{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "9f6d9ac9-9e61-4545-b959-37bc91f4d18f",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Análise Exploratória de Dados com o Dataset do TMDB 5000"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "469046ff-eea3-4032-b21f-a62220b0f2b2",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Importação de Bibliotecas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ad99f271-c469-4555-8056-0e27bde902fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importa o numpy com o apelido np\n",
    "import numpy as np\n",
    "\n",
    "# Importa o pandas com o apelido pd\n",
    "import pandas as pd\n",
    "\n",
    "# Importa o pyplot com o apelido plt\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Importa o seaborn com o apelido sns\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c136201b-afbe-4621-814a-fa6477dfcce6",
   "metadata": {},
   "source": [
    "## Leitura do Conjunto de Dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cbf5bbe3-fa2a-4cdb-9075-aef8abec961a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importa o arquivo ratings.csv\n",
    "notas = pd.read_csv('ratings.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a1e024ef-a4b6-45cc-be74-b85da621e70c",
   "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>userId</th>\n",
       "      <th>movieId</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>964982703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>964981247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>964982224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>47</td>\n",
       "      <td>5.0</td>\n",
       "      <td>964983815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>5.0</td>\n",
       "      <td>964982931</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   userId  movieId  rating  timestamp\n",
       "0       1        1     4.0  964982703\n",
       "1       1        3     4.0  964981247\n",
       "2       1        6     4.0  964982224\n",
       "3       1       47     5.0  964983815\n",
       "4       1       50     5.0  964982931"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exibe as cinco primeiras linhas do dataframe\n",
    "notas.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1ba23c35-4cbf-4677-8aa8-e79ad94f0119",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove a coluna especificada\n",
    "notas.drop('timestamp', axis='columns', inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6d1c7d2-dd42-4304-81e8-ecbb6f35112d",
   "metadata": {},
   "source": [
    "## Verificação do Tamanho do Conjunto de Dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "15e065b2-9c4f-4102-988c-f30fde90e102",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100836, 3)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exibe as dimensões do dataframe\n",
    "notas.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "eceebee1-45e2-4508-9062-0ec4fb4b0def",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Desempacota a tupla\n",
    "num_linhas, num_colunas = notas.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "44693cda-43f5-4bca-94ea-356cc6fcee05",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Há 100836 linhas distribuídas ao longo de 3 colunas.\n"
     ]
    }
   ],
   "source": [
    "print(f'Há {num_linhas} linhas distribuídas ao longo de {num_colunas} colunas.')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c1f2aec-bc04-4e22-a1fd-51997c58a49e",
   "metadata": {},
   "source": [
    "## Renomeando as Colunas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "cc36810c-77e4-4a71-b73d-eced5c9d8aa5",
   "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>usuarioId</th>\n",
       "      <th>filmeId</th>\n",
       "      <th>nota</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>47</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   usuarioId  filmeId  nota\n",
       "0          1        1   4.0\n",
       "1          1        3   4.0\n",
       "2          1        6   4.0\n",
       "3          1       47   5.0\n",
       "4          1       50   5.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Renomeia as colunas do dataframe\n",
    "notas.columns = ['usuarioId', 'filmeId', 'nota']\n",
    "\n",
    "# Exibe as cinco primeiras linhas\n",
    "notas.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a514b5d6-25e4-46e4-b4f7-a494dbc3aa4c",
   "metadata": {},
   "source": [
    "## Análise das Notas"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f64f6e7b-83fe-4aaf-95a6-0f06bed81246",
   "metadata": {},
   "source": [
    "### Distribuição de Frequência das Notas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "036b70b8-7aa1-4668-9115-8233300be42f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         4.0\n",
       "1         4.0\n",
       "2         4.0\n",
       "3         5.0\n",
       "4         5.0\n",
       "         ... \n",
       "100831    4.0\n",
       "100832    5.0\n",
       "100833    5.0\n",
       "100834    5.0\n",
       "100835    3.0\n",
       "Name: nota, Length: 100836, dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Seleciona a coluna nota, retornando uma Série\n",
    "notas['nota']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f1356d02-82d0-4d37-88ef-90bcad44c477",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exibe o tipo do objeto (série do pandas)\n",
    "type(notas['nota'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "49f81fb3-dd41-49f9-9089-ecc95be3f1d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([4. , 5. , 3. , 2. , 1. , 4.5, 3.5, 2.5, 0.5, 1.5])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Obtém os valores únicos da coluna nota em um array\n",
    "notas['nota'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "23bb440b-37be-41e0-a9d7-7c72da9c760e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.5, 1. , 1.5, 2. , 2.5, 3. , 3.5, 4. , 4.5, 5. ])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Ordena os valores únicos da variável `nota`\n",
    "np.sort(notas['nota'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "67194021-f708-47ef-98e1-c36028fdf775",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nota\n",
       "4.0    26818\n",
       "3.0    20047\n",
       "5.0    13211\n",
       "3.5    13136\n",
       "4.5     8551\n",
       "2.0     7551\n",
       "2.5     5550\n",
       "1.0     2811\n",
       "1.5     1791\n",
       "0.5     1370\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Retorna uma contagem dos valores únicos da coluna nota (distribuição de frequência)\n",
    "notas['nota'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "82dc330d-2731-4918-9838-7119fc14a3d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nota\n",
       "4.0    0.265957\n",
       "3.0    0.198808\n",
       "5.0    0.131015\n",
       "3.5    0.130271\n",
       "4.5    0.084801\n",
       "2.0    0.074884\n",
       "2.5    0.055040\n",
       "1.0    0.027877\n",
       "1.5    0.017762\n",
       "0.5    0.013586\n",
       "Name: proportion, dtype: float64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Retorna a distribuição de frequências relativas das notas\n",
    "notas['nota'].value_counts(normalize=True)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "f5b39258-f413-4d98-bdb6-262fcd7c23db",
   "metadata": {},
   "source": [
    "**Observação:** Note que este método ordenou as notas em ordem decrescente de frequência. Com isso, podemos identificar que $4.0$ foi a nota mais frequente deste conjunto de dados, ao passo que $0.5$ foi a nota menos frequente."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4e737b8-bb02-49ba-bb9a-5abcf2085a8e",
   "metadata": {},
   "source": [
    "### Estatísticas Descritivas"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f99042c-3ec3-4210-ad14-b2f907f56f32",
   "metadata": {},
   "source": [
    "#### Média"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4287efdd-37b7-49de-8aee-8dc3dc03cbd3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.501556983616962"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Obtém a média dos valores da coluna selecionada\n",
    "# Se todos os filmes tivessem recebido a mesma nota, esta seria a nota recebida\n",
    "notas['nota'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f12c6f5b-1e1e-4e62-83a5-c7a0de5d5619",
   "metadata": {},
   "source": [
    "#### Moda"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "1757c6c9-6d15-4c1d-819e-9cf36df9ab3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.0"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exibe a moda das notas\n",
    "notas['nota'].mode()[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3732bb43-173e-416d-a34d-8fa67d09856e",
   "metadata": {},
   "source": [
    "#### Mediana"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6fab6c14-da71-49ab-8d8d-3e50064ec191",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.5"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exibe a mediana das notas\n",
    "notas['nota'].median()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "ebfb7835-21c8-46dc-b804-e9d3ab9ce02c",
   "metadata": {},
   "source": [
    "Para este cojunto de dados, observamos a seguinte desigualdade:\n",
    "\n",
    "$$moda > media > mediana$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74d51a51-7bad-4067-96fb-e4e7daacbd7d",
   "metadata": {},
   "source": [
    "### Histograma de Frequência das Notas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "960febae-7f93-40f2-a8ba-2ff782f062af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Nota mínima\n",
    "menor_nota = notas['nota'].min()\n",
    "\n",
    "# Nota máxima\n",
    "maior_nota = notas['nota'].max()\n",
    "\n",
    "# Obtém a quantidade de valores únicos\n",
    "num_notas_unicas = notas['nota'].unique().size\n",
    "\n",
    "# Obtém os limites das categorias (fronteiras das classes)\n",
    "limites_categorias = np.histogram_bin_edges(\n",
    "    notas['nota'], \n",
    "    bins=np.linspace(menor_nota, maior_nota, num=num_notas_unicas, endpoint=True)\n",
    ")\n",
    "\n",
    "# Cria um histograma de frequências para as notas\n",
    "plt.hist(x=notas['nota'], bins=limites_categorias, alpha=0.5, color='b', edgecolor='k')\n",
    "\n",
    "# Rótulo do eixo horizontal\n",
    "plt.xlabel('Nota')\n",
    "\n",
    "# Rótulo do eixo vertical\n",
    "plt.ylabel('Frequência (Número de Avalições)')\n",
    "\n",
    "# Título do gráfico\n",
