PRACTICE ASSIGMENT.ipynb

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      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "season=pd.read_csv(\"/content/deliveries.csv\")\n",
        "season"
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              "       match_id  season  start_date                                  venue  \\\n",
              "0             1    2024  2024-06-02             Providence Stadium, Guyana   \n",
              "1             1    2024  2024-06-02             Providence Stadium, Guyana   \n",
              "2             1    2024  2024-06-02             Providence Stadium, Guyana   \n",
              "3             1    2024  2024-06-02             Providence Stadium, Guyana   \n",
              "4             1    2024  2024-06-02             Providence Stadium, Guyana   \n",
              "...         ...     ...         ...                                    ...   \n",
              "11467        54    2024  2024-06-29  Kensington Oval, Bridgetown, Barbados   \n",
              "11468        54    2024  2024-06-29  Kensington Oval, Bridgetown, Barbados   \n",
              "11469        54    2024  2024-06-29  Kensington Oval, Bridgetown, Barbados   \n",
              "11470        54    2024  2024-06-29  Kensington Oval, Bridgetown, Barbados   \n",
              "11471        54    2024  2024-06-29  Kensington Oval, Bridgetown, Barbados   \n",
              "\n",
              "       innings  ball      batting_team bowling_team     striker non_striker  \\\n",
              "0            1   0.1  Papua New Guinea  West Indies      TP Ura      A Vala   \n",
              "1            1   0.2  Papua New Guinea  West Indies      TP Ura      A Vala   \n",
              "2            1   0.3  Papua New Guinea  West Indies      A Vala      TP Ura   \n",
              "3            1   0.4  Papua New Guinea  West Indies      A Vala      TP Ura   \n",
              "4            1   0.5  Papua New Guinea  West Indies      A Vala      TP Ura   \n",
              "...        ...   ...               ...          ...         ...         ...   \n",
              "11467        2  19.3      South Africa        India    K Rabada  KA Maharaj   \n",
              "11468        2  19.4      South Africa        India  KA Maharaj    K Rabada   \n",
              "11469        2  19.5      South Africa        India    K Rabada  KA Maharaj   \n",
              "11470        2  19.6      South Africa        India    K Rabada  KA Maharaj   \n",
              "11471        2  19.7      South Africa        India    A Nortje  KA Maharaj   \n",
              "\n",
              "       ... extras  wides  noballs  byes  legbyes  penalty  wicket_type  \\\n",
              "0      ...      0    NaN      NaN   NaN      NaN      NaN          NaN   \n",
              "1      ...      0    NaN      NaN   NaN      NaN      NaN          NaN   \n",
              "2      ...      0    NaN      NaN   NaN      NaN      NaN          NaN   \n",
              "3      ...      0    NaN      NaN   NaN      NaN      NaN          NaN   \n",
              "4      ...      0    NaN      NaN   NaN      NaN      NaN          NaN   \n",
              "...    ...    ...    ...      ...   ...      ...      ...          ...   \n",
              "11467  ...      1    NaN      NaN   1.0      NaN      NaN          NaN   \n",
              "11468  ...      1    NaN      NaN   NaN      1.0      NaN          NaN   \n",
              "11469  ...      1    1.0      NaN   NaN      NaN      NaN          NaN   \n",
              "11470  ...      0    NaN      NaN   NaN      NaN      NaN       caught   \n",
              "11471  ...      0    NaN      NaN   NaN      NaN      NaN          NaN   \n",
              "\n",
              "       player_dismissed other_wicket_type other_player_dismissed  \n",
              "0                   NaN               NaN                    NaN  \n",
              "1                   NaN               NaN                    NaN  \n",
              "2                   NaN               NaN                    NaN  \n",
              "3                   NaN               NaN                    NaN  \n",
              "4                   NaN               NaN                    NaN  \n",
              "...                 ...               ...                    ...  \n",
              "11467               NaN               NaN                    NaN  \n",
              "11468               NaN               NaN                    NaN  \n",
              "11469               NaN               NaN                    NaN  \n",
              "11470          K Rabada               NaN                    NaN  \n",
              "11471               NaN               NaN                    NaN  \n",
              "\n",
              "[11472 rows x 22 columns]"
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              "      <td>0.3</td>\n",
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              "      <td>Kensington Oval, Bridgetown, Barbados</td>\n",
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              "      <td>19.3</td>\n",
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              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-2c84e967-3d17-4afc-97e4-2c5f3a493973 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_ea61c7d0-6909-414e-8b9d-e7fd80cebad2\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('season')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_ea61c7d0-6909-414e-8b9d-e7fd80cebad2 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('season');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "season"
