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+ "cells": [
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+ "cell_type": "markdown",
+ "source": [
+ "#Voyage.ai\n",
+ "\n",
+ "**By Srinivas Rao Chavan & Romit Ganjoo**"
+ ],
+ "metadata": {
+ "id": "SFDzbDxXm5bg"
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
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+ "outputId": "7cc19424-85dd-43bb-83ad-7c9a92d63ec5"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Requirement already satisfied: huggingface in /usr/local/lib/python3.10/dist-packages (0.0.1)\n",
+ "Requirement already satisfied: datasets in /usr/local/lib/python3.10/dist-packages (2.18.0)\n",
+ "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from datasets) (3.13.1)\n",
+ "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from datasets) (1.25.2)\n",
+ "Requirement already satisfied: pyarrow>=12.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (14.0.2)\n",
+ "Requirement already satisfied: pyarrow-hotfix in /usr/local/lib/python3.10/dist-packages (from datasets) (0.6)\n",
+ "Requirement already satisfied: dill<0.3.9,>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.3.8)\n",
+ "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets) (1.5.3)\n",
+ "Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (2.31.0)\n",
+ "Requirement already satisfied: tqdm>=4.62.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (4.66.2)\n",
+ "Requirement already satisfied: xxhash in /usr/local/lib/python3.10/dist-packages (from datasets) (3.4.1)\n",
+ "Requirement already satisfied: multiprocess in /usr/local/lib/python3.10/dist-packages (from datasets) (0.70.16)\n",
+ "Requirement already satisfied: fsspec[http]<=2024.2.0,>=2023.1.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (2023.6.0)\n",
+ "Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from datasets) (3.9.3)\n",
+ "Requirement already satisfied: huggingface-hub>=0.19.4 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.20.3)\n",
+ "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from datasets) (24.0)\n",
+ "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (6.0.1)\n",
+ "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.3.1)\n",
+ "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (23.2.0)\n",
+ "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.4.1)\n",
+ "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (6.0.5)\n",
+ "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.9.4)\n",
+ "Requirement already satisfied: async-timeout<5.0,>=4.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (4.0.3)\n",
+ "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.19.4->datasets) (4.10.0)\n",
+ "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (3.3.2)\n",
+ "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (3.6)\n",
+ "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (2.0.7)\n",
+ "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (2024.2.2)\n",
+ "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2.8.2)\n",
+ "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2023.4)\n",
+ "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas->datasets) (1.16.0)\n"
+ ]
+ }
+ ],
+ "source": [
+ "!pip install huggingface datasets"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [],
+ "metadata": {
+ "id": "RS5as6p3jElY"
+ },
+ "execution_count": 4,
+ "outputs": []
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "\n",
+ "\n",
+ "```\n",
+ "# This is formatted as code\n",
+ "```\n",
+ "\n",
+ "#Data Preprocessing"
+ ],
+ "metadata": {
+ "id": "G_rx4LWbmU_6"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "import pandas as pd\n",
+ "import seaborn as sns\n",
+ "import matplotlib.pyplot as plt\n",
+ "from wordcloud import WordCloud\n",
+ "from datetime import datetime"
+ ],
+ "metadata": {
+ "id": "tGVqrWTlScGz"
+ },
+ "execution_count": 5,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from datasets import load_dataset\n",