    "plt.title('Histograma de Frequência para as Notas')\n",
    "\n",
    "# Define os marcadores do eixo horizontal\n",
    "plt.xticks(limites_categorias)\n",
    "\n",
    "# Exibe o histograma\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "7ed55157-2e56-465f-905b-cf23e22a5f96",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    100836.000000\n",
       "mean          3.501557\n",
       "std           1.042529\n",
       "min           0.500000\n",
       "25%           3.000000\n",
       "50%           3.500000\n",
       "75%           4.000000\n",
       "max           5.000000\n",
       "Name: nota, dtype: float64"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exibe uma descrição estatística dos valores da coluna notas\n",
    "notas['nota'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e243c09b-af8f-4f2a-8b05-8bcb287b80e4",
   "metadata": {},
   "source": [
    "Com o histograma e a descrição acima, podemos chegar as seguinte conclusões:\n",
    "\n",
    "1. Há 100.836 avaliações neste conjunto de dados;\n",
    "2. A nota média dos filmes é 3.5;\n",
    "3. A menor nota dada por um crítico foi de 0.5;\n",
    "4. A maior nota dada por um crítico foi de 5.0;\n",
    "5. A amplitude das notas é $5.0 - 0.5 = 4.5$;\n",
    "6. 25% das notas são inferiores a 3.0 e 75% são superiores a este valor;\n",
    "7. 50% das notas são inferiores a 3.5 e 50% são superiores a este valor;\n",
    "8. 75% das notas são inferiores a 4.0 e 25% são superiores a este valor;\n",
    "9. O desvio padrão das notas é de 1.04."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "e888cdc1-de20-4d73-aaf4-5390c2e68328",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Boxplot das Notas dos Filmes'}, xlabel='Nota'>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Exibe um boxplot da variável `nota`\n",
    "ax = sns.boxplot(\n",
    "    data=notas,\n",
    "    x='nota',\n",
    "    width=.5,\n",
    "    flierprops={'marker': 'o'},\n",
    "    linewidth=.75\n",
    ")\n",
    "\n",
    "# Define um título para o boxplot\n",
    "ax.set_title('Boxplot das Notas dos Filmes')\n",
    "\n",
    "# Define um título para o eixo x\n",
    "ax.set_xlabel('Nota')\n",
    "\n",
    "# Define os marcadores do eixo x\n",
    "plt.xticks(np.linspace(menor_nota, maior_nota, num=num_notas_unicas, endpoint=True))\n",
    "\n",
    "# Exibe o boxplot\n",
    "ax"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "adac5301-7a6b-4c50-af94-efde5af4a948",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Análise Exploratória de Dados (EDA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "ed16177f-eefe-4d8e-b95a-b76745ac5843",
   "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>movieId</th>\n",
       "      <th>title</th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>Adventure|Animation|Children|Comedy|Fantasy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Jumanji (1995)</td>\n",
       "      <td>Adventure|Children|Fantasy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Grumpier Old Men (1995)</td>\n",
       "      <td>Comedy|Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Waiting to Exhale (1995)</td>\n",
       "      <td>Comedy|Drama|Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Father of the Bride Part II (1995)</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   movieId                               title   \n",
       "0        1                    Toy Story (1995)  \\\n",
       "1        2                      Jumanji (1995)   \n",
       "2        3             Grumpier Old Men (1995)   \n",
       "3        4            Waiting to Exhale (1995)   \n",
       "4        5  Father of the Bride Part II (1995)   \n",
       "\n",
       "                                        genres  \n",
       "0  Adventure|Animation|Children|Comedy|Fantasy  \n",
       "1                   Adventure|Children|Fantasy  \n",
       "2                               Comedy|Romance  \n",
       "3                         Comedy|Drama|Romance  \n",
       "4                                       Comedy  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lê o arquivo com os nomes dos filmes\n",
    "filmes = pd.read_csv('movies.csv')\n",
    "\n",
    "# Exibe as cinco primeiras linhas do dataframe\n",
    "filmes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "9fd94b51-a095-4acb-a6f9-db443f79f03a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Renomeia as colunas do dataframe\n",
    "filmes.columns = ['filmeId', 'titulo', 'generos']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "872083a9-7928-4a3c-957d-97c842e1d186",
   "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>filmeId</th>\n",
       "      <th>titulo</th>\n",
       "      <th>generos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>Adventure|Animation|Children|Comedy|Fantasy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Jumanji (1995)</td>\n",
       "      <td>Adventure|Children|Fantasy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Grumpier Old Men (1995)</td>\n",
       "      <td>Comedy|Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Waiting to Exhale (1995)</td>\n",
       "      <td>Comedy|Drama|Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Father of the Bride Part II (1995)</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   filmeId                              titulo   \n",
       "0        1                    Toy Story (1995)  \\\n",
       "1        2                      Jumanji (1995)   \n",
       "2        3             Grumpier Old Men (1995)   \n",
       "3        4            Waiting to Exhale (1995)   \n",
       "4        5  Father of the Bride Part II (1995)   \n",
       "\n",
       "                                       generos  \n",
       "0  Adventure|Animation|Children|Comedy|Fantasy  \n",
       "1                   Adventure|Children|Fantasy  \n",
       "2                               Comedy|Romance  \n",
       "3                         Comedy|Drama|Romance  \n",
       "4                                       Comedy  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filmes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "63a9441d-4849-4617-a4e0-69fa0a44fad2",
   "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>usuarioId</th>\n",
       "      <th>filmeId</th>\n",
       "      <th>nota</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>874</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1434</th>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1667</th>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97364</th>\n",
       "      <td>606</td>\n",
       "      <td>1</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98479</th>\n",
       "      <td>607</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98666</th>\n",
       "      <td>608</td>\n",
       "      <td>1</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99497</th>\n",
       "      <td>609</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99534</th>\n",
       "      <td>610</td>\n",
       "      <td>1</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>215 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       usuarioId  filmeId  nota\n",
       "0              1        1   4.0\n",
       "516            5        1   4.0\n",
       "874            7        1   4.5\n",
       "1434          15        1   2.5\n",
       "1667          17        1   4.5\n",
       "...          ...      ...   ...\n",
       "97364        606        1   2.5\n",
       "98479        607        1   4.0\n",
       "98666        608        1   2.5\n",
       "99497        609        1   3.0\n",
       "99534        610        1   5.0\n",
       "\n",
       "[215 rows x 3 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Localiza todas as linhas do dataframe `notas` em que o ID do filme é 1, isto é, o filme é Toy Story\n",
    "notas.query('filmeId == 1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "cc060931-4a6c-4ab4-b159-f58490a7632c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        4.0\n",
       "516      4.0\n",
       "874      4.5\n",
       "1434     2.5\n",
       "1667     4.5\n",
       "        ... \n",
       "97364    2.5\n",
       "98479    4.0\n",
       "98666    2.5\n",
       "99497    3.0\n",
       "99534    5.0\n",
       "Name: nota, Length: 215, dtype: float64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Seleciona a coluna notas do dataframe filtrado\n",
    "notas.query('filmeId == 1')['nota']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "a009a3eb-eb4c-4d53-a644-3bc23ba0d356",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.9209302325581397"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Obtém a média das notas do filme cujo id é 1\n",
    "notas.query('filmeId == 1')['nota'].mean()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "b3f4dd53-6b2f-437a-b674-a3a8cf7fb505",
   "metadata": {},
   "source": [
    "Observamos que a média das notas do filme cujo ID é 1 é 3.92, que é superior a média de notas geral."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "6df58e06-ef4d-4192-bd7c-a1f5b98780ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "filmeId\n",
       "1         3.920930\n",
       "2         3.431818\n",
       "3         3.259615\n",
       "4         2.357143\n",
       "5         3.071429\n",
       "            ...   \n",
       "193581    4.000000\n",
       "193583    3.500000\n",
       "193585    3.500000\n",
       "193587    3.500000\n",
       "193609    4.000000\n",
       "Name: nota, Length: 9724, dtype: float64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "notas.groupby('filmeId')['nota'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "21e13f01-c63c-473e-afa9-873c4c506560",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "filmeId\n",
       "1         3.920930\n",
       "2         3.431818\n",
       "3         3.259615\n",
       "4         2.357143\n",
       "5         3.071429\n",
       "            ...   \n",
       "193581    4.000000\n",
       "193583    3.500000\n",
       "193585    3.500000\n",
       "193587    3.500000\n",
       "193609    4.000000\n",
       "Name: nota, Length: 9724, dtype: float64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "medias_por_filme = notas.groupby('filmeId')['nota'].mean()\n",
    "medias_por_filme"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "54760efc-5a19-404f-b498-779c3b161bde",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Obtém os limites das categorias\n",
