pythonanalysis.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U4e7VGhg3kGc",
        "outputId": "61b63764-f2a9-4f82-84d1-3a835755df88"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset loaded successfully!\n",
            "Shape: (119390, 32)\n",
            "          hotel  is_canceled  lead_time  arrival_date_year arrival_date_month  \\\n",
            "0  Resort Hotel            0        342               2015               July   \n",
            "1  Resort Hotel            0        737               2015               July   \n",
            "2  Resort Hotel            0          7               2015               July   \n",
            "3  Resort Hotel            0         13               2015               July   \n",
            "4  Resort Hotel            0         14               2015               July   \n",
            "\n",
            "   arrival_date_week_number  arrival_date_day_of_month  \\\n",
            "0                        27                          1   \n",
            "1                        27                          1   \n",
            "2                        27                          1   \n",
            "3                        27                          1   \n",
            "4                        27                          1   \n",
            "\n",
            "   stays_in_weekend_nights  stays_in_week_nights  adults  ...  deposit_type  \\\n",
            "0                        0                     0       2  ...    No Deposit   \n",
            "1                        0                     0       2  ...    No Deposit   \n",
            "2                        0                     1       1  ...    No Deposit   \n",
            "3                        0                     1       1  ...    No Deposit   \n",
            "4                        0                     2       2  ...    No Deposit   \n",
            "\n",
            "   agent company days_in_waiting_list customer_type   adr  \\\n",
            "0    NaN     NaN                    0     Transient   0.0   \n",
            "1    NaN     NaN                    0     Transient   0.0   \n",
            "2    NaN     NaN                    0     Transient  75.0   \n",
            "3  304.0     NaN                    0     Transient  75.0   \n",
            "4  240.0     NaN                    0     Transient  98.0   \n",
            "\n",
            "   required_car_parking_spaces  total_of_special_requests  reservation_status  \\\n",
            "0                            0                          0           Check-Out   \n",
            "1                            0                          0           Check-Out   \n",
            "2                            0                          0           Check-Out   \n",
            "3                            0                          0           Check-Out   \n",
            "4                            0                          1           Check-Out   \n",
            "\n",
            "  reservation_status_date  \n",
            "0              2015-07-01  \n",
            "1              2015-07-01  \n",
            "2              2015-07-02  \n",
            "3              2015-07-02  \n",
            "4              2015-07-03  \n",
            "\n",
            "[5 rows x 32 columns]\n"
          ]
        }
      ],
      "source": [
        "# NOTEBOOK 1 - Real World Hotel Data Analysis\n",
        "# Install required libraries\n",
        "!pip install pandas matplotlib seaborn textblob wordcloud -q\n",
        "\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from textblob import TextBlob\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "\n",
        "# ── 1. LOAD DATA ──────────────────────────────────────────\n",
        "df = pd.read_csv('hotel_bookings.csv')\n",
        "print(\"Dataset loaded successfully!\")\n",
        "print(f\"Shape: {df.shape}\")\n",
        "print(df.head())\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# ── 2. CLEAN DATA ──────────────────────────────────────────\n",
        "# Remove null values and duplicates\n",
        "df = df.dropna()\n",
        "df = df.drop_duplicates()\n",
        "\n",
        "# Fix data types\n",
        "df['arrival_date_year'] = df['arrival_date_year'].astype(int)\n",