+ "\n",
+ "dataset = load_dataset(\"traversaal-ai-hackathon/hotel_datasets\")"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 209,
+ "referenced_widgets": [
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+ "Generating train split: 0 examples [00:00, ? examples/s]"
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+ "df=pd.DataFrame(dataset['train'])"
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+ "execution_count": 7,
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+ },
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+ "source": [
+ "df.head()\n",
+ "df.tail()"
+ ],
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+ "colab": {
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+ "execution_count": 8,
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ " hotel_name \\\n",
+ "5992 Hotel Campanile Paris Bercy Village \n",
+ "5993 Hotel Campanile Paris Bercy Village \n",
+ "5994 Hotel Campanile Paris Bercy Village \n",
+ "5995 Hotel Campanile Paris Bercy Village \n",
+ "5996 Hotel Campanile Paris Bercy Village \n",
+ "\n",
+ " hotel_description \\\n",
+ "5992 In the east of Paris, the hotel Campanile Berc... \n",
+ "5993 In the east of Paris, the hotel Campanile Berc... \n",
+ "5994 In the east of Paris, the hotel Campanile Berc... \n",
+ "5995 In the east of Paris, the hotel Campanile Berc... \n",
+ "5996 In the east of Paris, the hotel Campanile Berc... \n",
+ "\n",
+ " review_title \\\n",
+ "5992 Nice hotel but had trouble booking in. \n",
+ "5993 Great Location \n",
+ "5994 Great location \n",
+ "5995 For one night only \n",
+ "5996 Nice hotel in Paris Bercy \n",
+ "\n",
+ " review_text rate \\\n",
+ "5992 We had just had a very long and delayed train ... 3.0 \n",
+ "5993 We stayed at the Kyriad Hotel Paris Bercy Vill... 4.0 \n",
+ "5994 Stayed here for a few days and it is a great l... 5.0 \n",
+ "5995 We stayed here for one night on our way to Ita... 3.0 \n",
+ "5996 The Hotel is close to the metro station Cour S... 4.0 \n",
+ "\n",
+ " tripdate hotel_url \\\n",
+ "5992 September 2019 https://www.tripadvisor.com/Hotel_Review-g1871... \n",
+ "5993 September 2019 https://www.tripadvisor.com/Hotel_Review-g1871... \n",
+ "5994 October 2019 https://www.tripadvisor.com/Hotel_Review-g1871... \n",
+ "5995 September 2019 https://www.tripadvisor.com/Hotel_Review-g1871... \n",
+ "5996 September 2019 https://www.tripadvisor.com/Hotel_Review-g1871... \n",
+ "\n",
+ " hotel_image \\\n",
+ "5992 https://media-cdn.tripadvisor.com/media/photo-... \n",
+ "5993 https://media-cdn.tripadvisor.com/media/photo-... \n",
+ "5994 https://media-cdn.tripadvisor.com/media/photo-... \n",
+ "5995 https://media-cdn.tripadvisor.com/media/photo-... \n",
+ "5996 https://media-cdn.tripadvisor.com/media/photo-... \n",
+ "\n",
+ " price_range rating_value \\\n",
+ "5992 $ (Based on Average Nightly Rates for a Standa... 4.0 \n",
+ "5993 $ (Based on Average Nightly Rates for a Standa... 4.0 \n",
+ "5994 $ (Based on Average Nightly Rates for a Standa... 4.0 \n",
+ "5995 $ (Based on Average Nightly Rates for a Standa... 4.0 \n",
+ "5996 $ (Based on Average Nightly Rates for a Standa... 4.0 \n",
+ "\n",
+ " review_count street_address locality country \n",
+ "5992 1625 17 rue Baron le Roy Paris France \n",
+ "5993 1625 17 rue Baron le Roy Paris France \n",
+ "5994 1625 17 rue Baron le Roy Paris France \n",
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+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "df.info()"
+ ],
+ "metadata": {
+ "id": "ecN-GZX4Sfo-",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "f4d13950-de89-48c0-c2d1-3adac82c5e6f"
+ },
+ "execution_count": 9,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\n",
+ "RangeIndex: 5997 entries, 0 to 5996\n",
+ "Data columns (total 14 columns):\n",
+ " # Column Non-Null Count Dtype \n",
+ "--- ------ -------------- ----- \n",
+ " 0 hotel_name 5997 non-null object \n",