    "limites_categorias = np.histogram_bin_edges(\n",
    "    medias_por_filme, \n",
    "    bins=np.linspace(menor_nota, maior_nota, num=num_notas_unicas, endpoint=True)\n",
    ")\n",
    "\n",
    "# Cria um histograma de frequências para as notas\n",
    "plt.hist(x=medias_por_filme, bins=limites_categorias, alpha=0.5, color='b', edgecolor='k')\n",
    "\n",
    "# Rótulo do eixo horizontal\n",
    "plt.xlabel('Média')\n",
    "\n",
    "# Rótulo do eixo vertical\n",
    "plt.ylabel('Frequência')\n",
    "\n",
    "# Título do gráfico\n",
    "plt.title('Histograma de Frequência para as Médias das Notas')\n",
    "\n",
    "# Define os marcadores do eixo horizontal\n",
    "plt.xticks(limites_categorias)\n",
    "\n",
    "# Exibe o histograma\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "f480deb3-568a-4c82-92a2-824f253f8bed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='nota'>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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xZMmSWLt2bUlTtaY1a9ZERER3d/ewyx988MG44YYbxn4gYu/evbF48eLo6+uLyZMnR1dXVzzzzDNx+eWXlz0alO7Pf/5zXHfddfHOO+/E1KlT48tf/nJs2bIlpk6dOuaz+LhnACDxdxAAgEQgAACJQAAAEoEAACQCAQBIBAIAkAgEACARCABAIhAAgEQgAIe1YsWK+PznP1/2GEAJBAIAkAgEOI51d3fHzTffHMuXL48pU6bEaaedFitWrBi6/q233oqFCxfGiSeeGB0dHXHNNdfEX//614iIWLt2baxcuTJeeOGFKIoiiqIY+rCxe++9N84777yYNGlSdHZ2xo033hj79+8vYQuB0SIQ4Di3bt26mDRpUjz//PNxzz33xN133x0bNmyIer0eCxcujHfffTc2bdoUGzZsiDfeeCOuvfbaiIi49tpr4/bbb49Zs2ZFX19f9PX1DV3X1tYW9913X+zatSvWrVsXv//972P58uVlbiZwjPk0RziOdXd3R61Wi+eee27osi9+8Ytx2WWXxdy5c2P+/Pmxe/fu6OzsjIiIl19+OWbNmhVbt26Niy66KFasWBGPPfZY7Ny58z+uZ/369fGtb30r3n777dHcHGAMOYIAx7murq5hy5/61Kdi79698corr0RnZ+dQHEREzJw5M0466aR45ZVX/uN9PvvsszF37tz49Kc/HdVqNa6//vp455134v333x+VbQDGnkCA49yECROGLRdFEfV6fcT39+abb8bXvva16Orqit/+9rfR09MT999/f0RE/OMf//ivZgWaR3vZAwDlOOecc6K3tzd6e3uHvcXw3nvvxcyZMyMi4oQTToharTbsdj09PVGv1+OHP/xhtLV9+G+MRx55ZGyHB0adIwjQoubNmxfnnXdeLFq0KHbs2BFbt26NxYsXxyWXXBIXXnhhRER85jOfid27d8fOnTvj7bffjsHBwTjrrLPigw8+iB//+MfxxhtvxC9+8Yv46U9/WvLWAMeaQIAWVRRFPP7443HyySfHnDlzYt68eXHmmWfGr3/966Gf+cY3vhFXXnllXHrppTF16tT41a9+Feeff37ce++98YMf/CDOPffc+OUvfxmrVq0qcUuA0eB/MQAAiSMIAEAiEACARCAAAIlAAAASgQAAJAIBAEgEAgCQCAQAIBEIAEAiEACARCAAAMn/AU8pijlhfCa4AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Exibe um box plot com a distribuição das notas médias\n",
    "sns.boxplot(\n",
    "    x=medias_por_filme,\n",
    "    width=.5,\n",
    "    flierprops={'marker': '.'},\n",
    "    linewidth=.75\n",
    ")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "9b26f53b-a0f7-4b62-8379-325f4846c62b",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Analisando alguma Variáveis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "2452dc01-0fa8-4b25-a213-bc27d7e83d76",
   "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>budget</th>\n",
       "      <th>genres</th>\n",
       "      <th>homepage</th>\n",
       "      <th>id</th>\n",
       "      <th>keywords</th>\n",
       "      <th>original_language</th>\n",
       "      <th>original_title</th>\n",
       "      <th>overview</th>\n",
       "      <th>popularity</th>\n",
       "      <th>production_companies</th>\n",
       "      <th>production_countries</th>\n",
       "      <th>release_date</th>\n",
       "      <th>revenue</th>\n",
       "      <th>runtime</th>\n",
       "      <th>spoken_languages</th>\n",
       "      <th>status</th>\n",
       "      <th>tagline</th>\n",
       "      <th>title</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>237000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
       "      <td>http://www.avatarmovie.com/</td>\n",
       "      <td>19995</td>\n",
       "      <td>[{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...</td>\n",
       "      <td>en</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>In the 22nd century, a paraplegic Marine is di...</td>\n",
       "      <td>150.437577</td>\n",
       "      <td>[{\"name\": \"Ingenious Film Partners\", \"id\": 289...</td>\n",
       "      <td>[{\"iso_3166_1\": \"US\", \"name\": \"United States o...</td>\n",
       "      <td>2009-12-10</td>\n",
       "      <td>2787965087</td>\n",
       "      <td>162.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...</td>\n",
       "      <td>Released</td>\n",
       "      <td>Enter the World of Pandora.</td>\n",
       "      <td>Avatar</td>\n",
       "      <td>7.2</td>\n",
       "      <td>11800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>300000000</td>\n",
       "      <td>[{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...</td>\n",
       "      <td>http://disney.go.com/disneypictures/pirates/</td>\n",
       "      <td>285</td>\n",
       "      <td>[{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...</td>\n",
       "      <td>en</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>Captain Barbossa, long believed to be dead, ha...</td>\n",
       "      <td>139.082615</td>\n",
       "      <td>[{\"name\": \"Walt Disney Pictures\", \"id\": 2}, {\"...</td>\n",
       "      <td>[{\"iso_3166_1\": \"US\", \"name\": \"United States o...</td>\n",
       "      <td>2007-05-19</td>\n",
       "      <td>961000000</td>\n",
       "      <td>169.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>At the end of the world, the adventure begins.</td>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>6.9</td>\n",
       "      <td>4500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>245000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
       "      <td>http://www.sonypictures.com/movies/spectre/</td>\n",
       "      <td>206647</td>\n",
       "      <td>[{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...</td>\n",
       "      <td>en</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>A cryptic message from Bond’s past sends him o...</td>\n",
       "      <td>107.376788</td>\n",
       "      <td>[{\"name\": \"Columbia Pictures\", \"id\": 5}, {\"nam...</td>\n",
       "      <td>[{\"iso_3166_1\": \"GB\", \"name\": \"United Kingdom\"...</td>\n",
       "      <td>2015-10-26</td>\n",
       "      <td>880674609</td>\n",
       "      <td>148.0</td>\n",
       "      <td>[{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"},...</td>\n",
       "      <td>Released</td>\n",
       "      <td>A Plan No One Escapes</td>\n",
       "      <td>Spectre</td>\n",
       "      <td>6.3</td>\n",
       "      <td>4466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>250000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam...</td>\n",
       "      <td>http://www.thedarkknightrises.com/</td>\n",
       "      <td>49026</td>\n",
       "      <td>[{\"id\": 849, \"name\": \"dc comics\"}, {\"id\": 853,...</td>\n",
       "      <td>en</td>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>Following the death of District Attorney Harve...</td>\n",
       "      <td>112.312950</td>\n",
       "      <td>[{\"name\": \"Legendary Pictures\", \"id\": 923}, {\"...</td>\n",
       "      <td>[{\"iso_3166_1\": \"US\", \"name\": \"United States o...</td>\n",
       "      <td>2012-07-16</td>\n",
       "      <td>1084939099</td>\n",
       "      <td>165.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>The Legend Ends</td>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>7.6</td>\n",
       "      <td>9106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>260000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
       "      <td>http://movies.disney.com/john-carter</td>\n",
       "      <td>49529</td>\n",
       "      <td>[{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...</td>\n",
       "      <td>en</td>\n",
       "      <td>John Carter</td>\n",
       "      <td>John Carter is a war-weary, former military ca...</td>\n",
       "      <td>43.926995</td>\n",
       "      <td>[{\"name\": \"Walt Disney Pictures\", \"id\": 2}]</td>\n",
       "      <td>[{\"iso_3166_1\": \"US\", \"name\": \"United States o...</td>\n",
       "      <td>2012-03-07</td>\n",
       "      <td>284139100</td>\n",
       "      <td>132.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>Lost in our world, found in another.</td>\n",
       "      <td>John Carter</td>\n",
       "      <td>6.1</td>\n",
       "      <td>2124</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      budget                                             genres   \n",
       "0  237000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...  \\\n",
       "1  300000000  [{\"id\": 12, \"name\": \"Adventure\"}, {\"id\": 14, \"...   \n",
       "2  245000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
       "3  250000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam...   \n",
       "4  260000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...   \n",
       "\n",
       "                                       homepage      id   \n",
       "0                   http://www.avatarmovie.com/   19995  \\\n",
       "1  http://disney.go.com/disneypictures/pirates/     285   \n",
       "2   http://www.sonypictures.com/movies/spectre/  206647   \n",
       "3            http://www.thedarkknightrises.com/   49026   \n",
       "4          http://movies.disney.com/john-carter   49529   \n",
       "\n",
       "                                            keywords original_language   \n",
       "0  [{\"id\": 1463, \"name\": \"culture clash\"}, {\"id\":...                en  \\\n",
       "1  [{\"id\": 270, \"name\": \"ocean\"}, {\"id\": 726, \"na...                en   \n",
       "2  [{\"id\": 470, \"name\": \"spy\"}, {\"id\": 818, \"name...                en   \n",
       "3  [{\"id\": 849, \"name\": \"dc comics\"}, {\"id\": 853,...                en   \n",
       "4  [{\"id\": 818, \"name\": \"based on novel\"}, {\"id\":...                en   \n",
       "\n",
       "                             original_title   \n",
       "0                                    Avatar  \\\n",
       "1  Pirates of the Caribbean: At World's End   \n",
       "2                                   Spectre   \n",
       "3                     The Dark Knight Rises   \n",
       "4                               John Carter   \n",
       "\n",
       "                                            overview  popularity   \n",
       "0  In the 22nd century, a paraplegic Marine is di...  150.437577  \\\n",
       "1  Captain Barbossa, long believed to be dead, ha...  139.082615   \n",
