01-exploratory_data_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import warnings\n",
    "sns.set_style(\"darkgrid\")\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Análise do Dataset Simplified Coffee\n",
    "\n",
    "Este dataset contém informações sobre diferentes cafés e suas avaliações. A seguir, apresento a descrição das colunas e algumas hipóteses que podem ser levantadas para análise.\n",
    "\n",
    "## Descrição das Colunas\n",
    "\n",
    "1. **Name**: Nome do café.\n",
    "   - Tipo de dado: Categórico (Nominal)\n",
    "   - Descrição: O nome do café, que pode ser uma marca ou uma descrição do tipo de \n",
    "     produto.\n",
    "\n",
    "2. **Roaster**: Nome do torrefador.\n",
    "   - Tipo de dado: Categórico (Nominal)\n",
    "   - Descrição: Refere-se à empresa ou marca responsável pela torrefa\n",
    "     ção do café.\n",
    "\n",
    "3. **Roast**: Tipo de torra do café (Exemplo: Light, Medium, Dark).\n",
    "   - Tipo de dado: Categórico (Nominal)\n",
    "   - Descrição: Indica o grau de torra do café. Pode influenciar o sabor e a inte\n",
    "     nsidade do café.\n",
    "\n",
    "4. **Loc_Country**: País de localização do torrefador ou da empresa.\n",
    "   - Tipo de dado: Categórico (Nominal)\n",
    "   - Descrição: País onde\n",
    "      o café foi torrado.\n",
    "\n",
    "5. **Origin**: País ou região de origem dos grãos de café.\n",
    "   - Tipo de dado: Categórico (Nominal)\n",
    "   - Descrição: Indica o local de cultivo dos grãos de café, como Brasil,\n",
    "      Colômbia, Etiópia, etc.\n",
    "\n",
    "6. **100g_USD**: Preço do café por 100g em dólares americanos.\n",
    "   - Tipo de dado: Numérico (Contínuo)\n",
    "   - Descrição: O preço do café\n",
    "      por 100 gramas, em dólares.\n",
    "\n",
    "7. **Rating**: Classificação do café\n",
    "   - Tipo de dado: Numérico (Contínuo)\n",
    "   - Descrição: A nota média dada pelos consumidores ao café, ref\n",
    "     letindo sua qualidade percebida.\n",
    "\n",
    "8. **Review_Date**: Data da avaliação.\n",
    "   - Tipo de dado: Temporal (Data)\n",
    "   - Descrição: \n",
    "     A data em que a avaliação foi feita.\n",
    "\n",
    "9. **Review**: Texto da avaliação.\n",
    "   - Tipo de dado: Texto (String)\n",
    "   - Descrição: Comentários\n",
    "     offe` e sugerir abordagens para exploração e validação das hipóteses.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
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   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>roaster</th>\n",
       "      <th>roast</th>\n",
       "      <th>loc_country</th>\n",
       "      <th>origin</th>\n",
       "      <th>100g_USD</th>\n",
       "      <th>rating</th>\n",
       "      <th>mes</th>\n",
       "      <th>ano</th>\n",
       "      <th>preco_qualidade</th>\n",
       "      <th>idade_cafe</th>\n",
       "      <th>avaliacao_rating</th>\n",
       "      <th>classificacao_preco</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ethiopia Shakiso Mormora</td>\n",
       "      <td>Revel Coffee</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>United States</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>4.70</td>\n",
       "      <td>92</td>\n",
       "      <td>November</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.051087</td>\n",
       "      <td>7</td>\n",
       "      <td>High</td>\n",
       "      <td>barato</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ethiopia Suke Quto</td>\n",
       "      <td>Roast House</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>United States</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>4.19</td>\n",
       "      <td>92</td>\n",
       "      <td>November</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.045543</td>\n",
       "      <td>7</td>\n",
       "      <td>High</td>\n",
       "      <td>barato</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ethiopia Gedeb Halo Beriti</td>\n",
       "      <td>Big Creek Coffee Roasters</td>\n",
       "      <td>Medium</td>\n",
       "      <td>United States</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>4.85</td>\n",
       "      <td>94</td>\n",
       "      <td>November</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.051596</td>\n",
       "      <td>7</td>\n",
       "      <td>High</td>\n",
       "      <td>barato</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ethiopia Kayon Mountain</td>\n",
       "      <td>Red Rooster Coffee Roaster</td>\n",
       "      <td>Light</td>\n",
       "      <td>United States</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>5.14</td>\n",
       "      <td>93</td>\n",
       "      <td>November</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.055269</td>\n",
       "      <td>7</td>\n",
       "      <td>High</td>\n",
       "      <td>barato</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ethiopia Gelgelu Natural Organic</td>\n",
       "      <td>Willoughby's Coffee &amp; Tea</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>United States</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>3.97</td>\n",
       "      <td>93</td>\n",
       "      <td>November</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.042688</td>\n",