            }
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "season.plot(y='season',x='start_date')\n",
        "season.plot(y=['season','venue'], x='start_date')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 901
        },
        "id": "SJCULRDkaQMU",
        "outputId": "9d69820d-ae63-41ac-9d10-aa3c692382c4"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='start_date'>"
            ]
          },
          "metadata": {},
          "execution_count": 17
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "season.plot.bar(y='season', x='start_date')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 534
        },
        "id": "p3X6buercjVu",
        "outputId": "fce2813b-778d-492e-e6cf-d702b8cd7a9b"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='start_date'>"
            ]
          },
          "metadata": {},
          "execution_count": 18
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "season.plot.scatter(y='match_id', x='start_date')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 468
        },
        "id": "At_PrKsFdFMk",
        "outputId": "5f07e349-d256-4fce-acfe-d98ba1d154cd"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='start_date', ylabel='match_id'>"
            ]
          },
          "metadata": {},
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Data set of heros\n",
        "mostviewer=pd.read_csv('/content/critic_reviews.csv')\n",
        "mostviewer"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 964
        },
        "id": "ZMvgPOlqfkDp",
        "outputId": "91b6fa0b-0d8c-4391-ab2e-cd165f42623a"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        reviewId creationDate          criticName  \\\n",
              "0        1912176   1966-07-30      Jennie Kermode   \n",
              "1        1895073   1998-08-21          Scott Nash   \n",
              "2          25507   2000-01-01         Roger Ebert   \n",
              "3          25508   2000-01-01                 NaN   \n",
              "4          25509   2000-01-01           Joe Brown   \n",
              "...          ...          ...                 ...   \n",
              "27137  102921224   2024-06-14          Mat Brunet   \n",
              "27138  102921566   2024-06-15         Josh Larsen   \n",
              "27139  102921714   2024-06-17         Casey Chong   \n",
              "27140  102923356   2024-06-24  Udita Jhunjhunwala   \n",
              "27141  102923418   2024-06-24  Udita Jhunjhunwala   \n",
              "\n",
              "                     criticPageUrl reviewState  isFresh  isRotten isRtUrl  \\\n",
              "0          /critics/jennie-kermode       fresh     True     False   False   \n",
              "1              /critics/scott-nash       fresh     True     False   False   \n",
              "2             /critics/roger-ebert       fresh     True     False   False   \n",
              "3                              NaN      rotten    False      True   False   \n",
              "4               /critics/joe-brown       fresh     True     False   False   \n",
              "...                            ...         ...      ...       ...     ...   \n",
              "27137          /critics/mat-brunet       fresh     True     False   False   \n",
              "27138         /critics/josh-larsen       fresh     True     False   False   \n",
              "27139         /critics/casey-chong       fresh     True     False   False   \n",
              "27140  /critics/udita-jhunjhunwala       fresh     True     False   False   \n",
              "27141  /critics/udita-jhunjhunwala      rotten    False      True   False   \n",
              "\n",
              "       isTopCritic             publicationUrl            publicationName  \\\n",
              "0            False       /critics/source/1869               Eye for Film   \n",
              "1            False       /critics/source/1465          Three Movie Buffs   \n",
              "2             True         /critics/source/67          Chicago Sun-Times   \n",
              "3             True        /critics/source/148            Empire Magazine   \n",
              "4             True        /critics/source/474            Washington Post   \n",
              "...            ...                        ...                        ...   \n",
              "27137        False  /critics/source/100009579  AniMat's Review (YouTube)   \n",
              "27138        False       /critics/source/1959               LarsenOnFilm   \n",
              "27139        False       /critics/source/3688        Casey's Movie Mania   \n",
              "27140         True       /critics/source/2785                   Livemint   \n",
              "27141         True       /critics/source/2785                   Livemint   \n",
              "\n",
              "                                               reviewUrl  \\\n",
              "0        http://www.eyeforfilm.co.uk/reviews.php?id=7898   \n",
              "1            http://www.threemoviebuffs.com/review/blade   \n",
              "2      http://www.rogerebert.com/reviews/the-rocketee...   \n",
              "3      http://www.empireonline.com/reviews/reviewcomp...   \n",
              "4      http://www.washingtonpost.com/wp-srv/style/lon...   \n",
              "...                                                  ...   \n",
              "27137                       https://youtu.be/ckNJciq0XUM   \n",
              "27138                  https://larsenonfilm.com/the-crow   \n",
              "27139  https://www.caseymoviemania.com/batman-honey-i...   \n",
              "27140  https://lifestyle.livemint.com/how-to-lounge/m...   \n",
              "27141  https://lifestyle.livemint.com/how-to-lounge/m...   \n",
              "\n",
              "                                                   quote scoreSentiment  \\\n",
              "0                                                    NaN       POSITIVE   \n",
              "1      It's stylish and fast-paced. It's also a lot o...       POSITIVE   \n",
              "2      You have to dial down, to return to an age of ...       POSITIVE   \n",
              "3            Reaches for the skies but runs out of fuel.       NEGATIVE   \n",
              "4      Based on a comic book, deliciously corny but n...       POSITIVE   \n",
              "...                                                  ...            ...   \n",
              "27137  I know this is meant to show the first time th...       POSITIVE   \n",
              "27138  &#46;&#46;&#46; dark&#44; rainy&#44; and askew...       POSITIVE   \n",
              "27139  Jack Nicholson&#44; who received top billing a...       POSITIVE   \n",
              "27140  Unlike the more recent superhero movies that a...       POSITIVE   \n",
              "27141  For a film about a very fast man, the narrativ...       NEGATIVE   \n",
              "\n",
              "      originalScore                               movieId  \n",
              "0               4/5  7602d2ab-c9bc-3439-9cd6-d3a06e81728e  \n",
              "1               3/4  4128b2f6-8c69-396a-a83d-0d44eb90e5f7  \n",
              "2               3/4  01935e47-e735-30c3-b8bd-72a9dbbcfa8a  \n",
              "3               2/5  01935e47-e735-30c3-b8bd-72a9dbbcfa8a  \n",
              "4               NaN  01935e47-e735-30c3-b8bd-72a9dbbcfa8a  \n",
              "...             ...                                   ...  \n",
              "27137          6/10  e53e6850-82b5-3727-a768-d99df185a901  \n",
              "27138           3/4  da04703c-b0d8-3dee-8910-bc1387164fc1  \n",
              "27139         3.5/5  f6f45d63-ea78-3139-985f-e5dc17caf85e  \n",
              "27140           NaN  10b522a5-873e-3e15-bd8b-65a079ab0b09  \n",
              "27141           NaN  7807e2b5-72d7-3dc7-8cd4-b9482b82fe01  \n",
              "\n",
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              "      <th>reviewId</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1912176</td>\n",
              "      <td>1966-07-30</td>\n",
              "      <td>Jennie Kermode</td>\n",
              "      <td>/critics/jennie-kermode</td>\n",
              "      <td>fresh</td>\n",
              "      <td>True</td>\n",
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              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>/critics/source/1869</td>\n",
              "      <td>Eye for Film</td>\n",
              "      <td>http://www.eyeforfilm.co.uk/reviews.php?id=7898</td>\n",
              "      <td>NaN</td>\n",
              "      <td>POSITIVE</td>\n",
              "      <td>4/5</td>\n",
              "      <td>7602d2ab-c9bc-3439-9cd6-d3a06e81728e</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1895073</td>\n",
              "      <td>1998-08-21</td>\n",
              "      <td>Scott Nash</td>\n",
              "      <td>/critics/scott-nash</td>\n",
              "      <td>fresh</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>/critics/source/1465</td>\n",
              "      <td>Three Movie Buffs</td>\n",
              "      <td>http://www.threemoviebuffs.com/review/blade</td>\n",
              "      <td>It's stylish and fast-paced. It's also a lot o...</td>\n",
              "      <td>POSITIVE</td>\n",
              "      <td>3/4</td>\n",
              "      <td>4128b2f6-8c69-396a-a83d-0d44eb90e5f7</td>\n",
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              "      <th>2</th>\n",
              "      <td>25507</td>\n",
              "      <td>2000-01-01</td>\n",
              "      <td>Roger Ebert</td>\n",
              "      <td>/critics/roger-ebert</td>\n",
              "      <td>fresh</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>/critics/source/67</td>\n",
              "      <td>Chicago Sun-Times</td>\n",
              "      <td>http://www.rogerebert.com/reviews/the-rocketee...</td>\n",
              "      <td>You have to dial down, to return to an age of ...</td>\n",
              "      <td>POSITIVE</td>\n",
              "      <td>3/4</td>\n",
              "      <td>01935e47-e735-30c3-b8bd-72a9dbbcfa8a</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>25508</td>\n",
              "      <td>2000-01-01</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>rotten</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>/critics/source/148</td>\n",
              "      <td>Empire Magazine</td>\n",
              "      <td>http://www.empireonline.com/reviews/reviewcomp...</td>\n",
