Create_Reviews_CSV_Version_2.ipynb

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      "source": [
        "import json\n",
        "import os\n",
        "\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib\n",
        "from matplotlib import pyplot as plt\n",
        "import seaborn as sns\n",
        "import statistics\n",
        "import numpy as np\n",
        "\n",
        "from tqdm import tqdm\n",
        "\n",
        "%matplotlib inline"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')"
      ],
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      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/gdrive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Business File"
      ],
      "metadata": {
        "id": "Xv4sJYOnGXVe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_b =pd.read_csv('/content/gdrive/MyDrive/yelp_dataset/yelp_business_clean_version1.csv')"
      ],
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        "id": "uLmZnmKSPaVL"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py:3326: DtypeWarning: Columns (43,44,45,46) have mixed types.Specify dtype option on import or set low_memory=False.\n",
            "  exec(code_obj, self.user_global_ns, self.user_ns)\n"
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      "cell_type": "code",
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        "df_b.shape"
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              "(35290, 68)"
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          "metadata": {},
          "execution_count": 4
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    {
      "cell_type": "markdown",
      "source": [
        "Review File"
      ],
      "metadata": {
        "id": "ATriCsjtGj2s"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "review_json_path = '/content/gdrive/MyDrive/yelp_dataset/yelp_academic_dataset_review.json'"
      ],
      "metadata": {
        "id": "jf9SVsOkGlWz"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data = {'user_id': [], 'business_id': [], 'date': [], 'stars': [], 'text': [], 'useful': [], 'funny': [],'cool': []}\n",
        "\n",
        "with open(review_json_path) as f:\n",
        "    for line in tqdm(f):\n",
        "        review = json.loads(line)\n",
        "        data['user_id'].append(review['user_id'])\n",
        "        data['business_id'].append(review['business_id'])\n",
        "        data['date'].append(review['date'])\n",
        "        data['stars'].append(review['stars'])\n",
        "        data['text'].append(review['text'])\n",
        "        data['useful'].append(review['useful'])\n",
        "        data['funny'].append(review['funny'])\n",
        "        data['cool'].append(review['cool'])"
      ],
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            "6990280it [01:42, 67924.79it/s] \n"
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    {
      "cell_type": "code",
      "source": [
        "df_r = pd.DataFrame(data)\n",
        "\n",
        "print(df_r.shape)\n",
        "df_r.head()"
      ],
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            "(6990280, 8)\n"
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              "                  user_id             business_id                 date  stars  \\\n",
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              "\n",
              "                                                text  useful  funny  cool  \n",
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      "source": [
        "# only keep businesses that are categorized as restaurant\n",
        "df_r = df_r.merge(df_b,left_on='business_id',right_on='business_id')"
      ],
      "metadata": {
        "id": "yQpy1xz-PaVO"
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        "df_r.head()"
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      "execution_count": 9,
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              "                  user_id             business_id                 date  \\\n",
              "0  8g_iMtfSiwikVnbP2etR0A  YjUWPpI6HXG530lwP-fb2A  2014-02-05 20:30:30   \n",
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              "4  -rGU3wo4fgEnGRboYdMTjw  YjUWPpI6HXG530lwP-fb2A  2015-06-22 16:08:27   \n",
              "\n",
              "   stars_x                                               text  useful  funny  \\\n",
              "0      3.0  Family diner. Had the buffet. Eclectic assortm...       0      0   \n",
              "1      2.0  Let me start by saying the service is AWESOME!...       1      0   \n",
              "2      5.0  Went here for the first time for the dinner bu...       0      0   \n",
              "3      5.0  This is my 1st experience here at Kettle.  The...       0      0   \n",
              "4      3.0  Located on the west side of Starr Pass Blvd, K...       3      0   \n",
              "\n",
              "   cool  Unnamed: 0               name  ... NoiseLevel_very_loud  \\\n",
              "0     0       13266  Kettle Restaurant  ...                    0   \n",
              "1     0       13266  Kettle Restaurant  ...                    0   \n",
              "2     0       13266  Kettle Restaurant  ...                    0   \n",
              "3     0       13266  Kettle Restaurant  ...                    0   \n",
              "4     0       13266  Kettle Restaurant  ...                    0   \n",
              "\n",
              "  RestaurantsAttire_casual RestaurantsAttire_dressy  RestaurantsAttire_formal  \\\n",
              "0                        1                        0                         0   \n",
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              "4                        1                        0                         0   \n",
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          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_r  = df_r.iloc[: , :8]\n",
        "df_r = df_r.rename(columns = {'stars_x':'stars'})"
      ],
      "metadata": {
        "id": "2ID1nlfSPaVP"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_r.head()"
      ],
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        "colab": {
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          "height": 206
        },
        "id": "nfW44nJuHdy0",
        "outputId": "bcfb2666-849d-458d-e43a-acba052dac37"
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      "execution_count": 11,
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              "                  user_id             business_id                 date  stars  \\\n",
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    {
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        "df_r.shape"
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        "outputId": "d637273e-cae3-4a0c-97ca-503ebc2cc976",
        "id": "PPb5-3NmPaVQ"
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      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(3700354, 8)"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
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    },
    {
      "cell_type": "markdown",
      "source": [
        "Most reviews received 0 votes for useful, funny, and cool. Therefore, the clean dataset will not include these variables."
      ],
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        "id": "Wte94MMRJVWi"
      }
    },
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        "df_r.describe()"
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          "height": 300
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        "id": "u_1aje_EJS_Z",
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      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              stars        useful         funny          cool\n",
              "count  3.700354e+06  3.700354e+06  3.700354e+06  3.700354e+06\n",
              "mean   3.805917e+00  9.761228e-01  2.963743e-01  4.683973e-01\n",
              "std    1.374893e+00  2.786812e+00  1.784660e+00  2.191670e+00\n",
              "min    1.000000e+00 -1.000000e+00 -1.000000e+00 -1.000000e+00\n",
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              "50%    4.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00\n",
              "75%    5.000000e+00  1.000000e+00  0.000000e+00  0.000000e+00\n",
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              "      <th>useful</th>\n",
              "      <th>funny</th>\n",
              "      <th>cool</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>3.700354e+06</td>\n",
              "      <td>3.700354e+06</td>\n",
              "      <td>3.700354e+06</td>\n",
              "      <td>3.700354e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>3.805917e+00</td>\n",
              "      <td>9.761228e-01</td>\n",
              "      <td>2.963743e-01</td>\n",
              "      <td>4.683973e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>1.374893e+00</td>\n",
              "      <td>2.786812e+00</td>\n",
              "      <td>1.784660e+00</td>\n",
              "      <td>2.191670e+00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000e+00</td>\n",
              "      <td>-1.000000e+00</td>\n",
              "      <td>-1.000000e+00</td>\n",
              "      <td>-1.000000e+00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>3.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>4.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>5.000000e+00</td>\n",
              "      <td>1.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.000000e+00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>5.000000e+00</td>\n",
              "      <td>4.200000e+02</td>\n",
              "      <td>7.920000e+02</td>\n",
              "      <td>4.040000e+02</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-66cc7deb-c708-48aa-8c74-aa6134faedf6')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      border-radius: 50%;\n",
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              "      fill: #1967D2;\n",
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              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-66cc7deb-c708-48aa-8c74-aa6134faedf6 button.colab-df-convert');\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-66cc7deb-c708-48aa-8c74-aa6134faedf6');\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",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Remove useful, funny, and cool from dataset\n",
        "df_r = df_r.iloc[:, :5]"
      ],
      "metadata": {
        "id": "Zu8hw1eOIa-i"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "There are no empty reviews with missing entries"
      ],
      "metadata": {
        "id": "5nP2Gj7mPC0I"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "nan_in_col  = df_r[df_r['text'].isna()]"
      ],
      "metadata": {
        "id": "onx8-2MmLAwm"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "nan_in_col"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49
        },
        "id": "fYahsLuGLA0i",
        "outputId": "ab0f3b20-5d41-4c9d-cb76-e8a3eb5ecd74"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Empty DataFrame\n",
              "Columns: [user_id, business_id, date, stars, text]\n",
              "Index: []"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b9513bca-2579-462e-875f-ee8c77b8435f\">\n",
              "    <div 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>user_id</th>\n",
              "      <th>business_id</th>\n",
              "      <th>date</th>\n",
              "      <th>stars</th>\n",
              "      <th>text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b9513bca-2579-462e-875f-ee8c77b8435f')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
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              "      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",
              "    [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-b9513bca-2579-462e-875f-ee8c77b8435f 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-b9513bca-2579-462e-875f-ee8c77b8435f');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Save as CSV file"
      ],
      "metadata": {
        "id": "xwh2rY79PdnX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_r.to_csv('/content/gdrive/MyDrive/yelp_dataset/yelp_reviews_version2.csv', index = False)"
      ],
      "metadata": {
        "id": "_uZgoVltPaVR"
      },
      "execution_count": 17,
      "outputs": []
    }
  ]
}