dv-most-popular-youtube-videos.ipynb

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     "text": [
      "/kaggle/input/most-popular-1000-youtube-videos/Most popular 1000 Youtube videos.csv\n"
     ]
    }
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   "source": [
    "# This Python 3 environment comes with many helpful analytics libraries installed\n",
    "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n",
    "# For example, here's several helpful packages to load\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "# Input data files are available in the read-only \"../input/\" directory\n",
    "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
    "\n",
    "import os\n",
    "for dirname, _, filenames in os.walk('/kaggle/input'):\n",
    "    for filename in filenames:\n",
    "        print(os.path.join(dirname, filename))\n",
    "\n",
    "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n",
    "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session"
   ]
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   "outputs": [],
   "source": [
    "df = pd.read_csv(\"/kaggle/input/most-popular-1000-youtube-videos/Most popular 1000 Youtube videos.csv\")"
   ]
  },
  {
   "cell_type": "code",
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     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rank</th>\n",
       "      <th>Video</th>\n",
       "      <th>Video views</th>\n",
       "      <th>Likes</th>\n",
       "      <th>Dislikes</th>\n",
       "      <th>Category</th>\n",
       "      <th>published</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Lil Nas X - Old Town Road (Official Movie) ft....</td>\n",
       "      <td>54,071,677</td>\n",
       "      <td>3,497,955</td>\n",
       "      <td>78,799</td>\n",
       "      <td>Music</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>20 Tennis shots if they were not filmed, NOBOD...</td>\n",
       "      <td>3,471,237</td>\n",
       "      <td>19,023</td>\n",
       "      <td>859</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>JoJo Siwa - Karma (Official Video)</td>\n",
       "      <td>34,206,747</td>\n",
       "      <td>293,563</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Music</td>\n",
       "      <td>2024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>David Kushner - Daylight (Official Music Video)</td>\n",
       "      <td>18,558,390</td>\n",
       "      <td>680,732</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Music</td>\n",
       "      <td>2023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Wiz Khalifa - See You Again ft. Charlie Puth [...</td>\n",
       "      <td>6,547,981,039</td>\n",
       "      <td>44,428,537</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Music</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   rank                                              Video    Video views  \\\n",
       "0     1  Lil Nas X - Old Town Road (Official Movie) ft....     54,071,677   \n",
       "1     2  20 Tennis shots if they were not filmed, NOBOD...      3,471,237   \n",
       "2     3                 JoJo Siwa - Karma (Official Video)     34,206,747   \n",
       "3     4    David Kushner - Daylight (Official Music Video)     18,558,390   \n",
       "4     5  Wiz Khalifa - See You Again ft. Charlie Puth [...  6,547,981,039   \n",
       "\n",
       "        Likes Dislikes Category  published  \n",
       "0   3,497,955   78,799    Music       2019  \n",
       "1      19,023      859      NaN       2017  \n",
       "2     293,563      NaN    Music       2024  \n",
       "3     680,732      NaN    Music       2023  \n",
       "4  44,428,537      NaN    Music       2015  "
      ]
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   "source": [
    "df.head()"
   ]
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     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 7 columns):\n",
      " #   Column       Non-Null Count  Dtype \n",
      "---  ------       --------------  ----- \n",
      " 0   rank         1000 non-null   int64 \n",
      " 1   Video        1000 non-null   object\n",
      " 2   Video views  1000 non-null   object\n",
      " 3   Likes        1000 non-null   object\n",
      " 4   Dislikes     527 non-null    object\n",
      " 5   Category     982 non-null    object\n",
      " 6   published    1000 non-null   int64 \n",
      "dtypes: int64(2), object(5)\n",
      "memory usage: 54.8+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
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    {
     "data": {
      "text/plain": [
       "rank             0\n",
       "Video            0\n",
       "Video views      0\n",
       "Likes            0\n",
       "Dislikes       473\n",
       "Category        18\n",
       "published        0\n",
       "dtype: int64"
      ]
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   "source": [
    "df.isnull().sum()"
   ]
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   "id": "1fb1d9e1",
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    {
     "data": {
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       "  <thead>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>500.500000</td>\n",
       "      <td>2019.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>288.819436</td>\n",
       "      <td>5.384328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>2005.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>250.750000</td>\n",