       "      <td>7</td>\n",
       "      <td>High</td>\n",
       "      <td>barato</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               name                     roaster         roast  \\\n",
       "0          Ethiopia Shakiso Mormora                Revel Coffee  Medium-Light   \n",
       "1                Ethiopia Suke Quto                 Roast House  Medium-Light   \n",
       "2        Ethiopia Gedeb Halo Beriti   Big Creek Coffee Roasters        Medium   \n",
       "3           Ethiopia Kayon Mountain  Red Rooster Coffee Roaster         Light   \n",
       "4  Ethiopia Gelgelu Natural Organic   Willoughby's Coffee & Tea  Medium-Light   \n",
       "\n",
       "     loc_country    origin  100g_USD  rating       mes   ano  preco_qualidade  \\\n",
       "0  United States  Ethiopia      4.70      92  November  2017         0.051087   \n",
       "1  United States  Ethiopia      4.19      92  November  2017         0.045543   \n",
       "2  United States  Ethiopia      4.85      94  November  2017         0.051596   \n",
       "3  United States  Ethiopia      5.14      93  November  2017         0.055269   \n",
       "4  United States  Ethiopia      3.97      93  November  2017         0.042688   \n",
       "\n",
       "   idade_cafe avaliacao_rating classificacao_preco  \n",
       "0           7             High              barato  \n",
       "1           7             High              barato  \n",
       "2           7             High              barato  \n",
       "3           7             High              barato  \n",
       "4           7             High              barato  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# importando os dados\n",
    "data = pd.read_csv('../data/raw/simplified_coffee.csv')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "132.28"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['100g_USD'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>roaster</th>\n",
       "      <th>roast</th>\n",
       "      <th>loc_country</th>\n",
       "      <th>origin</th>\n",
       "      <th>100g_USD</th>\n",
       "      <th>rating</th>\n",
       "      <th>mes</th>\n",
       "      <th>ano</th>\n",
       "      <th>preco_qualidade</th>\n",
       "      <th>idade_cafe</th>\n",
       "      <th>avaliacao_rating</th>\n",
       "      <th>classificacao_preco</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>943</th>\n",
       "      <td>Mama Cata Mokkita</td>\n",
       "      <td>Paradise Roasters</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>United States</td>\n",
       "      <td>Panama</td>\n",
       "      <td>132.28</td>\n",
       "      <td>97</td>\n",
       "      <td>November</td>\n",
       "      <td>2021</td>\n",
       "      <td>1.363711</td>\n",
       "      <td>3</td>\n",
       "      <td>Excellent</td>\n",
       "      <td>caro</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  name            roaster         roast    loc_country  \\\n",
       "943  Mama Cata Mokkita  Paradise Roasters  Medium-Light  United States   \n",
       "\n",
       "     origin  100g_USD  rating       mes   ano  preco_qualidade  idade_cafe  \\\n",
       "943  Panama    132.28      97  November  2021         1.363711           3   \n",
       "\n",
       "    avaliacao_rating classificacao_preco  \n",
       "943        Excellent                caro  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['100g_USD'] == 132.28]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Descrição dos dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>100g_USD</th>\n",
       "      <th>rating</th>\n",
       "      <th>ano</th>\n",
       "      <th>preco_qualidade</th>\n",
       "      <th>idade_cafe</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1246.000000</td>\n",
       "      <td>1246.000000</td>\n",
       "      <td>1246.000000</td>\n",
       "      <td>1246.000000</td>\n",
       "      <td>1246.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>10.479125</td>\n",
       "      <td>93.306581</td>\n",
       "      <td>2020.167737</td>\n",
       "      <td>0.111786</td>\n",
       "      <td>3.832263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>13.486674</td>\n",
       "      <td>1.479413</td>\n",
       "      <td>1.444542</td>\n",
       "      <td>0.142413</td>\n",
       "      <td>1.444542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.170000</td>\n",
       "      <td>84.000000</td>\n",
       "      <td>2017.000000</td>\n",
       "      <td>0.001809</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5.260000</td>\n",
       "      <td>93.000000</td>\n",
       "      <td>2019.000000</td>\n",
       "      <td>0.055895</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>6.170000</td>\n",
       "      <td>93.000000</td>\n",
       "      <td>2020.000000</td>\n",
       "      <td>0.065638</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>9.600000</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>2021.000000</td>\n",
       "      <td>0.103226</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>132.280000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>2022.000000</td>\n",
       "      <td>1.363711</td>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          100g_USD       rating          ano  preco_qualidade   idade_cafe\n",
       "count  1246.000000  1246.000000  1246.000000      1246.000000  1246.000000\n",
       "mean     10.479125    93.306581  2020.167737         0.111786     3.832263\n",
       "std      13.486674     1.479413     1.444542         0.142413     1.444542\n",
       "min       0.170000    84.000000  2017.000000         0.001809     2.000000\n",
       "25%       5.260000    93.000000  2019.000000         0.055895     3.000000\n",
       "50%       6.170000    93.000000  2020.000000         0.065638     4.000000\n",
       "75%       9.600000    94.000000  2021.000000         0.103226     5.000000\n",
       "max     132.280000    97.000000  2022.000000         1.363711     7.000000"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1246, 13)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1246 entries, 0 to 1245\n",
      "Data columns (total 13 columns):\n",
      " #   Column               Non-Null Count  Dtype  \n",
      "---  ------               --------------  -----  \n",
      " 0   name                 1246 non-null   object \n",
      " 1   roaster              1246 non-null   object \n",
      " 2   roast                1234 non-null   object \n",
      " 3   loc_country          1246 non-null   object \n",
      " 4   origin               1246 non-null   object \n",
      " 5   100g_USD             1246 non-null   float64\n",
      " 6   rating               1246 non-null   int64  \n",
      " 7   mes                  1246 non-null   object \n",
      " 8   ano                  1246 non-null   int64  \n",
      " 9   preco_qualidade      1246 non-null   float64\n",
      " 10  idade_cafe           1246 non-null   int64  \n",
      " 11  avaliacao_rating     1246 non-null   object \n",
      " 12  classificacao_preco  1246 non-null   object \n",
      "dtypes: float64(2), int64(3), object(8)\n",
      "memory usage: 126.7+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "name                    0\n",
       "roaster                 0\n",
       "roast                  12\n",
       "loc_country             0\n",
       "origin                  0\n",
       "100g_USD                0\n",
       "rating                  0\n",
       "mes                     0\n",
       "ano                     0\n",
       "preco_qualidade         0\n",
       "idade_cafe              0\n",
       "avaliacao_rating        0\n",
       "classificacao_preco     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Preço médio dos grãos de café: USD 10.48\n",
      "75% dos cafés têm preço até: USD 9.60\n",
      "Maior valor de café: USD 132.28 (possível outlier)\n",
      "Amplitude das notas de avaliação: 13\n",
      "Distância interquartil (IQR) das notas: 1.00\n"
     ]
    }
   ],
   "source": [
    "\n",
    "preco_medio = data['100g_USD'].mean()\n",
    "\n",
    "# Calcular os percentis (25%, 50%, 75%)\n",
    "percentil_25 = data['100g_USD'].quantile(0.25)\n",
    "percentil_50 = data['100g_USD'].median()\n",
    "percentil_75 = data['100g_USD'].quantile(0.75)\n",
    "\n",
    "# Identificar o maior valor de preço\n",
    "preco_maximo = data['100g_USD'].max()\n",
    "\n",
    "amplitude_rating = data['rating'].max() - data['rating'].min()\n",
    "iqr_rating = data['rating'].quantile(0.75) - data['rating'].quantile(0.25)\n",
    "\n",
    "print(f\"Preço médio dos grãos de café: USD {preco_medio:.2f}\")\n",
    "print(f\"75% dos cafés têm preço até: USD {percentil_75:.2f}\")\n",
    "print(f\"Maior valor de café: USD {preco_maximo:.2f} (possível outlier)\")\n",
    "print(f\"Amplitude das notas de avaliação: {amplitude_rating}\")\n",
    "print(f\"Distância interquartil (IQR) das notas: {iqr_rating:.2f}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Quantidade de outliers removidos por coluna:\n"
     ]
    }
   ],
   "source": [
    "\n",
    "def detect_outliers_iqr(data, column):\n",
    "    Q1 = data[column].quantile(0.25)\n",
    "    Q3 = data[column].quantile(0.75)\n",
    "    IQR = Q3 - Q1\n",
    "    lower_bound = Q1 - 1.5 * IQR\n",
    "    upper_bound = Q3 + 1.5 * IQR\n",
    "    return data[(data[column] < lower_bound) | (data[column] > upper_bound)]\n",
    "\n",
    "# Detectar e remover outliers em variáveis numéricas\n",
    "outliers_dict = {}\n",
    "for col in data.select_dtypes(include=[np.number]).columns:\n",
    "    outliers = detect_outliers_iqr(data, col)\n",
    "    if not outliers.empty:\n",
    "        outliers_dict[col] = len(outliers)\n",
    "        data = data[~data.index.isin(outliers.index)]\n",
    "\n",
    "print(\"\\nQuantidade de outliers removidos por coluna:\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Das duas células acima, podemos ver que o dataset possui 1246 linhas (instâncias) e 9 colunas (features). Podemos ver também que esse dataset tem dados faltantes para o atributo \"roast\" (torra) e no atributo \"desc_3\".\n",
    "\n",
    "O atributo torra possui 12 valores faltantes,  \n",
    "\n",
    "\n",
    "Conseguimos ver o preço médio dos grãos de café (USD 10,48) e que 75% dos dados possuem valor até USD 9,60 mas o café de maior valor custa USD 132,28, o que pode ser um outlier.    \n",
    "Em relação às notas das avaliações temos uma amplitude de 13 pontos e a distância inter-quartil (IQR) é de apenas 1 ponto, o que pode mostrar que os cafés tem notas altas que variam pouco, por ter alta qualidade."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5727923627684964"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculando a porcentagem de dados faltantos\n",
    "dados_faltantes_roast = data['roast'].isnull().sum()\n",
    "porcentagem_dados_faltantes = (dados_faltantes_roast / 2095) * 100\n",
    "porcentagem_dados_faltantes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ou seja, temos 0.5% de dados faltantes nessa coluna. Por ser um valor baixo, podemos retirar essas linhas."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Vamos avaliar quais tipos de torra e quais países são produtos do grão."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Medium-Light', 'Medium', 'Light', 'Medium-Dark', nan, 'Dark'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "torras = data['roast'].unique()\n",
    "torras"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "27"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "paises = data['origin'].unique()\n",
    "len(paises)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Features Enginner\n",
    "\n",
    "* Vamos criar novas variáveis a partir da que temos no nosso dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# preço por unidade de qualidade\n",
    "\n",
    "data['preco_qualidade'] = data['100g_USD']/data['rating']\n",
    "\n",
    "# idade do café, considerando o ano que estamos\n",
    "\n",
    "ano = 2024\n",
    "data['idade_cafe'] = ano - data['ano']\n",
    "\n",
    "# intervalo de avaliação\n",
    "\n",
    "bins = [0 , 85, 90, 95, 100]\n",
    "labels = ['Low', 'Medium', 'High', 'Excellent']\n",
    "data['avaliacao_rating'] = pd.cut(data['rating'], bins = bins , labels = labels)\n",
    "\n",
    "\n",
    "#Classificação de preço\n",
    "data['classificacao_preco'] = pd.qcut(data['100g_USD'], q =3, labels = ['barato', 'intermediario', 'caro'] )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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>name</th>\n",
       "      <th>roaster</th>\n",
       "      <th>roast</th>\n",
       "      <th>loc_country</th>\n",
       "      <th>origin</th>\n",
       "      <th>100g_USD</th>\n",
       "      <th>rating</th>\n",
       "      <th>mes</th>\n",
       "      <th>ano</th>\n",
       "      <th>preco_qualidade</th>\n",
       "      <th>idade_cafe</th>\n",
       "      <th>avaliacao_rating</th>\n",
       "      <th>classificacao_preco</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ethiopia Shakiso Mormora</td>\n",
       "      <td>Revel Coffee</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>United States</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>4.70</td>\n",
       "      <td>92</td>\n",
       "      <td>November</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.051087</td>\n",
       "      <td>7</td>\n",
       "      <td>High</td>\n",
       "      <td>barato</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ethiopia Suke Quto</td>\n",
       "      <td>Roast House</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>United States</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>4.19</td>\n",
       "      <td>92</td>\n",
       "      <td>November</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.045543</td>\n",
       "      <td>7</td>\n",
       "      <td>High</td>\n",
       "      <td>barato</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ethiopia Gedeb Halo Beriti</td>\n",
       "      <td>Big Creek Coffee Roasters</td>\n",
       "      <td>Medium</td>\n",
       "      <td>United States</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>4.85</td>\n",
       "      <td>94</td>\n",
       "      <td>November</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.051596</td>\n",
       "      <td>7</td>\n",
       "      <td>High</td>\n",
       "      <td>barato</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ethiopia Kayon Mountain</td>\n",
       "      <td>Red Rooster Coffee Roaster</td>\n",
       "      <td>Light</td>\n",
       "      <td>United States</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>5.14</td>\n",
       "      <td>93</td>\n",
       "      <td>November</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.055269</td>\n",
       "      <td>7</td>\n",
       "      <td>High</td>\n",
       "      <td>barato</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ethiopia Gelgelu Natural Organic</td>\n",
       "      <td>Willoughby's Coffee &amp; Tea</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>United States</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>3.97</td>\n",
       "      <td>93</td>\n",
       "      <td>November</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.042688</td>\n",
       "      <td>7</td>\n",
       "      <td>High</td>\n",
       "      <td>barato</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1241</th>\n",
       "      <td>Finca Patzibir</td>\n",
       "      <td>El Gran Cafe</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>4.70</td>\n",
       "      <td>92</td>\n",
       "      <td>November</td>\n",
       "      <td>2022</td>\n",
       "      <td>0.051087</td>\n",
       "      <td>2</td>\n",
       "      <td>High</td>\n",
       "      <td>barato</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1242</th>\n",
       "      <td>Proyecto Aurora</td>\n",
       "      <td>El Gran Cafe</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>2.94</td>\n",
       "      <td>93</td>\n",
       "      <td>November</td>\n",
       "      <td>2022</td>\n",
       "      <td>0.031613</td>\n",
       "      <td>2</td>\n",
       "      <td>High</td>\n",
       "      <td>barato</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1243</th>\n",
       "      <td>Finca El Potrero</td>\n",
       "      <td>El Gran Cafe</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>2.94</td>\n",
       "      <td>93</td>\n",
       "      <td>November</td>\n",
       "      <td>2022</td>\n",
       "      <td>0.031613</td>\n",
       "      <td>2</td>\n",
       "      <td>High</td>\n",
       "      <td>barato</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1244</th>\n",
       "      <td>Chacayá Santiago Atitlán</td>\n",
       "      <td>El Gran Cafe</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>4.70</td>\n",
       "      <td>93</td>\n",
       "      <td>November</td>\n",
       "      <td>2022</td>\n",
       "      <td>0.050538</td>\n",
       "      <td>2</td>\n",
       "      <td>High</td>\n",
       "      <td>barato</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1245</th>\n",
       "      <td>Espresso No. 3</td>\n",
       "      <td>El Gran Cafe</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>5.88</td>\n",
       "      <td>94</td>\n",
       "      <td>November</td>\n",
       "      <td>2022</td>\n",
       "      <td>0.062553</td>\n",
       "      <td>2</td>\n",
       "      <td>High</td>\n",
       "      <td>intermediario</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1246 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  name                     roaster  \\\n",
       "0             Ethiopia Shakiso Mormora                Revel Coffee   \n",
       "1                   Ethiopia Suke Quto                 Roast House   \n",
       "2           Ethiopia Gedeb Halo Beriti   Big Creek Coffee Roasters   \n",
       "3              Ethiopia Kayon Mountain  Red Rooster Coffee Roaster   \n",
       "4     Ethiopia Gelgelu Natural Organic   Willoughby's Coffee & Tea   \n",
       "...                                ...                         ...   \n",
       "1241                    Finca Patzibir                El Gran Cafe   \n",
       "1242                   Proyecto Aurora                El Gran Cafe   \n",
       "1243                  Finca El Potrero                El Gran Cafe   \n",
       "1244          Chacayá Santiago Atitlán                El Gran Cafe   \n",
       "1245                    Espresso No. 3                El Gran Cafe   \n",
       "\n",
       "             roast    loc_country     origin  100g_USD  rating       mes  \\\n",
       "0     Medium-Light  United States   Ethiopia      4.70      92  November   \n",
       "1     Medium-Light  United States   Ethiopia      4.19      92  November   \n",
       "2           Medium  United States   Ethiopia      4.85      94  November   \n",
       "3            Light  United States   Ethiopia      5.14      93  November   \n",
       "4     Medium-Light  United States   Ethiopia      3.97      93  November   \n",
       "...            ...            ...        ...       ...     ...       ...   \n",
       "1241  Medium-Light      Guatemala  Guatemala      4.70      92  November   \n",
       "1242  Medium-Light      Guatemala  Guatemala      2.94      93  November   \n",
       "1243  Medium-Light      Guatemala  Guatemala      2.94      93  November   \n",
       "1244  Medium-Light      Guatemala  Guatemala      4.70      93  November   \n",
       "1245  Medium-Light      Guatemala  Guatemala      5.88      94  November   \n",
       "\n",
       "       ano  preco_qualidade  idade_cafe avaliacao_rating classificacao_preco  \n",
       "0     2017         0.051087           7             High              barato  \n",
       "1     2017         0.045543           7             High              barato  \n",
       "2     2017         0.051596           7             High              barato  \n",
       "3     2017         0.055269           7             High              barato  \n",
       "4     2017         0.042688           7             High              barato  \n",
       "...    ...              ...         ...              ...                 ...  \n",
       "1241  2022         0.051087           2             High              barato  \n",
       "1242  2022         0.031613           2             High              barato  \n",
       "1243  2022         0.031613           2             High              barato  \n",
       "1244  2022         0.050538           2             High              barato  \n",
       "1245  2022         0.062553           2             High       intermediario  \n",
       "\n",