       "2  A cryptic message from Bond’s past sends him o...  107.376788   \n",
       "3  Following the death of District Attorney Harve...  112.312950   \n",
       "4  John Carter is a war-weary, former military ca...   43.926995   \n",
       "\n",
       "                                production_companies   \n",
       "0  [{\"name\": \"Ingenious Film Partners\", \"id\": 289...  \\\n",
       "1  [{\"name\": \"Walt Disney Pictures\", \"id\": 2}, {\"...   \n",
       "2  [{\"name\": \"Columbia Pictures\", \"id\": 5}, {\"nam...   \n",
       "3  [{\"name\": \"Legendary Pictures\", \"id\": 923}, {\"...   \n",
       "4        [{\"name\": \"Walt Disney Pictures\", \"id\": 2}]   \n",
       "\n",
       "                                production_countries release_date     revenue   \n",
       "0  [{\"iso_3166_1\": \"US\", \"name\": \"United States o...   2009-12-10  2787965087  \\\n",
       "1  [{\"iso_3166_1\": \"US\", \"name\": \"United States o...   2007-05-19   961000000   \n",
       "2  [{\"iso_3166_1\": \"GB\", \"name\": \"United Kingdom\"...   2015-10-26   880674609   \n",
       "3  [{\"iso_3166_1\": \"US\", \"name\": \"United States o...   2012-07-16  1084939099   \n",
       "4  [{\"iso_3166_1\": \"US\", \"name\": \"United States o...   2012-03-07   284139100   \n",
       "\n",
       "   runtime                                   spoken_languages    status   \n",
       "0    162.0  [{\"iso_639_1\": \"en\", \"name\": \"English\"}, {\"iso...  Released  \\\n",
       "1    169.0           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
       "2    148.0  [{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"},...  Released   \n",
       "3    165.0           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
       "4    132.0           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]  Released   \n",
       "\n",
       "                                          tagline   \n",
       "0                     Enter the World of Pandora.  \\\n",
       "1  At the end of the world, the adventure begins.   \n",
       "2                           A Plan No One Escapes   \n",
       "3                                 The Legend Ends   \n",
       "4            Lost in our world, found in another.   \n",
       "\n",
       "                                      title  vote_average  vote_count  \n",
       "0                                    Avatar           7.2       11800  \n",
       "1  Pirates of the Caribbean: At World's End           6.9        4500  \n",
       "2                                   Spectre           6.3        4466  \n",
       "3                     The Dark Knight Rises           7.6        9106  \n",
       "4                               John Carter           6.1        2124  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Base de dados do tmdb 5000\n",
    "tmdb = pd.read_csv('tmdb_5000_movies.csv')\n",
    "tmdb.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "9bc0f8de-3aaf-4674-b854-2eae0adc5098",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['en', 'ja', 'fr', 'zh', 'es', 'de', 'hi', 'ru', 'ko', 'te', 'cn',\n",
       "       'it', 'nl', 'ta', 'sv', 'th', 'da', 'xx', 'hu', 'cs', 'pt', 'is',\n",
       "       'tr', 'nb', 'af', 'pl', 'he', 'ar', 'vi', 'ky', 'id', 'ro', 'fa',\n",
       "       'no', 'sl', 'ps', 'el'], dtype=object)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Valores únicos de idiomas\n",
    "tmdb['original_language'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "080ce80d-4024-4b79-a6b8-4d0f5443dfbc",
   "metadata": {},
   "source": [
    "- **Tipo de Dado:** qualitativo\n",
    "- **Nível de Mensuração:** nominal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "25302b79-8511-478c-9f8d-d783cae676cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       237000000\n",
       "1       300000000\n",
       "2       245000000\n",
       "3       250000000\n",
       "4       260000000\n",
       "          ...    \n",
       "4798       220000\n",
       "4799         9000\n",
       "4800            0\n",
       "4801            0\n",
       "4802            0\n",
       "Name: budget, Length: 4803, dtype: int64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tmdb['budget']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "892f8985-d364-4c33-b022-e38600fe9a4a",
   "metadata": {},
   "source": [
    "- **Tipo de Dado:** quantitativo\n",
    "- **Nível de Mensuração:** razão"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "c08aa7e7-a027-4e5c-b353-81a92bcfcbf1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       11800\n",
       "1        4500\n",
       "2        4466\n",
       "3        9106\n",
       "4        2124\n",
       "        ...  \n",
       "4798      238\n",
       "4799        5\n",
       "4800        6\n",
       "4801        7\n",
       "4802       16\n",
       "Name: vote_count, Length: 4803, dtype: int64"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tmdb['vote_count']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93119c6e-8d0d-4dc6-b46a-0e21f95ee227",
   "metadata": {},
   "source": [
    "- **Tipo de Dado:** quantitativo\n",
    "- **Nível de Mensuração:** razão"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "1a862dc5-d015-40dc-bad0-cba3031367c1",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Visualização de Dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "31fa5a9e-279e-4e91-a358-8d6f43f7c567",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "original_language\n",
       "en    4505\n",
       "fr      70\n",
       "es      32\n",
       "zh      27\n",
       "de      27\n",
       "hi      19\n",
       "ja      16\n",
       "it      14\n",
       "cn      12\n",
       "ru      11\n",
       "ko      11\n",
       "pt       9\n",
       "da       7\n",
       "sv       5\n",
       "nl       4\n",
       "fa       4\n",
       "th       3\n",
       "he       3\n",
       "ta       2\n",
       "cs       2\n",
       "ro       2\n",
       "id       2\n",
       "ar       2\n",
       "vi       1\n",
       "sl       1\n",
       "ps       1\n",
       "no       1\n",
       "ky       1\n",
       "hu       1\n",
       "pl       1\n",
       "af       1\n",
       "nb       1\n",
       "tr       1\n",
       "is       1\n",
       "xx       1\n",
       "te       1\n",
       "el       1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Conta o número de vezes que cada idioma aparece na coluna original_language\n",
    "tmdb['original_language'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "b9087d53-8081-470d-8849-c684d6b75ede",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4505"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "contagem_linguas = tmdb['original_language'].value_counts()\n",
    "contagem_linguas.loc['en']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "7a9f7d42-3f2c-4a77-b5d9-71e79b05ec05",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['en', 'fr', 'es', 'zh', 'de', 'hi', 'ja', 'it', 'cn', 'ru', 'ko', 'pt',\n",
       "       'da', 'sv', 'nl', 'fa', 'th', 'he', 'ta', 'cs', 'ro', 'id', 'ar', 'vi',\n",
       "       'sl', 'ps', 'no', 'ky', 'hu', 'pl', 'af', 'nb', 'tr', 'is', 'xx', 'te',\n",
       "       'el'],\n",
       "      dtype='object', name='original_language')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Obtém um array com os índices da série\n",
    "tmdb['original_language'].value_counts().index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "205c1409-755d-4121-a64d-4951185d505f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([4505,   70,   32,   27,   27,   19,   16,   14,   12,   11,   11,\n",
       "          9,    7,    5,    4,    4,    3,    3,    2,    2,    2,    2,\n",
       "          2,    1,    1,    1,    1,    1,    1,    1,    1,    1,    1,\n",
       "          1,    1,    1,    1])"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Obtém um array com os valores da série\n",
    "tmdb['original_language'].value_counts().values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "02181d2b-ebba-452f-b273-670c2f370515",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe 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>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>original_language</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>en</th>\n",
       "      <td>4505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fr</th>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>es</th>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zh</th>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>de</th>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hi</th>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ja</th>\n",
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       "      <th>it</th>\n",
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       "    <tr>\n",
       "      <th>ko</th>\n",
       "      <td>11</td>\n",
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       "    <tr>\n",
       "      <th>pt</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>da</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sv</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nl</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fa</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>th</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>he</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ta</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cs</th>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>ro</th>\n",
       "      <td>2</td>\n",
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       "      <th>id</th>\n",
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       "    <tr>\n",
       "      <th>ar</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vi</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sl</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ps</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>no</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ky</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hu</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pl</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>af</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nb</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tr</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>is</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>xx</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>te</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>el</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   count\n",
