Yelp_Data_Converting_User_Json_to_CSV.ipynb

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      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')"
      ],
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        "id": "g-r1ezXE2WGA",
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          "base_uri": "https://localhost:8080/"
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      "execution_count": 5,
      "outputs": [
        {
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          "name": "stdout",
          "text": [
            "Mounted at /content/gdrive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import json\n",
        "import os\n",
        "\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "from tqdm import tqdm"
      ],
      "metadata": {
        "id": "LpW_FjImgZT9"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "User file"
      ],
      "metadata": {
        "id": "bYV1Ok6-5pBE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "user_json_path = '/content/gdrive/MyDrive/yelp_dataset/yelp_academic_dataset_user.json'"
      ],
      "metadata": {
        "id": "Op7ik-2UrNRw"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data = {'user_id': [], 'name': [], 'review_count': [], 'yelping_since': [], 'friends': [], 'useful': [], 'funny': [], 'cool': [], 'fans': [], \n",
        "        'elite': [], 'average_stars': []}\n",
        "\n",
        "with open(user_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['name'].append(review['name'])\n",
        "        data['review_count'].append(review['review_count'])\n",
        "        data['yelping_since'].append(review['yelping_since'])\n",
        "        data['friends'].append(review['friends'])\n",
        "        data['useful'].append(review['useful'])\n",
        "        data['funny'].append(review['funny'])\n",
        "        data['cool'].append(review['cool'])\n",
        "        data['fans'].append(review['fans'])\n",
        "        data['elite'].append(review['elite'])\n",
        "        data['average_stars'].append(review['average_stars'])"
      ],
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      "outputs": [
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            "1987897it [00:58, 33868.53it/s]\n"
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    {
      "cell_type": "code",
      "source": [
        "df_user = pd.DataFrame(data)\n",
        "\n",
        "print(df_user.shape)\n",
        "df_user.head()"
      ],
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          "base_uri": "https://localhost:8080/",
          "height": 354
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            "(1987897, 11)\n"
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              "                  user_id    name  review_count        yelping_since  \\\n",
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              "4  hA5lMy-EnncsH4JoR-hFGQ   Karen            79  2007-01-05 19:40:59   \n",
              "\n",
              "                                             friends  useful  funny   cool  \\\n",
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              "\n",
              "   fans                                              elite  average_stars  \n",
              "0   267                                               2007           3.91  \n",
              "1  3138  2009,2010,2011,2012,2013,2014,2015,2016,2017,2...           3.74  \n",
              "2    52                           2009,2010,2011,2012,2013           3.32  \n",
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              "4     1                                                              3.54  "
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      "cell_type": "code",
      "source": [
        "df_reviews =pd.read_csv('/content/gdrive/MyDrive/498_Group52/yelp_dataset/yelp_reviews_restaurants.csv')"
      ],
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      "execution_count": 10,
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            "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py:3326: DtypeWarning: Columns (0) 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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      "execution_count": 11,
      "outputs": [
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            "text/plain": [
              "  Unnamed: 0                 user_id             business_id  \\\n",
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              "                  date  stars  \\\n",
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              "\n",
              "                                                text  \n",
              "0  If you decide to eat here, just be aware it is...  \n",
              "1  This is the second time we tried turning point...  \n",
              "2  The place is cute and the staff was very frien...  \n",
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            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_reviews.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MHtYfc8_BGVS",
        "outputId": "55c83577-4b78-40d2-cecc-cb53973d54e4"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(4724686, 6)"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# only keep users that left restaurant reviews\n",
        "df2 = df_user.merge(df_reviews,left_on='user_id',right_on='user_id')\n",
        "df2 = df2.drop_duplicates(subset=['user_id'])\n",
        "users_restaurants_only  = df2.iloc[: , :11]"
      ],
      "metadata": {
        "id": "WkK4tGwVx6d7"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "users_restaurants_only.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QlFRnn_eCQUm",
        "outputId": "e0afcf5e-966b-46be-ec86-6664cfc7a733"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1446025, 11)"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "users_restaurants_only.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "id": "j8SZG0AuB13y",
        "outputId": "592067aa-77d5-42d9-d383-b12d047b40f3"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "                   user_id    name  review_count        yelping_since  \\\n",
              "0   qVc8ODYU5SZjKXVBgXdI7w  Walker           585  2007-01-25 16:47:26   \n",
              "7   j14WgRoU_-2ZE1aw1dXrJg  Daniel          4333  2009-01-25 04:35:42   \n",
              "34  2WnXYQFK0hXEoTxPtV2zvg   Steph           665  2008-07-25 10:41:00   \n",
              "45  SZDeASXq7o05mMNLshsdIA    Gwen           224  2005-11-29 04:38:33   \n",
              "52  hA5lMy-EnncsH4JoR-hFGQ   Karen            79  2007-01-05 19:40:59   \n",
              "\n",
              "                                              friends  useful  funny   cool  \\\n",
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              "52  PBK4q9KEEBHhFvSXCUirIw, 3FWPpM7KU1gXeOM_ZbYMbA...      29     15      7   \n",
              "\n",
              "    fans                                              elite  average_stars  \n",
              "0    267                                               2007           3.91  \n",
              "7   3138  2009,2010,2011,2012,2013,2014,2015,2016,2017,2...           3.74  \n",
              "34    52                           2009,2010,2011,2012,2013           3.32  \n",
              "45    28                                     2009,2010,2011           4.27  \n",
              "52     1                                                              3.54  "
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          "metadata": {},
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    },
    {
      "cell_type": "code",
      "source": [
        "users_restaurants_only.to_csv('/content/gdrive/MyDrive/yelp_dataset/yelp_user_restaurants.csv')"
      ],
      "metadata": {
        "id": "C-Ox9Wm76djD"
      },
      "execution_count": 17,
      "outputs": []
    }
  ]
}