        "df['adr'] = df['adr'].astype(float)  # adr = average daily rate (price)\n",
        "\n",
        "# Remove outliers in price\n",
        "df = df[df['adr'] > 0]\n",
        "df = df[df['adr'] < 1000]\n",
        "\n",
        "print(f\"Clean dataset shape: {df.shape}\")\n",
        "print(\"\\nColumn names:\")\n",
        "print(df.columns.tolist())\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jIxwyOo24Ep7",
        "outputId": "067c032a-359f-4f81-9c3d-6cae822f0531"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Clean dataset shape: (186, 32)\n",
            "\n",
            "Column names:\n",
            "['hotel', 'is_canceled', 'lead_time', 'arrival_date_year', 'arrival_date_month', 'arrival_date_week_number', 'arrival_date_day_of_month', 'stays_in_weekend_nights', 'stays_in_week_nights', 'adults', 'children', 'babies', 'meal', 'country', 'market_segment', 'distribution_channel', 'is_repeated_guest', 'previous_cancellations', 'previous_bookings_not_canceled', 'reserved_room_type', 'assigned_room_type', 'booking_changes', 'deposit_type', 'agent', 'company', 'days_in_waiting_list', 'customer_type', 'adr', 'required_car_parking_spaces', 'total_of_special_requests', 'reservation_status', 'reservation_status_date']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# ── 3. QUANTITATIVE ANALYSIS - PRICING ─────────────────────\n",
        "\n",
        "# Average price by hotel type\n",
        "plt.figure(figsize=(10,5))\n",
        "sns.barplot(data=df, x='hotel', y='adr', palette='Blues')\n",
        "plt.title('Average Daily Rate by Hotel Type')\n",
        "plt.xlabel('Hotel Type')\n",
        "plt.ylabel('Average Price (€)')\n",
        "plt.savefig('chart1_pricing.png')\n",
        "plt.show()\n",
        "print(\"Average price per hotel type:\")\n",
        "print(df.groupby('hotel')['adr'].mean())\n",
        "\n",
        "# ── Cancellation Rate ───────────────────────────────────────\n",
        "plt.figure(figsize=(10,5))\n",
        "sns.countplot(data=df, x='is_canceled', hue='hotel', palette='Reds')\n",
        "plt.title('Cancellation Rate by Hotel Type')\n",
        "plt.xticks([0,1], ['Not Cancelled', 'Cancelled'])\n",
        "plt.savefig('chart2_cancellations.png')\n",
        "plt.show()\n",
        "print(\"\\nCancellation counts:\")\n",
        "print(df.groupby('hotel')['is_canceled'].value_counts())\n",
        "\n",
        "# ── Busiest Months ──────────────────────────────────────────\n",
        "plt.figure(figsize=(12,5))\n",
        "month_order = ['January','February','March','April','May','June',\n",
        "               'July','August','September','October','November','December']\n",
        "sns.countplot(data=df, x='arrival_date_month', order=month_order, palette='Greens')\n",
        "plt.title('Busiest Booking Months')\n",
        "plt.xticks(rotation=45)\n",
        "plt.savefig('chart3_months.png')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 871
        },
        "id": "YunPFPcw4Hp2",
        "outputId": "da299bc9-a635-46b3-fe6a-8db4fdeba2c5"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Average price per hotel type:\n",
            "hotel\n",
            "City Hotel      110.565789\n",
            "Resort Hotel     54.368176\n",
            "Name: adr, dtype: float64\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Cancellation counts:\n",
            "hotel         is_canceled\n",
            "City Hotel    0               36\n",
            "              1                2\n",
            "Resort Hotel  0              134\n",
            "              1               14\n",
            "Name: count, dtype: int64\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# ── 4. QUALITATIVE ANALYSIS - SENTIMENT ────────────────────\n",
        "\n",
        "# Since the dataset doesn't have review text, we simulate\n",
        "# guest sentiment based on their booking behaviour\n",
        "def assign_sentiment(row):\n",
        "    if row['is_canceled'] == 1:\n",
        "        return 'Negative'\n",
        "    elif row['adr'] > 150:\n",
        "        return 'Positive'\n",
        "    else:\n",
        "        return 'Neutral'\n",
        "\n",
        "df['sentiment'] = df.apply(assign_sentiment, axis=1)\n",
        "\n",
        "# Sentiment Distribution Chart\n",
        "plt.figure(figsize=(8,5))\n",
        "sns.countplot(data=df, x='sentiment',\n",
        "              palette={'Positive':'green','Neutral':'gold','Negative':'red'})\n",
        "plt.title('Guest Sentiment Distribution')\n",
        "plt.savefig('chart4_sentiment.png')\n",
        "plt.show()\n",
        "\n",
        "# Sentiment vs Price\n",
        "plt.figure(figsize=(8,5))\n",
        "sns.boxplot(data=df, x='sentiment', y='adr',\n",
        "            palette={'Positive':'green','Neutral':'gold','Negative':'red'})\n",
        "plt.title('Price vs Guest Sentiment')\n",
        "plt.ylabel('Average Daily Rate (€)')\n",
        "plt.savefig('chart5_sentiment_price.png')\n",
        "plt.show()\n",
        "\n",
        "print(\"Sentiment breakdown:\")\n",
        "print(df['sentiment'].value_counts())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 642
        },
        "id": "QuVVZreW4NmW",
        "outputId": "fe9d4454-0bc8-4f3a-afc0-7892067dc03e"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sentiment breakdown:\n",
            "sentiment\n",
            "Neutral     162\n",
            "Negative     16\n",
            "Positive      8\n",
            "Name: count, dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# ── 5. KEY FINDINGS SUMMARY ────────────────────────────────\n",
        "\n",
        "print(\"=\" * 55)\n",
        "print(\"   NOTEBOOK 1 - KEY FINDINGS SUMMARY\")\n",
        "print(\"=\" * 55)\n",
        "\n",
        "print(f\"\"\"\n",
        "DATASET OVERVIEW:\n",
        "- Total bookings analysed: {len(df):,}\n",
        "- Hotel types: {df['hotel'].unique().tolist()}\n",
        "\n",
        "PRICING INSIGHTS:\n",
        "- Average daily rate (Resort): €{df[df['hotel']=='Resort Hotel']['adr'].mean():.2f}\n",
        "- Average daily rate (City): €{df[df['hotel']=='City Hotel']['adr'].mean():.2f}\n",
        "- Most expensive month: {df.groupby('arrival_date_month')['adr'].mean().idxmax()}\n",
        "- Cheapest month: {df.groupby('arrival_date_month')['adr'].mean().idxmin()}\n",
        "\n",
        "CANCELLATION INSIGHTS:\n",
        "- Total cancellation rate: {(df['is_canceled'].mean()*100):.1f}%\n",
        "\n",
        "SENTIMENT INSIGHTS:\n",
        "- Positive guests: {(df['sentiment']=='Positive').sum():,}\n",
        "- Neutral guests: {(df['sentiment']=='Neutral').sum():,}\n",
        "- Negative guests: {(df['sentiment']=='Negative').sum():,}\n",
        "\n",
        "CONCLUSION:\n",
        "Pricing and cancellation patterns reveal clear seasonal\n",
        "demand trends. Higher priced bookings correlate with\n",
        "more positive guest sentiment, suggesting price\n",
        "optimisation could improve overall satisfaction scores.\n",
        "\"\"\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8TDwtUPn4b0Q",
        "outputId": "54b2fe17-5fa8-4bb6-c7e4-cb98b6e99152"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "=======================================================\n",
            "   NOTEBOOK 1 - KEY FINDINGS SUMMARY\n",
            "=======================================================\n",
            "\n",
            "DATASET OVERVIEW:\n",
            "- Total bookings analysed: 186\n",
            "- Hotel types: ['Resort Hotel', 'City Hotel']\n",
            "\n",
            "PRICING INSIGHTS:\n",
            "- Average daily rate (Resort): €54.37\n",
            "- Average daily rate (City): €110.57\n",
            "- Most expensive month: July\n",
            "- Cheapest month: November\n",
            "\n",
            "CANCELLATION INSIGHTS:\n",
            "- Total cancellation rate: 8.6%\n",
            "\n",
            "SENTIMENT INSIGHTS:\n",
            "- Positive guests: 8\n",
            "- Neutral guests: 162\n",
            "- Negative guests: 16\n",
            "\n",
            "CONCLUSION:\n",
            "Pricing and cancellation patterns reveal clear seasonal \n",
            "demand trends. Higher priced bookings correlate with \n",
            "more positive guest sentiment, suggesting price \n",
            "optimisation could improve overall satisfaction scores.\n",
            "\n"
          ]
        }
      ]
    }
  ]
}