              "      <td>Reaches for the skies but runs out of fuel.</td>\n",
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              "      <td>2/5</td>\n",
              "      <td>01935e47-e735-30c3-b8bd-72a9dbbcfa8a</td>\n",
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              "      <th>4</th>\n",
              "      <td>25509</td>\n",
              "      <td>2000-01-01</td>\n",
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              "      <td>True</td>\n",
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              "      <td>False</td>\n",
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              "      <td>/critics/source/474</td>\n",
              "      <td>Washington Post</td>\n",
              "      <td>http://www.washingtonpost.com/wp-srv/style/lon...</td>\n",
              "      <td>Based on a comic book, deliciously corny but n...</td>\n",
              "      <td>POSITIVE</td>\n",
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              "      <th>...</th>\n",
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              "      <td>...</td>\n",
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              "      <td>102921224</td>\n",
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              "      <td>102921566</td>\n",
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              "      <td>102921714</td>\n",
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              "      --bg-color: #E8F0FE;\n",
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "\n",
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              "      const quickchartButtonEl =\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
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              "\n",
              "  <div id=\"id_5780d3c9-c0b9-494c-99fd-b6bed27c9877\">\n",
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              "\n",
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              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "      [theme=dark] .colab-df-generate {\n",
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              "        fill: #D2E3FC;\n",
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              "      [theme=dark] .colab-df-generate:hover {\n",
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              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('mostviewer')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "      buttonEl.onclick = () => {\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "mostviewer",
              "summary": "{\n  \"name\": \"mostviewer\",\n  \"rows\": 27142,\n  \"fields\": [\n    {\n      \"column\": \"reviewId\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 34939631,\n        \"min\": 1705,\n        \"max\": 102923418,\n        \"num_unique_values\": 27142,\n        \"samples\": [\n          2581308,\n          2566368,\n          2827825\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"creationDate\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 4016,\n        \"samples\": [\n          \"2010-04-01\",\n          \"2011-01-05\",\n          \"2019-03-10\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"criticName\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3111,\n        \"samples\": [\n          \"Peter T. Chattaway\",\n          \"Oliver Jones\",\n          \"David Forsmark\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"criticPageUrl\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3116,\n        \"samples\": [\n          \"/critics/dave-calhoun\",\n          \"/critics/nikki-baughan\",\n          \"/critics/david-chute\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"reviewState\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"rotten\",\n          \"fresh\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"isFresh\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          false,\n          true\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"isRotten\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          true,\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"isRtUrl\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          true,\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"isTopCritic\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          true,\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"publicationUrl\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1755,\n        \"samples\": [\n          \"/critics/source/823\",\n          \"/critics/source/100009552\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"publicationName\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1755,\n        \"samples\": [\n          \"Times (UK)\",\n          \"Crum on Showbiz\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"reviewUrl\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 24726,\n        \"samples\": [\n          \"http://denersteinunleashed.blogspot.com/2019/04/a-juvenile-shazam-has-its-virtues.html\",\n          \"http://www.cnn.com/2017/06/01/entertainment/wonder-woman-review/index.html\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"quote\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 26946,\n        \"samples\": [\n          \"A pulsing, wooshing, visceral experience that amounts to great fun and an entirely disposable movie.\",\n          \"...doesn't have the emotional involvement of the best of sci-fi action films, but it's a thrashing good big dipper ride and the 3D actually works...\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"scoreSentiment\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"NEGATIVE\",\n          \"POSITIVE\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"originalScore\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 309,\n        \"samples\": [\n          \"B \",\n          \"3.5/4\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"movieId\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 100,\n        \"samples\": [\n          \"78566114-a33b-3c58-8a31-42bdb19ec6bd\",\n          \"1ce8792a-fb45-3bd8-a726-22005f03e075\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# This is the head cuted data\n",
        "mostviewer.head(2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 306
        },
        "id": "dKnkDCNlgUBt",
        "outputId": "afad2cb4-24f0-4fc9-99ad-492ba0294eb1"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   reviewId creationDate      criticName            criticPageUrl reviewState  \\\n",
              "0   1912176   1966-07-30  Jennie Kermode  /critics/jennie-kermode       fresh   \n",
              "1   1895073   1998-08-21      Scott Nash      /critics/scott-nash       fresh   \n",
              "\n",
              "   isFresh  isRotten isRtUrl  isTopCritic        publicationUrl  \\\n",
              "0     True     False   False        False  /critics/source/1869   \n",
              "1     True     False   False        False  /critics/source/1465   \n",
              "\n",
              "     publicationName                                        reviewUrl  \\\n",
              "0       Eye for Film  http://www.eyeforfilm.co.uk/reviews.php?id=7898   \n",
              "1  Three Movie Buffs      http://www.threemoviebuffs.com/review/blade   \n",
              "\n",
              "                                               quote scoreSentiment  \\\n",
              "0                                                NaN       POSITIVE   \n",
              "1  It's stylish and fast-paced. It's also a lot o...       POSITIVE   \n",
              "\n",
              "  originalScore                               movieId  \n",
              "0           4/5  7602d2ab-c9bc-3439-9cd6-d3a06e81728e  \n",
              "1           3/4  4128b2f6-8c69-396a-a83d-0d44eb90e5f7  "
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              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
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              "\n",
              "  .colab-df-spinner {\n",
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              "\n",
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              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
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              "        document.querySelector('#df-1894c378-59d0-4a2c-9327-40f11bd1bffe button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "mostviewer",
              "summary": "{\n  \"name\": \"mostviewer\",\n  \"rows\": 27142,\n  \"fields\": [\n    {\n      \"column\": \"reviewId\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 34939631,\n        \"min\": 1705,\n        \"max\": 102923418,\n        \"num_unique_values\": 27142,\n        \"samples\": [\n          2581308,\n          2566368,\n          2827825\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"creationDate\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 4016,\n        \"samples\": [\n          \"2010-04-01\",\n          \"2011-01-05\",\n          \"2019-03-10\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"criticName\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3111,\n        \"samples\": [\n          \"Peter T. Chattaway\",\n          \"Oliver Jones\",\n          \"David Forsmark\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"criticPageUrl\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3116,\n        \"samples\": [\n          \"/critics/dave-calhoun\",\n          \"/critics/nikki-baughan\",\n          \"/critics/david-chute\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"reviewState\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"rotten\",\n          \"fresh\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"isFresh\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          false,\n          true\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"isRotten\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          true,\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"isRtUrl\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          true,\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"isTopCritic\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          true,\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"publicationUrl\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1755,\n        \"samples\": [\n          \"/critics/source/823\",\n          \"/critics/source/100009552\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"publicationName\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1755,\n        \"samples\": [\n          \"Times (UK)\",\n          \"Crum on Showbiz\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"reviewUrl\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 24726,\n        \"samples\": [\n          \"http://denersteinunleashed.blogspot.com/2019/04/a-juvenile-shazam-has-its-virtues.html\",\n          \"http://www.cnn.com/2017/06/01/entertainment/wonder-woman-review/index.html\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"quote\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 26946,\n        \"samples\": [\n          \"A pulsing, wooshing, visceral experience that amounts to great fun and an entirely disposable movie.\",\n          \"...doesn't have the emotional involvement of the best of sci-fi action films, but it's a thrashing good big dipper ride and the 3D actually works...\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"scoreSentiment\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"NEGATIVE\",\n          \"POSITIVE\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"originalScore\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 309,\n        \"samples\": [\n          \"B \",\n          \"3.5/4\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"movieId\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 100,\n        \"samples\": [\n          \"78566114-a33b-3c58-8a31-42bdb19ec6bd\",\n          \"1ce8792a-fb45-3bd8-a726-22005f03e075\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# This is the Tail cuted data\n",
        "mostviewer.tail(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 486
        },
        "id": "ZoP1QNzhgv2T",
        "outputId": "3bdecec8-aa94-4556-f115-fb1f33945ed0"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        reviewId creationDate          criticName  \\\n",
              "27137  102921224   2024-06-14          Mat Brunet   \n",
              "27138  102921566   2024-06-15         Josh Larsen   \n",
              "27139  102921714   2024-06-17         Casey Chong   \n",
              "27140  102923356   2024-06-24  Udita Jhunjhunwala   \n",
              "27141  102923418   2024-06-24  Udita Jhunjhunwala   \n",
              "\n",
              "                     criticPageUrl reviewState  isFresh  isRotten isRtUrl  \\\n",
              "27137          /critics/mat-brunet       fresh     True     False   False   \n",
              "27138         /critics/josh-larsen       fresh     True     False   False   \n",
              "27139         /critics/casey-chong       fresh     True     False   False   \n",
              "27140  /critics/udita-jhunjhunwala       fresh     True     False   False   \n",
              "27141  /critics/udita-jhunjhunwala      rotten    False      True   False   \n",
              "\n",
              "       isTopCritic             publicationUrl            publicationName  \\\n",
              "27137        False  /critics/source/100009579  AniMat's Review (YouTube)   \n",
              "27138        False       /critics/source/1959               LarsenOnFilm   \n",
              "27139        False       /critics/source/3688        Casey's Movie Mania   \n",
              "27140         True       /critics/source/2785                   Livemint   \n",
              "27141         True       /critics/source/2785                   Livemint   \n",
              "\n",
              "                                               reviewUrl  \\\n",
              "27137                       https://youtu.be/ckNJciq0XUM   \n",
              "27138                  https://larsenonfilm.com/the-crow   \n",
              "27139  https://www.caseymoviemania.com/batman-honey-i...   \n",
              "27140  https://lifestyle.livemint.com/how-to-lounge/m...   \n",
              "27141  https://lifestyle.livemint.com/how-to-lounge/m...   \n",
              "\n",
              "                                                   quote scoreSentiment  \\\n",
              "27137  I know this is meant to show the first time th...       POSITIVE   \n",
              "27138  &#46;&#46;&#46; dark&#44; rainy&#44; and askew...       POSITIVE   \n",
              "27139  Jack Nicholson&#44; who received top billing a...       POSITIVE   \n",
              "27140  Unlike the more recent superhero movies that a...       POSITIVE   \n",
              "27141  For a film about a very fast man, the narrativ...       NEGATIVE   \n",
              "\n",
              "      originalScore                               movieId  \n",
              "27137          6/10  e53e6850-82b5-3727-a768-d99df185a901  \n",
              "27138           3/4  da04703c-b0d8-3dee-8910-bc1387164fc1  \n",
              "27139         3.5/5  f6f45d63-ea78-3139-985f-e5dc17caf85e  \n",
              "27140           NaN  10b522a5-873e-3e15-bd8b-65a079ab0b09  \n",
              "27141           NaN  7807e2b5-72d7-3dc7-8cd4-b9482b82fe01  "
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              "      <th></th>\n",
              "      <th>reviewId</th>\n",
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              "      <td>2024-06-14</td>\n",
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              "      <td>https://youtu.be/ckNJciq0XUM</td>\n",
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              "      <td>2024-06-15</td>\n",
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              "      <td>fresh</td>\n",
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              "      <td>False</td>\n",
              "      <td>False</td>\n",
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              "      <td>LarsenOnFilm</td>\n",
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              "      <td>&amp;#46;&amp;#46;&amp;#46; dark&amp;#44; rainy&amp;#44; and askew...</td>\n",
              "      <td>POSITIVE</td>\n",
              "      <td>3/4</td>\n",
              "      <td>da04703c-b0d8-3dee-8910-bc1387164fc1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27139</th>\n",
              "      <td>102921714</td>\n",
              "      <td>2024-06-17</td>\n",
              "      <td>Casey Chong</td>\n",
              "      <td>/critics/casey-chong</td>\n",
              "      <td>fresh</td>\n",
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              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>/critics/source/3688</td>\n",
              "      <td>Casey's Movie Mania</td>\n",
              "      <td>https://www.caseymoviemania.com/batman-honey-i...</td>\n",
              "      <td>Jack Nicholson&amp;#44; who received top billing a...</td>\n",
              "      <td>POSITIVE</td>\n",
              "      <td>3.5/5</td>\n",
              "      <td>f6f45d63-ea78-3139-985f-e5dc17caf85e</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27140</th>\n",
              "      <td>102923356</td>\n",
              "      <td>2024-06-24</td>\n",
              "      <td>Udita Jhunjhunwala</td>\n",
              "      <td>/critics/udita-jhunjhunwala</td>\n",
              "      <td>fresh</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>/critics/source/2785</td>\n",
              "      <td>Livemint</td>\n",
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              "      <td>Unlike the more recent superhero movies that a...</td>\n",
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              "      <td>2024-06-24</td>\n",
              "      <td>Udita Jhunjhunwala</td>\n",
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              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-071ef5fe-6713-401e-b871-8cd45e6ebc27 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-071ef5fe-6713-401e-b871-8cd45e6ebc27');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-a5dc5d4d-decb-4566-9f4f-c4bc0fa3e1b2\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-a5dc5d4d-decb-4566-9f4f-c4bc0fa3e1b2')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-a5dc5d4d-decb-4566-9f4f-c4bc0fa3e1b2 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "repr_error": "0"
            }
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "COLUMNS"
      ],
      "metadata": {
        "id": "6ULPK5wvhbXj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "mostviewer.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QxtSqQyziORM",
        "outputId": "8d112ed6-8f9b-41cb-a52a-392cbfff358c"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['reviewId', 'creationDate', 'criticName', 'criticPageUrl',\n",
              "       'reviewState', 'isFresh', 'isRotten', 'isRtUrl', 'isTopCritic',\n",
              "       'publicationUrl', 'publicationName', 'reviewUrl', 'quote',\n",
              "       'scoreSentiment', 'originalScore', 'movieId'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mostviewer.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "Ey9k3Nd-jWPV",
        "outputId": "82139f42-6b00-4307-ff93-a5a2d271c9eb"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           reviewId\n",
              "count  2.714200e+04\n",
              "mean   1.628587e+07\n",
              "std    3.493963e+07\n",
              "min    1.705000e+03\n",
              "25%    2.082886e+06\n",
              "50%    2.407968e+06\n",
              "75%    2.667693e+06\n",
              "max    1.029234e+08"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f668a474-8b61-4738-b67c-d184a779c532\" class=\"colab-df-container\">\n",
              "    <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>reviewId</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>2.714200e+04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>1.628587e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>3.493963e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.705000e+03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>2.082886e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>2.407968e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>2.667693e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.029234e+08</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f668a474-8b61-4738-b67c-d184a779c532')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-f668a474-8b61-4738-b67c-d184a779c532 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-f668a474-8b61-4738-b67c-d184a779c532');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-a23a20ed-087f-4671-8716-493fa714188c\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-a23a20ed-087f-4671-8716-493fa714188c')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-a23a20ed-087f-4671-8716-493fa714188c button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"mostviewer\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"reviewId\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 35542360.479199834,\n        \"min\": 1705.0,\n        \"max\": 102923418.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          16285866.29463562,\n          2407967.5,\n          27142.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    }
  ]
}