       "original_language       \n",
       "en                  4505\n",
       "fr                    70\n",
       "es                    32\n",
       "zh                    27\n",
       "de                    27\n",
       "hi                    19\n",
       "ja                    16\n",
       "it                    14\n",
       "cn                    12\n",
       "ru                    11\n",
       "ko                    11\n",
       "pt                     9\n",
       "da                     7\n",
       "sv                     5\n",
       "nl                     4\n",
       "fa                     4\n",
       "th                     3\n",
       "he                     3\n",
       "ta                     2\n",
       "cs                     2\n",
       "ro                     2\n",
       "id                     2\n",
       "ar                     2\n",
       "vi                     1\n",
       "sl                     1\n",
       "ps                     1\n",
       "no                     1\n",
       "ky                     1\n",
       "hu                     1\n",
       "pl                     1\n",
       "af                     1\n",
       "nb                     1\n",
       "tr                     1\n",
       "is                     1\n",
       "xx                     1\n",
       "te                     1\n",
       "el                     1"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Converte a série em um dataframe\n",
    "tmdb['original_language'].value_counts().to_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "600abdb7-69dc-49d7-976b-6b0298a42690",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>original_language</th>\n",
       "      <th>count</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
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       "      <td>70</td>\n",
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       "      <th>2</th>\n",
       "      <td>es</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
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       "      <th>3</th>\n",
       "      <td>zh</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>de</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>hi</td>\n",
       "      <td>19</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>ja</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>cn</td>\n",
       "      <td>12</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>ko</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>pt</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>da</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>sv</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>nl</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>fa</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>th</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>he</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>ta</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>cs</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>ro</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>id</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>ar</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>vi</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>sl</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>ps</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>no</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>ky</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>hu</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>pl</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>af</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>nb</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>tr</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>is</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>xx</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>te</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>el</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   original_language  count\n",
       "0                 en   4505\n",
       "1                 fr     70\n",
       "2                 es     32\n",
       "3                 zh     27\n",
       "4                 de     27\n",
       "5                 hi     19\n",
       "6                 ja     16\n",
       "7                 it     14\n",
       "8                 cn     12\n",
       "9                 ru     11\n",
       "10                ko     11\n",
       "11                pt      9\n",
       "12                da      7\n",
       "13                sv      5\n",
       "14                nl      4\n",
       "15                fa      4\n",
       "16                th      3\n",
       "17                he      3\n",
       "18                ta      2\n",
       "19                cs      2\n",
       "20                ro      2\n",
       "21                id      2\n",
       "22                ar      2\n",
       "23                vi      1\n",
       "24                sl      1\n",
       "25                ps      1\n",
       "26                no      1\n",
       "27                ky      1\n",
       "28                hu      1\n",
       "29                pl      1\n",
       "30                af      1\n",
       "31                nb      1\n",
       "32                tr      1\n",
       "33                is      1\n",
       "34                xx      1\n",
       "35                te      1\n",
       "36                el      1"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reseta os índices\n",
    "tmdb['original_language'].value_counts().to_frame().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "7ab41284-48cb-401f-86f6-bb8d3e52de83",
   "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>original_language</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>en</td>\n",
       "      <td>4505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>fr</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>es</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>zh</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>de</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  original_language  total\n",
       "0                en   4505\n",
       "1                fr     70\n",
       "2                es     32\n",
       "3                zh     27\n",
       "4                de     27"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "contagem_de_linguas = tmdb['original_language'].value_counts().to_frame().reset_index()\n",
    "contagem_de_linguas.columns = ['original_language', 'total']\n",
    "contagem_de_linguas.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "c56efba9-09c1-4cfc-9fef-79c43fff9e4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='original_language', ylabel='total'>"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='original_language', y='total', data=contagem_de_linguas)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "a54361a4-0783-4cea-8811-ac299badb046",
   "metadata": {},
   "source": [
    "Para o conjunto de dados que estamos analisando, o gráfico de barras nos informa que existem mais filmes na língua inglesa do que nas demais línguas. No entanto, ele nos diz pouco acerca da quantidade de filmes produzidos em outros idiomas, porque as barras menores não são vistas claramente. Além disso, os rótulos do eixo horizontal estão sobrepostos."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "27c43506-e8b8-4052-af9c-d0447da7246a",
   "metadata": {},
   "source": [
    "Em vez de criarmos um dataframe com a contagem do número de aparições de cada idioma para depois plotarmos um gráfico de barras com `sns.barplot()`, podemos usar um gráfico de categorias — `sns.catplot()` — e especificar um tipo de agregação como contagem."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "826010ee-32da-4d64-b9c0-8dfa15d3999c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7f5913672a50>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Conta o número de aparições de cada idioma e plota um gráfico de barras\n",
    "sns.catplot(x='original_language', kind='count', data=tmdb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "6e302849-8a7f-4a5d-9cb6-99dfd71903b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "original_language\n",
       "en    4505\n",
       "fr      70\n",
       "es      32\n",
       "zh      27\n",
       "de      27\n",
       "hi      19\n",
       "ja      16\n",
       "it      14\n",
       "cn      12\n",
       "ru      11\n",
       "ko      11\n",
       "pt       9\n",
       "da       7\n",
       "sv       5\n",
       "nl       4\n",
       "fa       4\n",
       "th       3\n",
       "he       3\n",
       "ta       2\n",
       "cs       2\n",
       "ro       2\n",
       "id       2\n",
       "ar       2\n",
       "vi       1\n",
       "sl       1\n",
       "ps       1\n",
       "no       1\n",
       "ky       1\n",
       "hu       1\n",
       "pl       1\n",
       "af       1\n",
       "nb       1\n",
       "tr       1\n",
       "is       1\n",
       "xx       1\n",
       "te       1\n",
       "el       1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_por_lingua = tmdb['original_language'].value_counts()\n",
    "total_por_lingua"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "2d9b3e30-4d4b-4c78-9f57-2625c8938d38",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total Geral: 4803\n",
      "Total Inglês: 4505\n",
      "Total Resto: 298\n"
     ]
    }
   ],
   "source": [
    "# Soma os valores da série\n",
    "total_geral = total_por_lingua.sum()\n",
    "\n",
    "# Obtém o total para inglês\n",
    "total_ingles = total_por_lingua.loc['en']\n",
    "\n",
    "# Obtém o total para as outras línguas\n",
    "total_resto = total_geral - total_ingles\n",
    "\n",
    "# Exibição\n",
    "print(f'Total Geral: {total_geral}')\n",
    "print(f'Total Inglês: {total_ingles}')\n",
    "print(f'Total Resto: {total_resto}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "5c73a880-5d59-4191-9f9e-2b7041b97bbc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='lingua', ylabel='totais'>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Cria um dicionário para armazenar os dados que obtivemos\n",
    "dados = {\n",