       "[1246 rows x 13 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hipóteses e Perguntas Levantadas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cafés mais Caros podem ser Avaliados de Forma mais Positiva?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pela análise gráfica, sugere que o preço do café está fortemente ligado à sua qualidade percebida, ou seja, em geral a qualidade do café, medida pela nota, está positivamente relacionada ao seu preço. Consumidores que buscam cafés de alta qualidade estão dispostos a pagar mais por eles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.scatterplot(data=data, x='rating', y='100g_USD')\n",
    "plt.title(\"Gráfico de dispersão - Preço x Nota do café\")\n",
    "ax.set_xlabel('Nota')\n",
    "ax.set_ylabel('Preço café')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Influência do Local de Venda no Preço do Café"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Esse gráfico já pode sugerir que o preço pode estar relacionado com o local da venda, uma vez que os grãos mais caros estão em países mais desenvolvidos e não produtores de café (Taiwan, Estados Unidos, Inglaterra)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.scatterplot(data=data, y='loc_country', x='100g_USD')\n",
    "plt.title(\"Gráfico de Dispersão - Local de Venda x Preço do Café (USD) \")\n",
    "ax.set_xlabel('')\n",
    "ax.set_ylabel('')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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>name</th>\n",
       "      <th>roaster</th>\n",
       "      <th>roast</th>\n",
       "      <th>loc_country</th>\n",
       "      <th>origin</th>\n",
       "      <th>100g_USD</th>\n",
       "      <th>rating</th>\n",
       "      <th>mes</th>\n",
       "      <th>ano</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ethiopia Shakiso Mormora</td>\n",
       "      <td>Revel Coffee</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>United States</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>4.70</td>\n",
       "      <td>92</td>\n",
       "      <td>November</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ethiopia Suke Quto</td>\n",
       "      <td>Roast House</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>United States</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>4.19</td>\n",
       "      <td>92</td>\n",
       "      <td>November</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ethiopia Gedeb Halo Beriti</td>\n",
       "      <td>Big Creek Coffee Roasters</td>\n",
       "      <td>Medium</td>\n",
       "      <td>United States</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>4.85</td>\n",
       "      <td>94</td>\n",
       "      <td>November</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ethiopia Kayon Mountain</td>\n",
       "      <td>Red Rooster Coffee Roaster</td>\n",
       "      <td>Light</td>\n",
       "      <td>United States</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>5.14</td>\n",
       "      <td>93</td>\n",
       "      <td>November</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ethiopia Gelgelu Natural Organic</td>\n",
       "      <td>Willoughby's Coffee &amp; Tea</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>United States</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>3.97</td>\n",
       "      <td>93</td>\n",
       "      <td>November</td>\n",
       "      <td>2017</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1241</th>\n",
       "      <td>Finca Patzibir</td>\n",
       "      <td>El Gran Cafe</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>4.70</td>\n",
       "      <td>92</td>\n",
       "      <td>November</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1242</th>\n",
       "      <td>Proyecto Aurora</td>\n",
       "      <td>El Gran Cafe</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>2.94</td>\n",
       "      <td>93</td>\n",
       "      <td>November</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1243</th>\n",
       "      <td>Finca El Potrero</td>\n",
       "      <td>El Gran Cafe</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>2.94</td>\n",
       "      <td>93</td>\n",
       "      <td>November</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1244</th>\n",
       "      <td>Chacayá Santiago Atitlán</td>\n",
       "      <td>El Gran Cafe</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>4.70</td>\n",
       "      <td>93</td>\n",
       "      <td>November</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1245</th>\n",
       "      <td>Espresso No. 3</td>\n",
       "      <td>El Gran Cafe</td>\n",
       "      <td>Medium-Light</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>5.88</td>\n",
       "      <td>94</td>\n",
       "      <td>November</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1246 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  name                     roaster  \\\n",
       "0             Ethiopia Shakiso Mormora                Revel Coffee   \n",
       "1                   Ethiopia Suke Quto                 Roast House   \n",
       "2           Ethiopia Gedeb Halo Beriti   Big Creek Coffee Roasters   \n",
       "3              Ethiopia Kayon Mountain  Red Rooster Coffee Roaster   \n",
       "4     Ethiopia Gelgelu Natural Organic   Willoughby's Coffee & Tea   \n",
       "...                                ...                         ...   \n",
       "1241                    Finca Patzibir                El Gran Cafe   \n",
       "1242                   Proyecto Aurora                El Gran Cafe   \n",
       "1243                  Finca El Potrero                El Gran Cafe   \n",
       "1244          Chacayá Santiago Atitlán                El Gran Cafe   \n",
       "1245                    Espresso No. 3                El Gran Cafe   \n",
       "\n",
       "             roast    loc_country     origin  100g_USD  rating       mes   ano  \n",
       "0     Medium-Light  United States   Ethiopia      4.70      92  November  2017  \n",
       "1     Medium-Light  United States   Ethiopia      4.19      92  November  2017  \n",
       "2           Medium  United States   Ethiopia      4.85      94  November  2017  \n",
       "3            Light  United States   Ethiopia      5.14      93  November  2017  \n",
       "4     Medium-Light  United States   Ethiopia      3.97      93  November  2017  \n",
       "...            ...            ...        ...       ...     ...       ...   ...  \n",
       "1241  Medium-Light      Guatemala  Guatemala      4.70      92  November  2022  \n",
       "1242  Medium-Light      Guatemala  Guatemala      2.94      93  November  2022  \n",
       "1243  Medium-Light      Guatemala  Guatemala      2.94      93  November  2022  \n",
       "1244  Medium-Light      Guatemala  Guatemala      4.70      93  November  2022  \n",
       "1245  Medium-Light      Guatemala  Guatemala      5.88      94  November  2022  \n",
       "\n",
       "[1246 rows x 9 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "O gráfico a seguir, sugere que o valor \"100g_USD\" apresentou uma tendência de alta nos primeiros anos do período analiado, possivelmente devido a fatores como inflação, aumento da demanda ou outras variáveis que influenciam esse valor. No entanto, a partir de 2021, houve uma reversão dessa tendência, com uma queda acentuada no valor médio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# calcular a média de '100g_USD' por ano\n",
    "media_por_ano = data.groupby('ano')['100g_USD'].mean()\n",
    "plt.plot(media_por_ano.index, media_por_ano.values)\n",
    "plt.title('Tendência de Evolução do Valor do Café')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ambos os gráficos apresentam um ponto de inflexão em 2019, onde a taxa de crescimento da nota do café aumenta significativamente. Isso pode indicar a implementação de novas práticas agrícolas, investimentos em tecnologia ou outros fatores que contribuíram para a melhoria da qualidade do café a partir desse ano.\n",
    "\n",
    "É evidente que o valor médio das notas tem apresentado um crescimento contínuo desde 2020. Esse aumento pode ser atribuído, em parte, à queda nos preços do café, o que tem tornado o produto mais acessível. Com preços mais baixos, os consumidores têm a oportunidade de adquirir cafés de melhor qualidade, o que, por sua vez, eleva o valor das notas. Essa dinâmica reflete uma relação positiva entre a acessibilidade ao café de qualidade e a valorização das notas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "media_por_ano = data.groupby('ano')['rating'].mean()\n",
    "plt.plot(media_por_ano.index, media_por_ano.values)\n",
    "plt.title('Taxa Média de Mudança da Nota ao Longo do tempo')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " Agora, vamos ver quantos países produtores distintos a base possui e em quantos países esses vendedores estão localizados. Depois vamos repetir as análises para os cafés mais caros."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Existem 27 países produtores\n",
      "Existem 12 países que vendem esses cafés\n",
      "\n",
      "Países produtores: ['Ethiopia' \"Hawai'I\" 'Kenya' 'Guatemala' 'Colombia' 'Panama' 'Nicaragua'\n",
      " 'Indonesia' 'Peru' 'Rwanda' 'Nepal' 'Costa Rica' 'Ecuador' 'Brazil'\n",
      " 'Democratic Republic Of The Congo' 'Burundi' 'El Salvador' 'Yemen'\n",
      " 'Bolivia' 'Taiwan' 'Mexico' 'Dominican Republic' 'Honduras' 'Thailand'\n",
      " 'Uganda' 'Tanzania' 'Philippines']\n",
      "\n",
      "Países vendedores: ['United States' 'Canada' 'Hong Kong' \"Hawai'i\" 'Taiwan' 'England'\n",
      " 'Australia' 'Guatemala' 'Japan' 'China' 'Kenya' 'New Taiwan']\n"
     ]
    }
   ],
   "source": [
    "paises_produtores = data['origin'].nunique()\n",
    "paises_vendedores = data['loc_country'].nunique()\n",
    "\n",
    "print(f\"Existem {paises_produtores} países produtores\")\n",
    "print(f\"Existem {paises_vendedores} países que vendem esses cafés\")\n",
    "\n",
    "# Listar os países produtores e vendedores de café\n",
    "print(\"\\nPaíses produtores:\", data['origin'].unique())\n",
    "print(\"\\nPaíses vendedores:\", data['loc_country'].unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "O gráfico apresenta os cinco principais países produtores de café, classificados pela nota média de seus grãos. A Tanzânia lidera o ranking, seguida de perto pelo Panamá e Equador. Quênia e Iêmen completam a lista dos cinco primeiros. A alta classificação desses países indica uma qualidade excepcional em seus cafés, resultado de fatores como clima, variedade de grãos e processos de produção"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "media_notas = data.groupby('origin')['rating'].mean()\n",
    "top_5_paises = media_notas.nlargest(5)\n",
    "\n",
    "plt.figure(figsize = (10, 6))\n",
    "\n",