       "      <td>2017.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>500.500000</td>\n",
       "      <td>2021.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>750.250000</td>\n",
       "      <td>2024.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>2025.000000</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "              rank    published\n",
       "count  1000.000000  1000.000000\n",
       "mean    500.500000  2019.100000\n",
       "std     288.819436     5.384328\n",
       "min       1.000000  2005.000000\n",
       "25%     250.750000  2017.000000\n",
       "50%     500.500000  2021.000000\n",
       "75%     750.250000  2024.000000\n",
       "max    1000.000000  2025.000000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "928c3012",
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    "tags": []
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   "source": [
    "**A razão de não termos outros elementos é por conta do formato deles, como a maior parte está como object não conseguimos ter informações estatísticas. Vamos precisar fazer uma *limpeza* nos dados fornecidos**"
   ]
  },
  {
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   "id": "5c695288",
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    "tags": []
   },
   "source": [
    "# Limpando os dados"
   ]
  },
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   "id": "e05092d0",
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   },
   "outputs": [],
   "source": [
    "# 1. Remover separadores de milhar e converter para numérico as colunas 'Video views', 'Likes' e 'Dislikes'\n",
    "# Vamos remover qualquer vírgula ou ponto e depois converter para int.\n",
    "\n",
    "col_limp = ['Video views', 'Likes', 'Dislikes']\n",
    "for coluna in col_limp:\n",
    "    df[coluna] = df[coluna].replace(',', '', regex=True)\n",
    "\n",
    "# Convertendo para valores numéricos\n",
    "col_num = ['Video views', 'Likes', 'Dislikes']\n",
    "for coluna in col_num:\n",
    "    df[coluna] = pd.to_numeric(df[coluna], errors='coerce')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
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    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# 2. Preencher valores ausentes da coluna 'Category' com \"desconhecido\"\n",
    "df['Category'] = df['Category'].fillna('desconhecido')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6a0920a4",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   rank                                              Video  Video views  \\\n",
      "0     1  Lil Nas X - Old Town Road (Official Movie) ft....     54071677   \n",
      "1     2  20 Tennis shots if they were not filmed, NOBOD...      3471237   \n",
      "2     3                 JoJo Siwa - Karma (Official Video)     34206747   \n",
      "3     4    David Kushner - Daylight (Official Music Video)     18558390   \n",
      "4     5  Wiz Khalifa - See You Again ft. Charlie Puth [...   6547981039   \n",
      "\n",
      "      Likes  Dislikes      Category  published  \n",
      "0   3497955   78799.0         Music       2019  \n",
      "1     19023     859.0  desconhecido       2017  \n",
      "2    293563       0.0         Music       2024  \n",
      "3    680732       0.0         Music       2023  \n",
      "4  44428537       0.0         Music       2015  \n"
     ]
    }
   ],
   "source": [
    "# 3. Tratamento para a coluna 'Dislikes':\n",
    "# Vamos preencher os valores faltantes da coluna 'Dislikes' com 0, caso deseje.\n",
    "# Caso prefira outro valor (como a mediana ou a média), é só ajustar.\n",
    "\n",
    "df['Dislikes'] = df['Dislikes'].fillna(0)\n",
    "\n",
    "# Exibindo o DataFrame atualizado\n",
    "print(df.head())\n"
   ]
  },
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    "tags": []
   },
   "source": [
    "# Analise exploratória"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e252a841",
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       "      <th></th>\n",
       "      <th>rank</th>\n",
       "      <th>Video views</th>\n",
       "      <th>Likes</th>\n",
       "      <th>Dislikes</th>\n",
       "      <th>published</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1.000000e+03</td>\n",
       "      <td>1.000000e+03</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>500.500000</td>\n",
       "      <td>2.453435e+07</td>\n",
       "      <td>3.685451e+05</td>\n",
       "      <td>1223.865000</td>\n",
       "      <td>2019.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>288.819436</td>\n",
       "      <td>2.512570e+08</td>\n",
       "      <td>1.629418e+06</td>\n",
       "      <td>7099.957793</td>\n",
       "      <td>5.384328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.493900e+04</td>\n",
       "      <td>4.330000e+02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2005.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>250.750000</td>\n",
       "      <td>9.815690e+05</td>\n",
       "      <td>9.427250e+03</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2017.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>500.500000</td>\n",
       "      <td>2.341652e+06</td>\n",
       "      <td>3.026200e+04</td>\n",
       "      <td>57.000000</td>\n",
       "      <td>2021.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>750.250000</td>\n",