    "    'lingua': ['Inglês', 'Outras'],\n",
    "    'totais': [total_ingles, total_resto]\n",
    "}\n",
    "\n",
    "# Cria um dataframe a partir do dicionário acima\n",
    "df = pd.DataFrame(dados)\n",
    "\n",
    "# Plota um gráfico de barras a partir do dataframe\n",
    "sns.barplot(x='lingua', y='totais', data=df)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "d938486f-0256-4b10-b873-4deb8ee048b5",
   "metadata": {},
   "source": [
    "Com esta visualização nossa mensagem fica muito mais clara: Existem muito mais filmes em inglês do que filmes em outras línguas, mesmo quando estes últimos são considerados juntos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "1ef78fbc-a1a6-4709-8aeb-6e1e99bd1564",
   "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>budget</th>\n",
       "      <th>genres</th>\n",
       "      <th>homepage</th>\n",
       "      <th>id</th>\n",
       "      <th>keywords</th>\n",
       "      <th>original_language</th>\n",
       "      <th>original_title</th>\n",
       "      <th>overview</th>\n",
       "      <th>popularity</th>\n",
       "      <th>production_companies</th>\n",
       "      <th>production_countries</th>\n",
       "      <th>release_date</th>\n",
       "      <th>revenue</th>\n",
       "      <th>runtime</th>\n",
       "      <th>spoken_languages</th>\n",
       "      <th>status</th>\n",
       "      <th>tagline</th>\n",
       "      <th>title</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>15000000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>315011</td>\n",
       "      <td>[{\"id\": 1299, \"name\": \"monster\"}, {\"id\": 7671,...</td>\n",
       "      <td>ja</td>\n",
       "      <td>シン・ゴジラ</td>\n",
       "      <td>From the mind behind Evangelion comes a hit la...</td>\n",
       "      <td>9.476999</td>\n",
       "      <td>[{\"name\": \"Cine Bazar\", \"id\": 5896}, {\"name\": ...</td>\n",
       "      <td>[{\"iso_3166_1\": \"JP\", \"name\": \"Japan\"}]</td>\n",
       "      <td>2016-07-29</td>\n",
       "      <td>77000000</td>\n",
       "      <td>120.0</td>\n",
       "      <td>[{\"iso_639_1\": \"it\", \"name\": \"Italiano\"}, {\"is...</td>\n",
       "      <td>Released</td>\n",
       "      <td>A god incarnate. A city doomed.</td>\n",
       "      <td>Shin Godzilla</td>\n",
       "      <td>6.5</td>\n",
       "      <td>143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>235</th>\n",
       "      <td>97250400</td>\n",
       "      <td>[{\"id\": 14, \"name\": \"Fantasy\"}, {\"id\": 12, \"na...</td>\n",
       "      <td>http://www.asterixauxjeuxolympiques.com/index.php</td>\n",
       "      <td>2395</td>\n",
       "      <td>[{\"id\": 271, \"name\": \"competition\"}, {\"id\": 12...</td>\n",
       "      <td>fr</td>\n",
       "      <td>Astérix aux Jeux Olympiques</td>\n",
       "      <td>Astérix and Obélix have to win the Olympic Gam...</td>\n",
       "      <td>20.344364</td>\n",
       "      <td>[{\"name\": \"Constantin Film\", \"id\": 47}, {\"name...</td>\n",
       "      <td>[{\"iso_3166_1\": \"BE\", \"name\": \"Belgium\"}, {\"is...</td>\n",
       "      <td>2008-01-13</td>\n",
       "      <td>132900000</td>\n",
       "      <td>116.0</td>\n",
       "      <td>[{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"},...</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Asterix at the Olympic Games</td>\n",
       "      <td>5.0</td>\n",
       "      <td>471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317</th>\n",
       "      <td>94000000</td>\n",
       "      <td>[{\"id\": 18, \"name\": \"Drama\"}, {\"id\": 36, \"name...</td>\n",
       "      <td>http://www.theflowersofwarmovie.com/</td>\n",
       "      <td>76758</td>\n",
       "      <td>[{\"id\": 173251, \"name\": \"forced prostitution\"}...</td>\n",
       "      <td>zh</td>\n",
       "      <td>金陵十三釵</td>\n",
       "      <td>A Westerner finds refuge with a group of women...</td>\n",
       "      <td>12.516546</td>\n",
       "      <td>[{\"name\": \"Beijing New Picture Film Co. Ltd.\",...</td>\n",
       "      <td>[{\"iso_3166_1\": \"CN\", \"name\": \"China\"}, {\"iso_...</td>\n",
       "      <td>2011-12-15</td>\n",
       "      <td>95311434</td>\n",
       "      <td>145.0</td>\n",
       "      <td>[{\"iso_639_1\": \"zh\", \"name\": \"\\u666e\\u901a\\u8b...</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>The Flowers of War</td>\n",
       "      <td>7.1</td>\n",
       "      <td>187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>474</th>\n",
       "      <td>0</td>\n",
       "      <td>[{\"id\": 9648, \"name\": \"Mystery\"}, {\"id\": 18, \"...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>330770</td>\n",
       "      <td>[{\"id\": 428, \"name\": \"nurse\"}, {\"id\": 658, \"na...</td>\n",
       "      <td>fr</td>\n",
       "      <td>Évolution</td>\n",
       "      <td>11-year-old Nicolas lives with his mother in a...</td>\n",
       "      <td>3.300061</td>\n",
       "      <td>[{\"name\": \"Ex Nihilo\", \"id\": 3307}, {\"name\": \"...</td>\n",
       "      <td>[{\"iso_3166_1\": \"BE\", \"name\": \"Belgium\"}, {\"is...</td>\n",
       "      <td>2015-09-14</td>\n",
       "      <td>0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>[{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Evolution</td>\n",
       "      <td>6.4</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>8000000</td>\n",
       "      <td>[{\"id\": 35, \"name\": \"Comedy\"}, {\"id\": 16, \"nam...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>293644</td>\n",
       "      <td>[{\"id\": 209714, \"name\": \"3d\"}]</td>\n",
       "      <td>es</td>\n",
       "      <td>Don Gato: El inicio de la pandilla</td>\n",
       "      <td>Top Cat has arrived to charm his way into your...</td>\n",
       "      <td>0.719996</td>\n",
       "      <td>[{\"name\": \"Anima Estudios\", \"id\": 9965}, {\"nam...</td>\n",
       "      <td>[{\"iso_3166_1\": \"IN\", \"name\": \"India\"}, {\"iso_...</td>\n",
       "      <td>2015-10-30</td>\n",
       "      <td>0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>[]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Top Cat Begins</td>\n",
       "      <td>5.3</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4739</th>\n",
       "      <td>0</td>\n",
       "      <td>[{\"id\": 35, \"name\": \"Comedy\"}, {\"id\": 10749, \"...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90414</td>\n",
       "      <td>[{\"id\": 187056, \"name\": \"woman director\"}]</td>\n",
       "      <td>fr</td>\n",
       "      <td>I Love You, Don't Touch Me!</td>\n",
       "      <td>The story of a 25 year old virgin girl, lookin...</td>\n",
       "      <td>0.020839</td>\n",
       "      <td>[]</td>\n",
       "      <td>[{\"iso_3166_1\": \"US\", \"name\": \"United States o...</td>\n",
       "      <td>1997-01-21</td>\n",
       "      <td>0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>[{\"iso_639_1\": \"en\", \"name\": \"English\"}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>Just Your Typical Boy-Loves-Girl Who Doesn't L...</td>\n",
       "      <td>I Love You, Don't Touch Me!</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4751</th>\n",
       "      <td>0</td>\n",
       "      <td>[{\"id\": 18, \"name\": \"Drama\"}, {\"id\": 10749, \"n...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42109</td>\n",
       "      <td>[]</td>\n",
       "      <td>pt</td>\n",
       "      <td>Gabriela, Cravo e Canela</td>\n",
       "      <td>In 1925, Gabriela becomes cook, mistress, and ...</td>\n",
       "      <td>0.557602</td>\n",
       "      <td>[{\"name\": \"United Artists\", \"id\": 60}, {\"name\"...</td>\n",
       "      <td>[{\"iso_3166_1\": \"BR\", \"name\": \"Brazil\"}]</td>\n",
       "      <td>1983-03-24</td>\n",
       "      <td>0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>[{\"iso_639_1\": \"pt\", \"name\": \"Portugu\\u00eas\"}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gabriela</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4790</th>\n",
       "      <td>0</td>\n",
       "      <td>[{\"id\": 18, \"name\": \"Drama\"}, {\"id\": 10769, \"n...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13898</td>\n",
       "      <td>[]</td>\n",
       "      <td>fa</td>\n",
       "      <td>دایره</td>\n",
       "      <td>Various women struggle to function in the oppr...</td>\n",
       "      <td>1.193779</td>\n",
       "      <td>[{\"name\": \"Jafar Panahi Film Productions\", \"id...</td>\n",
       "      <td>[{\"iso_3166_1\": \"IR\", \"name\": \"Iran\"}]</td>\n",
       "      <td>2000-09-08</td>\n",
       "      <td>0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>[{\"iso_639_1\": \"fa\", \"name\": \"\\u0641\\u0627\\u06...</td>\n",
       "      <td>Released</td>\n",
       "      <td>NaN</td>\n",
       "      <td>The Circle</td>\n",
       "      <td>6.6</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4792</th>\n",
       "      <td>20000</td>\n",
       "      <td>[{\"id\": 80, \"name\": \"Crime\"}, {\"id\": 27, \"name...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36095</td>\n",
       "      <td>[{\"id\": 233, \"name\": \"japan\"}, {\"id\": 549, \"na...</td>\n",
       "      <td>ja</td>\n",
       "      <td>キュア</td>\n",
       "      <td>A wave of gruesome murders is sweeping Tokyo. ...</td>\n",
       "      <td>0.212443</td>\n",
       "      <td>[{\"name\": \"Daiei Studios\", \"id\": 881}]</td>\n",
       "      <td>[{\"iso_3166_1\": \"JP\", \"name\": \"Japan\"}]</td>\n",
       "      <td>1997-11-06</td>\n",
       "      <td>99000</td>\n",
       "      <td>111.0</td>\n",
       "      <td>[{\"iso_639_1\": \"ja\", \"name\": \"\\u65e5\\u672c\\u8a...</td>\n",
       "      <td>Released</td>\n",
       "      <td>Madness. Terror. Murder.</td>\n",
       "      <td>Cure</td>\n",
       "      <td>7.4</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4798</th>\n",
       "      <td>220000</td>\n",
       "      <td>[{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9367</td>\n",
       "      <td>[{\"id\": 5616, \"name\": \"united states\\u2013mexi...</td>\n",
       "      <td>es</td>\n",
       "      <td>El Mariachi</td>\n",
       "      <td>El Mariachi just wants to play his guitar and ...</td>\n",
       "      <td>14.269792</td>\n",
       "      <td>[{\"name\": \"Columbia Pictures\", \"id\": 5}]</td>\n",
       "      <td>[{\"iso_3166_1\": \"MX\", \"name\": \"Mexico\"}, {\"iso...</td>\n",
       "      <td>1992-09-04</td>\n",
       "      <td>2040920</td>\n",
       "      <td>81.0</td>\n",
       "      <td>[{\"iso_639_1\": \"es\", \"name\": \"Espa\\u00f1ol\"}]</td>\n",
       "      <td>Released</td>\n",
       "      <td>He didn't come looking for trouble, but troubl...</td>\n",
       "      <td>El Mariachi</td>\n",
       "      <td>6.6</td>\n",
       "      <td>238</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>298 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        budget                                             genres   \n",
       "97    15000000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 12, \"nam...  \\\n",
       "235   97250400  [{\"id\": 14, \"name\": \"Fantasy\"}, {\"id\": 12, \"na...   \n",
       "317   94000000  [{\"id\": 18, \"name\": \"Drama\"}, {\"id\": 36, \"name...   \n",
       "474          0  [{\"id\": 9648, \"name\": \"Mystery\"}, {\"id\": 18, \"...   \n",
       "492    8000000  [{\"id\": 35, \"name\": \"Comedy\"}, {\"id\": 16, \"nam...   \n",
       "...        ...                                                ...   \n",
       "4739         0  [{\"id\": 35, \"name\": \"Comedy\"}, {\"id\": 10749, \"...   \n",
       "4751         0  [{\"id\": 18, \"name\": \"Drama\"}, {\"id\": 10749, \"n...   \n",
       "4790         0  [{\"id\": 18, \"name\": \"Drama\"}, {\"id\": 10769, \"n...   \n",
       "4792     20000  [{\"id\": 80, \"name\": \"Crime\"}, {\"id\": 27, \"name...   \n",
       "4798    220000  [{\"id\": 28, \"name\": \"Action\"}, {\"id\": 80, \"nam...   \n",
       "\n",
       "                                               homepage      id   \n",
       "97                                                  NaN  315011  \\\n",
       "235   http://www.asterixauxjeuxolympiques.com/index.php    2395   \n",
       "317                http://www.theflowersofwarmovie.com/   76758   \n",
       "474                                                 NaN  330770   \n",
       "492                                                 NaN  293644   \n",
       "...                                                 ...     ...   \n",
       "4739                                                NaN   90414   \n",
       "4751                                                NaN   42109   \n",
       "4790                                                NaN   13898   \n",
       "4792                                                NaN   36095   \n",
       "4798                                                NaN    9367   \n",
       "\n",
       "                                               keywords original_language   \n",
       "97    [{\"id\": 1299, \"name\": \"monster\"}, {\"id\": 7671,...                ja  \\\n",
       "235   [{\"id\": 271, \"name\": \"competition\"}, {\"id\": 12...                fr   \n",
       "317   [{\"id\": 173251, \"name\": \"forced prostitution\"}...                zh   \n",
       "474   [{\"id\": 428, \"name\": \"nurse\"}, {\"id\": 658, \"na...                fr   \n",
       "492                      [{\"id\": 209714, \"name\": \"3d\"}]                es   \n",
       "...                                                 ...               ...   \n",
       "4739         [{\"id\": 187056, \"name\": \"woman director\"}]                fr   \n",
       "4751                                                 []                pt   \n",
       "4790                                                 []                fa   \n",
       "4792  [{\"id\": 233, \"name\": \"japan\"}, {\"id\": 549, \"na...                ja   \n",
       "4798  [{\"id\": 5616, \"name\": \"united states\\u2013mexi...                es   \n",
       "\n",
       "                          original_title   \n",
       "97                                シン・ゴジラ  \\\n",
       "235          Astérix aux Jeux Olympiques   \n",
       "317                                金陵十三釵   \n",
       "474                            Évolution   \n",
       "492   Don Gato: El inicio de la pandilla   \n",
       "...                                  ...   \n",
       "4739         I Love You, Don't Touch Me!   \n",
       "4751            Gabriela, Cravo e Canela   \n",
       "4790                               دایره   \n",
       "4792                                 キュア   \n",
       "4798                         El Mariachi   \n",
       "\n",
       "                                               overview  popularity   \n",
       "97    From the mind behind Evangelion comes a hit la...    9.476999  \\\n",
       "235   Astérix and Obélix have to win the Olympic Gam...   20.344364   \n",
       "317   A Westerner finds refuge with a group of women...   12.516546   \n",
       "474   11-year-old Nicolas lives with his mother in a...    3.300061   \n",
       "492   Top Cat has arrived to charm his way into your...    0.719996   \n",
       "...                                                 ...         ...   \n",
       "4739  The story of a 25 year old virgin girl, lookin...    0.020839   \n",
       "4751  In 1925, Gabriela becomes cook, mistress, and ...    0.557602   \n",
       "4790  Various women struggle to function in the oppr...    1.193779   \n",
       "4792  A wave of gruesome murders is sweeping Tokyo. ...    0.212443   \n",
       "4798  El Mariachi just wants to play his guitar and ...   14.269792   \n",
       "\n",
       "                                   production_companies   \n",
       "97    [{\"name\": \"Cine Bazar\", \"id\": 5896}, {\"name\": ...  \\\n",
       "235   [{\"name\": \"Constantin Film\", \"id\": 47}, {\"name...   \n",
       "317   [{\"name\": \"Beijing New Picture Film Co. Ltd.\",...   \n",
       "474   [{\"name\": \"Ex Nihilo\", \"id\": 3307}, {\"name\": \"...   \n",
       "492   [{\"name\": \"Anima Estudios\", \"id\": 9965}, {\"nam...   \n",
       "...                                                 ...   \n",
       "4739                                                 []   \n",
       "4751  [{\"name\": \"United Artists\", \"id\": 60}, {\"name\"...   \n",
       "4790  [{\"name\": \"Jafar Panahi Film Productions\", \"id...   \n",
       "4792             [{\"name\": \"Daiei Studios\", \"id\": 881}]   \n",
       "4798           [{\"name\": \"Columbia Pictures\", \"id\": 5}]   \n",
       "\n",
       "                                   production_countries release_date   \n",
       "97              [{\"iso_3166_1\": \"JP\", \"name\": \"Japan\"}]   2016-07-29  \\\n",
       "235   [{\"iso_3166_1\": \"BE\", \"name\": \"Belgium\"}, {\"is...   2008-01-13   \n",
       "317   [{\"iso_3166_1\": \"CN\", \"name\": \"China\"}, {\"iso_...   2011-12-15   \n",
       "474   [{\"iso_3166_1\": \"BE\", \"name\": \"Belgium\"}, {\"is...   2015-09-14   \n",
       "492   [{\"iso_3166_1\": \"IN\", \"name\": \"India\"}, {\"iso_...   2015-10-30   \n",
       "...                                                 ...          ...   \n",
       "4739  [{\"iso_3166_1\": \"US\", \"name\": \"United States o...   1997-01-21   \n",
       "4751           [{\"iso_3166_1\": \"BR\", \"name\": \"Brazil\"}]   1983-03-24   \n",
       "4790             [{\"iso_3166_1\": \"IR\", \"name\": \"Iran\"}]   2000-09-08   \n",
       "4792            [{\"iso_3166_1\": \"JP\", \"name\": \"Japan\"}]   1997-11-06   \n",
       "4798  [{\"iso_3166_1\": \"MX\", \"name\": \"Mexico\"}, {\"iso...   1992-09-04   \n",
       "\n",
       "        revenue  runtime                                   spoken_languages   \n",
       "97     77000000    120.0  [{\"iso_639_1\": \"it\", \"name\": \"Italiano\"}, {\"is...  \\\n",
       "235   132900000    116.0  [{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"},...   \n",
       "317    95311434    145.0  [{\"iso_639_1\": \"zh\", \"name\": \"\\u666e\\u901a\\u8b...   \n",
       "474           0     81.0     [{\"iso_639_1\": \"fr\", \"name\": \"Fran\\u00e7ais\"}]   \n",
       "492           0     89.0                                                 []   \n",
       "...         ...      ...                                                ...   \n",
       "4739          0     86.0           [{\"iso_639_1\": \"en\", \"name\": \"English\"}]   \n",
       "4751          0     99.0    [{\"iso_639_1\": \"pt\", \"name\": \"Portugu\\u00eas\"}]   \n",
       "4790          0     90.0  [{\"iso_639_1\": \"fa\", \"name\": \"\\u0641\\u0627\\u06...   \n",
       "4792      99000    111.0  [{\"iso_639_1\": \"ja\", \"name\": \"\\u65e5\\u672c\\u8a...   \n",
       "4798    2040920     81.0      [{\"iso_639_1\": \"es\", \"name\": \"Espa\\u00f1ol\"}]   \n",
       "\n",
       "        status                                            tagline   \n",
       "97    Released                    A god incarnate. A city doomed.  \\\n",
       "235   Released                                                NaN   \n",
       "317   Released                                                NaN   \n",
       "474   Released                                                NaN   \n",
       "492   Released                                                NaN   \n",
       "...        ...                                                ...   \n",
       "4739  Released  Just Your Typical Boy-Loves-Girl Who Doesn't L...   \n",
       "4751  Released                                                NaN   \n",
       "4790  Released                                                NaN   \n",
       "4792  Released                           Madness. Terror. Murder.   \n",
       "4798  Released  He didn't come looking for trouble, but troubl...   \n",
       "\n",
       "                             title  vote_average  vote_count  \n",
       "97                   Shin Godzilla           6.5         143  \n",
       "235   Asterix at the Olympic Games           5.0         471  \n",
       "317             The Flowers of War           7.1         187  \n",
       "474                      Evolution           6.4          47  \n",
       "492                 Top Cat Begins           5.3           9  \n",
       "...                            ...           ...         ...  \n",
       "4739   I Love You, Don't Touch Me!           6.0           1  \n",
       "4751                      Gabriela           6.0           2  \n",
       "4790                    The Circle           6.6          17  \n",
       "4792                          Cure           7.4          63  \n",
       "4798                   El Mariachi           6.6         238  \n",
       "\n",