    "ax = sns.barplot(x = top_5_paises.index, y = top_5_paises.values, palette = \"coolwarm\")\n",
    "\n",
    "# Adicionando os valores das médias nas barras\n",
    "for i, valor in enumerate(top_5_paises.values):\n",
    "    ax.text(i, valor + 1, f\"{valor:.1f}\", ha = \"center\", va= \"bottom\", fontsize = 10, color = \"black\")\n",
    "\n",
    "plt.title(\"Top 5 Países Produtores de Café por Nota Média\", fontsize = 14)\n",
    "ax.set_xlabel('')\n",
    "ax.set_ylabel('')\n",
    "plt.xticks(rotation = 360)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### O preço de cafés de torrefação mais escura (Dark) é mais alto em relação aos cafés de torrefação mais clara(Ligth e Medium)\n",
    "\n",
    "o gráfico nos oferece uma visão inicial da complexa relação entre preço, nota e tipo de torra do café. Ao compreender essa relação, podemos tomar decisões mais informadas na hora de escolher e consumir café, além de contribuir para o desenvolvimento de um mercado de café mais transparente e justo."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(14, 5))\n",
    "\n",
    "sns.scatterplot(data=data, x='rating', y='100g_USD', hue='roast', style='roast', ax=ax1)\n",
    "ax1.set_xlabel('Rating')\n",
    "ax1.set_ylabel('100g USD')\n",
    "ax1.set_title('', fontsize=12)\n",
    "\n",
    "\n",
    "sns.boxplot(data=data, x='rating', y='100g_USD', ax=ax2)\n",
    "ax2.set_xlabel('Rating')\n",
    "ax2.set_ylabel('100g USD')\n",
    "ax2.set_title('', fontsize=12)\n",
    "\n",
    "# Título para o dashboard\n",
    "fig.suptitle(\"Relação entre Preço, Nota e Tipo de Torra de Café\", fontsize=16)\n",
    "plt.tight_layout(rect=[0, 0, 1, 0.95])\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pode-se perceber que, existem apenas 3 registros com o tipo de torrefação mais escura, o que nos indica que esse tipo de pedido não é tão frequentem o que  implica na sua existencia na sociedade, ou seja,  nao é uma opção muito comum entre as demandas das empresas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.to_csv(\"../data/raw/simplified_coffee.csv\", index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Insights"
   ]
  },
  {
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    "### 1. Associação entre Preços Mais Altos e Avaliações Mais Positivas\n",
    "\n",
    "Existe uma possibilidade de que cafés com preços mais elevados recebam avaliações mais positivas. Isso pode indicar que consumidores associam preços mais altos à maior qualidade do produto. Essa percepção pode ser influenciada por fatores como:\n",
    "\n",
    "     Qualidade dos Grãos: Cafés mais caros frequentemente utilizam grãos de origem única ou de cultivos sustentáveis, que tendem a oferecer sabores mais complexos e aromáticos.\n",
    "\n",
    "     Processo de Torrefação: Métodos de torrefação mais artesanais e cuidadosos podem resultar em um produto final superior, justificando preços mais elevados.\n",
    "\n",
    "     Experiência do Consumidor: Consumidores dispostos a pagar mais podem esperar uma experiência de consumo diferenciada, influenciando suas avaliações positivas.\n",
    "\n",
    "\n",
    "### 2. Impacto do Local de Venda ou Torrefação no Preço\n",
    "\n",
    "O local onde o café é vendido ou torrado pode ter um impacto significativo no preço final do produto. Isso reflete:\n",
    "\n",
    "     Custos Operacionais: Regiões diferentes possuem custos variáveis de operação, como aluguel, mão de obra e transporte, que podem influenciar o preço do café.\n",
    "\n",
    "     Preferências Regionais: As preferências de sabor e qualidade podem variar de uma região para outra, afetando a demanda e, consequentemente, os preços.\n",
    "\n",
    "     Logística e Distribuição: A proximidade com centros de produção ou consumo pode reduzir custos de logística, permitindo preços mais competitivos.\n",
    "\n",
    "\n",
    "### 3. Melhoria da Qualidade dos Cafés ao Longo dos Anos\n",
    "\n",
    "A análise sugere que a qualidade dos cafés tem melhorado ao longo do tempo, possivelmente devido a:\n",
    "\n",
    "     Aprimoramento das Práticas de Cultivo: Técnicas agrícolas mais avançadas e sustentáveis contribuem para a produção de grãos de melhor qualidade.\n",
    "\n",
    "     Inovação na Torrefação: Investimentos em tecnologia e processos de torrefação mais precisos resultam em perfis de sabor mais refinados.\n",
    "\n",
    "     Educação e Treinamento: Aumento do conhecimento dos produtores e torrefadores sobre as melhores práticas, promovendo uma maior consistência e excelência no produto final.\n",
    "\n",
    "### 4. Impacto da Torra Escura no Preço\n",
    "\n",
    "Embora a análise atual apresente limitações devido ao tamanho reduzido da amostra para torras escuras, observa-se que:\n",
    "\n",
    "     Dominância das Torras Média e Clara: Essas torras são mais populares no mercado, o que permite uma análise mais robusta e insights mais consistentes sobre suas influências no preço e nas avaliações.\n",
    "\n",
    "     Desafios para Torras Escuras: A menor quantidade de dados pode dificultar a identificação de padrões claros, mas a inclusão de mais amostras no futuro poderá fornecer uma visão mais abrangente.\n",
    "\n",
    "\n",
    "\n",
    "\n"
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