       "      <td>1.162638e+07</td>\n",
       "      <td>1.649858e+05</td>\n",
       "      <td>523.250000</td>\n",
       "      <td>2024.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>6.547981e+09</td>\n",
       "      <td>4.442854e+07</td>\n",
       "      <td>178042.000000</td>\n",
       "      <td>2025.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              rank   Video views         Likes       Dislikes    published\n",
       "count  1000.000000  1.000000e+03  1.000000e+03    1000.000000  1000.000000\n",
       "mean    500.500000  2.453435e+07  3.685451e+05    1223.865000  2019.100000\n",
       "std     288.819436  2.512570e+08  1.629418e+06    7099.957793     5.384328\n",
       "min       1.000000  4.493900e+04  4.330000e+02       0.000000  2005.000000\n",
       "25%     250.750000  9.815690e+05  9.427250e+03       0.000000  2017.000000\n",
       "50%     500.500000  2.341652e+06  3.026200e+04      57.000000  2021.000000\n",
       "75%     750.250000  1.162638e+07  1.649858e+05     523.250000  2024.000000\n",
       "max    1000.000000  6.547981e+09  4.442854e+07  178042.000000  2025.000000"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9d991369",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-02-09T17:34:10.593419Z",
     "iopub.status.busy": "2025-02-09T17:34:10.593098Z",
     "iopub.status.idle": "2025-02-09T17:34:10.597139Z",
     "shell.execute_reply": "2025-02-09T17:34:10.596124Z"
    },
    "papermill": {
     "duration": 0.011453,
     "end_time": "2025-02-09T17:34:10.598936",
     "exception": false,
     "start_time": "2025-02-09T17:34:10.587483",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "sns.set_style(\"whitegrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "59f941c6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-02-09T17:34:10.610101Z",
     "iopub.status.busy": "2025-02-09T17:34:10.609734Z",
     "iopub.status.idle": "2025-02-09T17:34:11.738600Z",
     "shell.execute_reply": "2025-02-09T17:34:11.737229Z"
    },
    "papermill": {
     "duration": 1.136594,
     "end_time": "2025-02-09T17:34:11.740502",
     "exception": false,
     "start_time": "2025-02-09T17:34:10.603908",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Distribuição de colunas númericas(histograma)\n",
    "col_numericas = ['Likes', 'Dislikes', 'published']\n",
    "for col in col_numericas:\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    sns.histplot(df[col].dropna(), kde=True, bins=30, color=plt.cm.viridis(0.8))\n",
    "    plt.title(f'Distribution of {col}')\n",
    "    plt.xlabel(f'{col}')\n",
    "    plt.ylabel('Frequencia')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2129c60d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-02-09T17:34:11.755880Z",
     "iopub.status.busy": "2025-02-09T17:34:11.755521Z",
     "iopub.status.idle": "2025-02-09T17:34:12.126578Z",
     "shell.execute_reply": "2025-02-09T17:34:12.125256Z"
    },
    "papermill": {
     "duration": 0.38067,
     "end_time": "2025-02-09T17:34:12.128507",
     "exception": false,
     "start_time": "2025-02-09T17:34:11.747837",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Gráfico de Contagem para Categorias\n",
    "plt.figure(figsize=(12, 6))\n",
    "sns.countplot(data=df, x='Category', order=df['Category'].value_counts().index, palette='viridis')\n",
    "plt.title('Número de Vídeos por Categoria')\n",
    "plt.xlabel('Categoria')\n",
    "plt.ylabel('Contagem')\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "510fbe2e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-02-09T17:34:12.146506Z",
     "iopub.status.busy": "2025-02-09T17:34:12.146117Z",
     "iopub.status.idle": "2025-02-09T17:34:12.157016Z",
     "shell.execute_reply": "2025-02-09T17:34:12.156036Z"
    },
    "papermill": {
     "duration": 0.02147,
     "end_time": "2025-02-09T17:34:12.158648",
     "exception": false,
     "start_time": "2025-02-09T17:34:12.137178",
     "status": "completed"
    },
    "tags": []
   },
   "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>Category</th>\n",
       "      <th>Frequencia</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Music</td>\n",
       "      <td>431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>People &amp; Blogs</td>\n",
       "      <td>257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Entertainment</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Comedy</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Sports</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Film &amp; Animation</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Gaming</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Autos &amp; Vehicles</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>desconhecido</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Pets &amp; Animals</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>News &amp; Politics</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Education</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Science &amp; Technology</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Nonprofits &amp; Activism</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Travel &amp; Events</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Howto &amp; Style</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Category  Frequencia\n",
       "0                   Music         431\n",
       "1          People & Blogs         257\n",
       "2           Entertainment          81\n",
       "3                  Comedy          53\n",
       "4                  Sports          35\n",
       "5        Film & Animation          29\n",
       "6                  Gaming          22\n",
       "7        Autos & Vehicles          19\n",
       "8            desconhecido          18\n",
       "9          Pets & Animals          18\n",
       "10        News & Politics          14\n",
       "11              Education           5\n",
       "12   Science & Technology           5\n",
       "13  Nonprofits & Activism           5\n",
       "14        Travel & Events           4\n",
       "15          Howto & Style           4"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qtd = df['Category'].value_counts().reset_index(name='Frequencia')\n",
    "qtd.columns = ['Category', 'Frequencia']\n",
    "qtd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f3270523",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-02-09T17:34:12.177065Z",
     "iopub.status.busy": "2025-02-09T17:34:12.176681Z",
     "iopub.status.idle": "2025-02-09T17:34:12.190265Z",
     "shell.execute_reply": "2025-02-09T17:34:12.189189Z"
    },
    "papermill": {
     "duration": 0.024561,
     "end_time": "2025-02-09T17:34:12.192053",
     "exception": false,
     "start_time": "2025-02-09T17:34:12.167492",
     "status": "completed"
    },
    "tags": []
   },
   "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>Video</th>\n",
       "      <th>Likes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Wiz Khalifa - See You Again ft. Charlie Puth [...</td>\n",
       "      <td>44428537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Pedro Capó, Farruko - Calma (Remix - Official ...</td>\n",
       "      <td>13755637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>ROSALÍA, J Balvin - Con Altura (Official Video...</td>\n",
       "      <td>9768545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>6ix9ine - FEFE ft. Nicki Minaj, Murda Beatz</td>\n",
       "      <td>9015394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381</th>\n",
       "      <td>Jhay Cortez, J. Balvin, Bad Bunny - No Me Cono...</td>\n",
       "      <td>6622023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>278</th>\n",
       "      <td>0 Sharpness knife test?💀</td>\n",
       "      <td>4702361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Olivia Rodrigo - drivers license (Official Video)</td>\n",
       "      <td>3810456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>A disabled duckling helps his cat friend 🐥 #Du...</td>\n",
       "      <td>3749872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Lil Nas X - Old Town Road (Official Movie) ft....</td>\n",
       "      <td>3497955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>Could you do it faster?</td>\n",
       "      <td>3470844</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 Video     Likes\n",
       "4    Wiz Khalifa - See You Again ft. Charlie Puth [...  44428537\n",
       "60   Pedro Capó, Farruko - Calma (Remix - Official ...  13755637\n",
       "136  ROSALÍA, J Balvin - Con Altura (Official Video...   9768545\n",
       "31         6ix9ine - FEFE ft. Nicki Minaj, Murda Beatz   9015394\n",
       "381  Jhay Cortez, J. Balvin, Bad Bunny - No Me Cono...   6622023\n",
       "278                           0 Sharpness knife test?💀   4702361\n",
       "25   Olivia Rodrigo - drivers license (Official Video)   3810456\n",
       "192  A disabled duckling helps his cat friend 🐥 #Du...   3749872\n",
       "0    Lil Nas X - Old Town Road (Official Movie) ft....   3497955\n",
       "363                            Could you do it faster?   3470844"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convertendo a coluna 'Likes' para numérico, se necessário\n",
    "df['Likes'] = pd.to_numeric(df['Likes'], errors='coerce')\n",
    "\n",
    "# Ordenando os vídeos pelos valores de 'Likes' em ordem decrescente e selecionando os 10 maiores\n",
    "top_likes = df.sort_values(by='Likes', ascending=False).head(10)\n",
    "\n",
    "# Exibindo os 10 vídeos com mais likes\n",
    "top_likes[['Video', 'Likes']]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a0619cab",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-02-09T17:34:12.211806Z",
     "iopub.status.busy": "2025-02-09T17:34:12.211428Z",
     "iopub.status.idle": "2025-02-09T17:34:12.622934Z",
     "shell.execute_reply": "2025-02-09T17:34:12.621957Z"
    },
    "papermill": {
     "duration": 0.423249,
     "end_time": "2025-02-09T17:34:12.624810",
     "exception": false,
     "start_time": "2025-02-09T17:34:12.201561",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Criando o gráfico de barras\n",
    "plt.figure(figsize=(20, 10))  # Ajuste o tamanho do gráfico\n",
    "sns.barplot(x='Likes', y='Video', data=top_likes, palette='viridis')\n",
    "\n",
    "# Títulos e rótulos\n",
    "plt.title('Top 10 Vídeos com Mais Likes (1e7)', fontsize=16)\n",
    "plt.xlabel('Número de Likes', fontsize=14)\n",
    "plt.ylabel('Vídeos', fontsize=14)\n",
    "\n",
    "# Exibindo o gráfico\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kaggle": {
   "accelerator": "none",
   "dataSources": [
    {
     "datasetId": 6558249,
     "sourceId": 10595769,
     "sourceType": "datasetVersion"
    }
   ],
   "dockerImageVersionId": 30886,
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