       "[298 rows x 20 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Obtém todos os filmes cuja língua original NÃO é o inglês\n",
    "tmdb.query(\"original_language != 'en'\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "61ad753c-3289-4bd6-a1f4-e0ad7f221415",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "97      ja\n",
       "235     fr\n",
       "317     zh\n",
       "474     fr\n",
       "492     es\n",
       "        ..\n",
       "4739    fr\n",
       "4751    pt\n",
       "4790    fa\n",
       "4792    ja\n",
       "4798    es\n",
       "Name: original_language, Length: 298, dtype: object"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tmdb.query(\"original_language != 'en'\")['original_language']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "cbbcbc8d-038d-4a2d-8c89-f23b5a4842e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "original_language\n",
       "fr    70\n",
       "es    32\n",
       "zh    27\n",
       "de    27\n",
       "hi    19\n",
       "ja    16\n",
       "it    14\n",
       "cn    12\n",
       "ko    11\n",
       "ru    11\n",
       "pt     9\n",
       "da     7\n",
       "sv     5\n",
       "fa     4\n",
       "nl     4\n",
       "he     3\n",
       "th     3\n",
       "ro     2\n",
       "id     2\n",
       "ar     2\n",
       "cs     2\n",
       "ta     2\n",
       "tr     1\n",
       "nb     1\n",
       "af     1\n",
       "pl     1\n",
       "is     1\n",
       "hu     1\n",
       "vi     1\n",
       "ky     1\n",
       "xx     1\n",
       "te     1\n",
       "no     1\n",
       "sl     1\n",
       "ps     1\n",
       "el     1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tmdb.query(\"original_language != 'en'\")['original_language'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "6a1af3e7-78a7-45dd-9366-cfced6e69688",
   "metadata": {},
   "outputs": [],
   "source": [
    "filmes_sem_lingua_original_em_ingles = tmdb.query(\"original_language != 'en'\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "3298930f-0b5f-4b70-90ca-3964cd457026",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7f5913601610>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x='original_language', kind='count', data=filmes_sem_lingua_original_em_ingles)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "12a69e1c-e859-4270-9c9e-4e3cd287b6a9",
   "metadata": {},
   "source": [
    "Com esta visualização, notamos que há mais filmes produzidos em francês do que nas demais línguas. No entanto, os rótulos do eixo horizontal estão sobrepostos e fica díficil identificarmos as diferenças entre as categorias. É, portanto, uma boa ideia ordenarmos as barras deste gráfico em ordem decrescente a fim de que possamos identificar mais facilmente a diferença entre as categorias."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "62833216-8a90-4f9e-b7ab-07692712b6e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "original_language\n",
       "fr    70\n",
       "es    32\n",
       "zh    27\n",
       "de    27\n",
       "hi    19\n",
       "ja    16\n",
       "it    14\n",
       "cn    12\n",
       "ko    11\n",
       "ru    11\n",
       "pt     9\n",
       "da     7\n",
       "sv     5\n",
       "fa     4\n",
       "nl     4\n",
       "he     3\n",
       "th     3\n",
       "ro     2\n",
       "id     2\n",
       "ar     2\n",
       "cs     2\n",
       "ta     2\n",
       "tr     1\n",
       "nb     1\n",
       "af     1\n",
       "pl     1\n",
       "is     1\n",
       "hu     1\n",
       "vi     1\n",
       "ky     1\n",
       "xx     1\n",
       "te     1\n",
       "no     1\n",
       "sl     1\n",
       "ps     1\n",
       "el     1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "contagem_outras_linguas = tmdb.query(\"original_language != 'en'\")['original_language'].value_counts()\n",
    "contagem_outras_linguas.columns = ['original_language', 'total']\n",
    "contagem_outras_linguas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "4ae9e214-10ce-41c3-a184-8b8bc1cc0ad4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7f591332d890>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# aspect: Define um aspecto para a figura\n",
    "# Não podemos usar o plt.figure(figsize=(14,8))\n",
    "# sns.catplot é um método de alto nível\n",
    "# order: Define uma ordem para ordenar as categorias\n",
    "sns.catplot(x='original_language', kind='count', \n",
    "            data=filmes_sem_lingua_original_em_ingles,\n",
    "            palette='mako',\n",
    "            aspect=2, order=contagem_outras_linguas.index\n",
    "           )"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "41d887fc-4b3d-4a88-a57b-23f8227f5afe",
   "metadata": {},
   "source": [
    "Com esta visualização, podemos notar facilmente que há mais filmes produzidos em francês do que nas demais línguas. Além disso, podemos identificar a diferença entre as quantidades de filmes produzidos em cada língua bem facilmente."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "996d4124-8b4a-406c-9f60-364418ebeae6",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Dados e Estatística"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "cf984bf2-5cf3-457a-85d4-970232655607",
   "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>filmeId</th>\n",
       "      <th>titulo</th>\n",
       "      <th>generos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>Adventure|Animation|Children|Comedy|Fantasy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Jumanji (1995)</td>\n",
       "      <td>Adventure|Children|Fantasy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Grumpier Old Men (1995)</td>\n",
       "      <td>Comedy|Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Waiting to Exhale (1995)</td>\n",
       "      <td>Comedy|Drama|Romance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Father of the Bride Part II (1995)</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   filmeId                              titulo   \n",
       "0        1                    Toy Story (1995)  \\\n",
       "1        2                      Jumanji (1995)   \n",
       "2        3             Grumpier Old Men (1995)   \n",
       "3        4            Waiting to Exhale (1995)   \n",
       "4        5  Father of the Bride Part II (1995)   \n",
       "\n",
       "                                       generos  \n",
       "0  Adventure|Animation|Children|Comedy|Fantasy  \n",
       "1                   Adventure|Children|Fantasy  \n",
       "2                               Comedy|Romance  \n",
       "3                         Comedy|Drama|Romance  \n",
       "4                                       Comedy  "
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filmes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "7936ae8b-36c6-472e-922a-117b55ee3a21",
   "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>usuarioId</th>\n",
       "      <th>filmeId</th>\n",
       "      <th>nota</th>\n",
       "      <th>momento</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>964982703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>964981247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>964982224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>47</td>\n",
       "      <td>5.0</td>\n",
       "      <td>964983815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>5.0</td>\n",
       "      <td>964982931</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   usuarioId  filmeId  nota    momento\n",
       "0          1        1   4.0  964982703\n",
       "1          1        3   4.0  964981247\n",
       "2          1        6   4.0  964982224\n",
       "3          1       47   5.0  964983815\n",
       "4          1       50   5.0  964982931"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "notas.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "11865124-9ff9-4cad-a605-0c57ee004764",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "215 110\n"
     ]
    }
   ],
   "source": [
    "notas_do_toy_story = notas.query('filmeId == 1')\n",
    "notas_do_jumanji = notas.query('filmeId == 2')\n",
    "print(len(notas_do_toy_story), len(notas_do_jumanji))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "a64b48db-5fd5-41fc-8521-805e8f9bfe07",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nota média do Toy Story: 3.92\n",
      "Nota média do Jumanji: 3.43\n"
     ]
    }
   ],
   "source": [
    "print('Nota média do Toy Story: %.2f' % notas_do_toy_story['nota'].mean())\n",
    "print('Nota média do Jumanji: %.2f' % notas_do_jumanji['nota'].mean())"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "87eac3a4-3e1d-4988-8829-6e268e990b69",
   "metadata": {},
   "source": [
    "Com a média, não conseguimos saber quantas pessoas amaram e quantas odiaram cada filme, nem se a diferença entre o número das que amaram e das que odiaram é grande ou não."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "1b96396d-6f0e-45c9-b637-dbb0011314d5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mediana das notas do Toy Story: 4.00\n",
      "Mediana das notas do Jumanji: 3.50\n"
     ]
    }
   ],
   "source": [
    "print('Mediana das notas do Toy Story: %.2f' % notas_do_toy_story['nota'].median())\n",
    "print('Mediana das notas do Jumanji: %.2f' % notas_do_jumanji['nota'].median())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "a3fc4bc2-cfea-40a6-8c5f-2ca8a4253dd7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.boxplot([notas_do_toy_story['nota'], notas_do_jumanji['nota']])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "01100577-677b-4690-8184-cab092b6c53e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='filmeId', ylabel='nota'>"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='filmeId', y='nota', data=notas.query(\"filmeId in [1, 2, 3, 4, 5]\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "343b87ec-a7d9-4246-b949-fe659854a1c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.8348591407114047 0.8817134921476455\n"
     ]
    }
   ],
   "source": [
    "# Desvio padrão (medida que calcula o quanto os dados se desviam do padrão, isto é, de uma tendência central)\n",
    "print(notas_do_toy_story['nota'].std(), notas_do_jumanji['nota'].std())"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.3"
  },
  "toc-autonumbering": false,
  "toc-showcode": false,
  "toc-showmarkdowntxt": false,
  "toc-showtags": false
 },
 "nbformat": 4,
 "nbformat_minor": 5
}