "1                 GALINHADA QG - UN       15.99  0.500000  \n",
      "2             SALADA VINAGRETE - UN        0.01  0.500000  \n",
      "3             ARROZ CARRETEIRO - UN       18.99  0.500000  \n",
      "4                   P DE CARNE - UN        7.00  0.500000  \n",
      "...                             ...         ...       ...  \n",
      "13208  3 MINI BRIGADEIRO COMBO - UN        6.00  0.153846  \n",
      "13209     3 MINI CHURROS COMBO - UN        3.00  0.076923  \n",
      "13210         COCA COLA 300 ML - UN       14.00  0.153846  \n",
      "13211             FANTA 300 ML - UN        7.00  0.076923  \n",
      "13212      6 PASTEIS + 3 REFRI - UN       28.94  0.076923  \n",
      "\n",
      "[13213 rows x 6 columns]\n"
     ]
    }
   ],
   "source": [
    "print(qg_novaTabela)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "id": "Y1FKcm4Qk1Wf"
   },
   "outputs": [],
   "source": [
    "# Suponha que 'df' seja o seu DataFrame\n",
    "qg_novaTabela.to_excel('nome_do_arquivo.xlsx', index=False, engine='openpyxl')\n",
    "# index=False para não incluir índices no arquivo\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "id": "4vx047qaX-kF"
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 675
    },
    "id": "NWUh2i4UryVz",
    "outputId": "bf1e1192-4b32-4695-da1f-39318db5306e"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# Suponha que 'qg' seja o seu DataFrame\n",
    "qg_novaTabela = qg[['NMFILIAL', 'VALORVENDA']]\n",
    "\n",
    "# Agrupe os dados por 'NMFILIAL' e calcule a soma dos 'VALORVENDA' para cada filial\n",
    "agrupado = qg_novaTabela.groupby('NMFILIAL')['VALORVENDA'].sum()\n",
    "\n",
    "# Crie o gráfico de barras\n",
    "agrupado.plot(kind='bar')\n",
    "plt.title('Total de Vendas por Filial')\n",
    "plt.xlabel('Filial')\n",
    "plt.ylabel('Total de Vendas')\n",
    "plt.show()\n",
    "\n",
    "#Salva o gráfico em um arquivo PNG (ou outro formato desejado)\n",
    "plt.savefig('meu_grafico.png')"
   ]
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "gpuType": "T4",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}