+ " 1 hotel_description 5197 non-null object \n",
+ " 2 review_title 5997 non-null object \n",
+ " 3 review_text 4867 non-null object \n",
+ " 4 rate 4867 non-null float64\n",
+ " 5 tripdate 5997 non-null object \n",
+ " 6 hotel_url 5997 non-null object \n",
+ " 7 hotel_image 5997 non-null object \n",
+ " 8 price_range 5997 non-null object \n",
+ " 9 rating_value 5997 non-null float64\n",
+ " 10 review_count 5997 non-null int64 \n",
+ " 11 street_address 5997 non-null object \n",
+ " 12 locality 5997 non-null object \n",
+ " 13 country 5997 non-null object \n",
+ "dtypes: float64(2), int64(1), object(11)\n",
+ "memory usage: 656.0+ KB\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "Removing Duplicate rows in the dataset"
+ ],
+ "metadata": {
+ "id": "eLpz9jf4s2VH"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "df = df.drop_duplicates()"
+ ],
+ "metadata": {
+ "id": "trTqMaKltKd0"
+ },
+ "execution_count": 10,
+ "outputs": []
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "*Handling Missing Values*"
+ ],
+ "metadata": {
+ "id": "P9XiUPmdqkqB"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "df['hotel_description'] = df['hotel_description'].fillna('No description') #filling missing values in hotel_description with value 'No description'\n",
+ "df['review_text'] = df['review_text'].fillna('No review') #filling missing values in review_text with value 'No review'\n",
+ "df['rate'] = df['rate'].fillna(df['rate'].mean()) #filling missing values in rate with value average value in rate feature\n",
+ "df['rating_value'] = df['rating_value'].fillna(df['rating_value'].mean())\n",
+ "df['review_count'] = df['review_count'].fillna(df['review_count'].mean())"
+ ],
+ "metadata": {
+ "id": "EkRqmpZspMlH"
+ },
+ "execution_count": 11,
+ "outputs": []
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "*Convert price_range to a categorical type if it's not already*\n"
+ ],
+ "metadata": {
+ "id": "uk0BigKtuFNJ"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "df['price_range'] = df['price_range'].astype('category')"
+ ],
+ "metadata": {
+ "id": "SEFTPUwpuOld"
+ },
+ "execution_count": 12,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "len(df['hotel_name'].unique())"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "29jE65Rqt8b0",
+ "outputId": "87dc7dd9-f741-41c7-c8ff-f1e471ac5dfa"
+ },
+ "execution_count": 13,
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "150"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 13
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "#EDA"
+ ],
+ "metadata": {
+ "id": "lwNEMq8CuczJ"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "print(df.describe())"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "F8BFrIV5ufMy",
+ "outputId": "3e627d7a-834e-41d8-9aab-f89e44997cba"
+ },
+ "execution_count": 14,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ " rate rating_value review_count\n",
+ "count 5997.000000 5997.000000 5997.000000\n",
+ "mean 4.368810 4.446640 3380.770885\n",
+ "std 1.056208 0.432757 3771.730100\n",
+ "min 1.000000 3.000000 39.000000\n",
+ "25% 4.368810 4.000000 962.000000\n",
+ "50% 5.000000 4.500000 2053.000000\n",
+ "75% 5.000000 5.000000 4595.000000\n",
+ "max 5.000000 5.000000 24877.000000\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "*distribution of ratings and reviews*"
+ ],
+ "metadata": {
+ "id": "Ff7Fn_HWuzZX"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "plt.figure(figsize=(10, 4))\n",
+ "plt.subplot(1, 2, 1)\n",
+ "sns.histplot(df['rating_value'], bins=20, kde=True)\n",
+ "plt.title('Distribution of Rating Values')\n",
+ "\n",
+ "plt.subplot(1, 2, 2)\n",
+ "sns.histplot(df['review_count'], bins=20, kde=True)\n",
+ "plt.title('Distribution of Review Counts')\n",
+ "plt.show()"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 410
+ },
+ "id": "jGDIcI6Tu4tp",
+ "outputId": "771b40da-5313-47c2-8a45-7722fd644c92"
+ },
+ "execution_count": 15,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "