Copy_of_Airbnb_Bookings_Analysis_Capstone_Project.ipynb

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      "name": "Copy of Airbnb Bookings Analysis - Capstone Project.ipynb",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/Ramanmagar/Air-bnb-bookings-Analysis/blob/main/Copy_of_Airbnb_Bookings_Analysis_Capstone_Project.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "cell_type": "markdown",
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        "id": "Y06xIdG26kRF"
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      "source": [
        "## <b> Since 2008, guests and hosts have used Airbnb to expand on traveling possibilities and present a more unique, personalized way of experiencing the world. Today, Airbnb became one of a kind service that is used and recognized by the whole world. Data analysis on millions of listings provided through Airbnb is a crucial factor for the company. These millions of listings generate a lot of data - data that can be analyzed and used for security, business decisions, understanding of customers' and providers' (hosts) behavior and performance on the platform, guiding marketing initiatives, implementation of innovative additional services and much more. </b>\n",
        "\n",
        "## <b>This dataset has around 49,000 observations in it with 16 columns and it is a mix between categorical and numeric values. </b>\n",
        "\n",
        "## <b> Explore and analyze the data to discover key understandings (not limited to these) such as : \n",
        "* What can we learn about different hosts and areas?\n",
        "* What can we learn from predictions? (ex: locations, prices, reviews, etc)\n",
        "* Which hosts are the busiest and why?\n",
        "* Is there any noticeable difference of traffic among different areas and what could be the reason for it? </b>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Team Members:\n",
        "\n",
        "1. Premanand Gaikwad\n",
        "2. Sanchit Patil\n",
        "3. Raman Magar\n",
        "4. Osama Ansari\n"
      ],
      "metadata": {
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    {
      "cell_type": "code",
      "metadata": {
        "id": "dByMsuzT8Tnw"
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      "source": [
        "#Import the libraries required for further operations of EDA\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "%matplotlib inline"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Mounting the drive\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Pv6cenILLqB8",
        "outputId": "57b5cfe8-8961-4301-edfb-5fa44df186e7"
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      "execution_count": null,
      "outputs": [
        {
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          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# locating/reading the data file for analysis\n",
        "file_location='/content/drive/MyDrive/Airbnb Bookings Analysis-Premanand Gaikwad/Airbnb NYC 2019.csv'\n",
        "df=pd.read_csv(file_location)"
      ],
      "metadata": {
        "id": "bgQ1vgebLxx1"
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      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Checking the data\n",
        "df.head()"
      ],
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        "id": "aManrGzVModv",
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              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>name</th>\n",
              "      <th>host_id</th>\n",
              "      <th>host_name</th>\n",
              "      <th>neighbourhood_group</th>\n",
              "      <th>neighbourhood</th>\n",
              "      <th>latitude</th>\n",
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              "      <th>calculated_host_listings_count</th>\n",
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              "      <th>0</th>\n",
              "      <td>2539</td>\n",
              "      <td>Clean &amp; quiet apt home by the park</td>\n",
              "      <td>2787</td>\n",
              "      <td>John</td>\n",
              "      <td>Brooklyn</td>\n",
              "      <td>Kensington</td>\n",
              "      <td>40.64749</td>\n",
              "      <td>-73.97237</td>\n",
              "      <td>Private room</td>\n",
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              "      <td>2018-10-19</td>\n",
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              "      <td>365</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2595</td>\n",
              "      <td>Skylit Midtown Castle</td>\n",
              "      <td>2845</td>\n",
              "      <td>Jennifer</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Midtown</td>\n",
              "      <td>40.75362</td>\n",
              "      <td>-73.98377</td>\n",
              "      <td>Entire home/apt</td>\n",
              "      <td>225</td>\n",
              "      <td>1</td>\n",
              "      <td>45</td>\n",
              "      <td>2019-05-21</td>\n",
              "      <td>0.38</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3647</td>\n",
              "      <td>THE VILLAGE OF HARLEM....NEW YORK !</td>\n",
              "      <td>4632</td>\n",
              "      <td>Elisabeth</td>\n",
              "      <td>Manhattan</td>\n",
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              "      <td>Cozy Entire Floor of Brownstone</td>\n",
              "      <td>4869</td>\n",
              "      <td>LisaRoxanne</td>\n",
              "      <td>Brooklyn</td>\n",
              "      <td>Clinton Hill</td>\n",
              "      <td>40.68514</td>\n",
              "      <td>-73.95976</td>\n",
              "      <td>Entire home/apt</td>\n",
              "      <td>89</td>\n",
              "      <td>1</td>\n",
              "      <td>270</td>\n",
              "      <td>2019-07-05</td>\n",
              "      <td>4.64</td>\n",
              "      <td>1</td>\n",
              "      <td>194</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5022</td>\n",
              "      <td>Entire Apt: Spacious Studio/Loft by central park</td>\n",
              "      <td>7192</td>\n",
              "      <td>Laura</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>East Harlem</td>\n",
              "      <td>40.79851</td>\n",
              "      <td>-73.94399</td>\n",
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              "     id  ... availability_365\n",
              "0  2539  ...              365\n",
              "1  2595  ...              355\n",
              "2  3647  ...              365\n",
              "3  3831  ...              194\n",
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              "[5 rows x 16 columns]"
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      "cell_type": "code",
      "source": [
        "# checking the information of the data\n",
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
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        "id": "JxFKoMf5S2_I",
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            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 48895 entries, 0 to 48894\n",
            "Data columns (total 16 columns):\n",
            " #   Column                          Non-Null Count  Dtype  \n",
            "---  ------                          --------------  -----  \n",
            " 0   id                              48895 non-null  int64  \n",
            " 1   name                            48879 non-null  object \n",
            " 2   host_id                         48895 non-null  int64  \n",
            " 3   host_name                       48874 non-null  object \n",
            " 4   neighbourhood_group             48895 non-null  object \n",
            " 5   neighbourhood                   48895 non-null  object \n",
            " 6   latitude                        48895 non-null  float64\n",
            " 7   longitude                       48895 non-null  float64\n",
            " 8   room_type                       48895 non-null  object \n",
            " 9   price                           48895 non-null  int64  \n",
            " 10  minimum_nights                  48895 non-null  int64  \n",
            " 11  number_of_reviews               48895 non-null  int64  \n",
            " 12  last_review                     38843 non-null  object \n",
            " 13  reviews_per_month               38843 non-null  float64\n",
            " 14  calculated_host_listings_count  48895 non-null  int64  \n",
            " 15  availability_365                48895 non-null  int64  \n",
            "dtypes: float64(3), int64(7), object(6)\n",
            "memory usage: 6.0+ MB\n"
          ]
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      "cell_type": "markdown",
      "source": [
        "- From above information it is seen that data contains:\n",
        "\n",
        "  Rows = 48895 \n",
        "\n",
        "  Column = 16 ,  i.e we have 16 informational variables by which we can analyse"
      ],
      "metadata": {
        "id": "uEO6AsSvT67c"
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    {
      "cell_type": "code",
      "source": [
        "# checking the number of null data in each columns\n",
        "df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Wjutlr4gUuyY",
        "outputId": "84bf6512-2851-45b9-d09d-ca7e2c8a7f2c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id                                    0\n",
              "name                                 16\n",
              "host_id                               0\n",
              "host_name                            21\n",
              "neighbourhood_group                   0\n",
              "neighbourhood                         0\n",
              "latitude                              0\n",
              "longitude                             0\n",
              "room_type                             0\n",
              "price                                 0\n",
              "minimum_nights                        0\n",
              "number_of_reviews                     0\n",
              "last_review                       10052\n",
              "reviews_per_month                 10052\n",
              "calculated_host_listings_count        0\n",
              "availability_365                      0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "- From above null values information,  it seen that columns ' name ' & ' host_name ' contain less number of null values as compare to null values in the columns ' last_review ' & ' reviews_per_month '. \n",
        "- So we will replace the null values in the columns ' name ' & ' host_name ' with the \" Unavailable \".\n",
        "- Columns ' last_review ' & ' reviews_per_month ' contain so many null values so from them we can't conclude any beneficial information so that we willdrop them."
      ],
      "metadata": {
        "id": "Kkvyv-S0XYp-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Dropping the columns 'last_review' & 'reviews_per_month'\n",
        "df.drop(['last_review','reviews_per_month'],axis=1,inplace=True)"
      ],
      "metadata": {
        "id": "2l-Vlw1iXX_y"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Replacing the null values in columns of 'name' & 'host_name' with \"Unavailable\"\n",
        "df[\"name\"].fillna(\"Unavailable\",inplace=True)        # replacing null values of 'name' column\n",
        "df[\"host_name\"].fillna(\"Unavailable\",inplace=True)    # replacing null values of 'host_name' column"
      ],
      "metadata": {
        "id": "qdosPwaLZZ9i"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Now check the any null value present in data\n",
        "df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NBivdMGIafb5",
        "outputId": "cb8dd922-bb04-4915-fef2-2b3f4cbdc850"
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      "execution_count": null,
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id                                0\n",
              "name                              0\n",
              "host_id                           0\n",
              "host_name                         0\n",
              "neighbourhood_group               0\n",
              "neighbourhood                     0\n",
              "latitude                          0\n",
              "longitude                         0\n",
              "room_type                         0\n",
              "price                             0\n",
              "minimum_nights                    0\n",
              "number_of_reviews                 0\n",
              "calculated_host_listings_count    0\n",
              "availability_365                  0\n",
              "dtype: int64"
            ]
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          "metadata": {},
          "execution_count": 10
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    {
      "cell_type": "markdown",
      "source": [
        "- As seen above, we have cleaned the data.\n",
        "### Now, let's begin to find some beneficial infomation.\n",
        "   \n",
        "  1.First analyse the which host is the busy, for that we will  compare the host with the different variables i.e columns.\n",
        "  \n",
        "    1.1 Analyse based on the total number of reviews."
      ],
      "metadata": {
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      "cell_type": "code",
      "source": [
        "# Grouping the host_id and number_of reviews to obtain the total number of reviews for perticular host id\n",
        "busy_host1=df.groupby(\"host_id\")[\"number_of_reviews\"].sum().sort_values(ascending=False).reset_index()\n",
        "\n",
        "# Again grouping the host id and host name to obatin the name of perticular host id(owner)\n",
        "owner_name=df.groupby(\"host_id\")[\"host_name\"].unique().reset_index()\n",
        "\n",
        "# Now merge above both dataframe based on the host id and get top 10 id\n",
        "busy_host_id1=pd.merge(busy_host1,owner_name, on=\"host_id\", how=\"left\").set_index(\"host_id\").iloc[0:10]\n",
        "busy_host_id1\n"
      ],
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              "      <th></th>\n",
              "      <th>number_of_reviews</th>\n",
              "      <th>host_name</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>host_id</th>\n",
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              "      <th></th>\n",
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              "      <th>37312959</th>\n",
              "      <td>2273</td>\n",
              "      <td>[Maya]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>344035</th>\n",
              "      <td>2205</td>\n",
              "      <td>[Brooklyn&amp;   Breakfast    -Len-]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26432133</th>\n",
              "      <td>2017</td>\n",
              "      <td>[Danielle]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35524316</th>\n",
              "      <td>1971</td>\n",
              "      <td>[Yasu &amp; Akiko]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40176101</th>\n",
              "      <td>1818</td>\n",
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              "    <tr>\n",
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              "      <td>[Jj]</td>\n",
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              "    <tr>\n",
              "      <th>16677326</th>\n",
              "      <td>1355</td>\n",
              "      <td>[Alex And Zeena]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
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              "      <td>1346</td>\n",
              "      <td>[Randy]</td>\n",
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              "    <tr>\n",
              "      <th>219517861</th>\n",
              "      <td>1281</td>\n",
              "      <td>[Sonder (NYC)]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23591164</th>\n",
              "      <td>1269</td>\n",
              "      <td>[Angela]</td>\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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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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              "  "
            ],
            "text/plain": [
              "           number_of_reviews                         host_name\n",
              "host_id                                                       \n",
              "37312959                2273                            [Maya]\n",
              "344035                  2205  [Brooklyn&   Breakfast    -Len-]\n",
              "26432133                2017                        [Danielle]\n",
              "35524316                1971                    [Yasu & Akiko]\n",
              "40176101                1818                           [Brady]\n",
              "4734398                 1798                              [Jj]\n",
              "16677326                1355                  [Alex And Zeena]\n",
              "6885157                 1346                           [Randy]\n",
              "219517861               1281                    [Sonder (NYC)]\n",
              "23591164                1269                          [Angela]"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Now plot the abov result using bar plot\n",
        "plt.rcParams['figure.figsize'] = (10, 5)      # defining the size of the graph\n",
        "busy_host_id1.plot.bar(color=\"orange\")\n",
        "plt.title(\"Top 10 busiest host based on total number of reviews\")\n",
        "plt.xlabel(\"Host ID\")\n",
        "plt.ylabel(\" Total number of reviews\")\n",
        "plt.xticks(rotation=30)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 412
        },
        "id": "xuMhlF3Mssib",
        "outputId": "cb0d8a1b-cd6e-4621-c06e-438241e76269"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]),\n",
              " <a list of 10 Text major ticklabel objects>)"
            ]
          },
          "metadata": {},
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "[link text](https://)Result 1.1: By considering total number of reviews:\n",
        "\n",
        "              Host ID = 37312959          \n",
        "              Host name = Maya,  is the busiest host ( 2273 reviews)\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "9itL5d7e4m7d"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "1.2 Analyse based on number of properties listed"
      ],
      "metadata": {
        "id": "sd6TZkij6G4v"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Grouping the host_id and name of property to obatin number of properties listed by perticular owner(host)\n",
        "busy_host3=df.groupby(\"host_id\")[\"name\"].count().sort_values(ascending=False).reset_index()\n",
        "\n",
        "#Grouping the host id to obatin the host name\n",
        "owner_name=df.groupby(\"host_id\")[\"host_name\"].unique().reset_index()\n",
        "\n",
        "#Now merge both above dataframe to obtain the top 10 host of higher number of properties listed\n",
        "busy_host_id3=pd.merge(busy_host3,owner_name, on=\"host_id\", how=\"left\").set_index(\"host_id\").iloc[0:10]\n",
        "busy_host_id3\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "id": "7gvz-ZZk6YvS",
        "outputId": "bad2307f-7d25-43f6-b1a6-dc3491f48245"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-f3921216-b185-4fd7-8fe6-1708def290ec\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
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              "        vertical-align: middle;\n",
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              "\n",
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              "    }\n",
              "\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>host_name</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>host_id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>219517861</th>\n",
              "      <td>327</td>\n",
              "      <td>[Sonder (NYC)]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>107434423</th>\n",
              "      <td>232</td>\n",
              "      <td>[Blueground]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30283594</th>\n",
              "      <td>121</td>\n",
              "      <td>[Kara]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>137358866</th>\n",
              "      <td>103</td>\n",
              "      <td>[Kazuya]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16098958</th>\n",
              "      <td>96</td>\n",
              "      <td>[Jeremy &amp; Laura]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12243051</th>\n",
              "      <td>96</td>\n",
              "      <td>[Sonder]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>61391963</th>\n",
              "      <td>91</td>\n",
              "      <td>[Corporate Housing]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22541573</th>\n",
              "      <td>87</td>\n",
              "      <td>[Ken]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200380610</th>\n",
              "      <td>65</td>\n",
              "      <td>[Pranjal]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1475015</th>\n",
              "      <td>52</td>\n",
              "      <td>[Mike]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f3921216-b185-4fd7-8fe6-1708def290ec')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\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",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f3921216-b185-4fd7-8fe6-1708def290ec 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-f3921216-b185-4fd7-8fe6-1708def290ec');\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",
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              "          docLink.innerHTML = docLinkHtml;\n",
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              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "           name            host_name\n",
              "host_id                             \n",
              "219517861   327       [Sonder (NYC)]\n",
              "107434423   232         [Blueground]\n",
              "30283594    121               [Kara]\n",
              "137358866   103             [Kazuya]\n",
              "16098958     96     [Jeremy & Laura]\n",
              "12243051     96             [Sonder]\n",
              "61391963     91  [Corporate Housing]\n",
              "22541573     87                [Ken]\n",
              "200380610    65            [Pranjal]\n",
              "1475015      52               [Mike]"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Now plot the above result using horizontal bar\n",
        "plt.rcParams['figure.figsize'] = (10, 5)      # defining the size of the graph\n",
        "\n",
        "busy_host_id3.plot.barh(color=\"skyblue\")\n",
        "plt.title(\"Top 10 busiest host based on number of properties listed\")          \n",
        "plt.xlabel(\"Host ID\")\n",
        "plt.ylabel(\" Number of properties\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 367
        },
        "id": "vY3yW2GxDF4j",
        "outputId": "e056d6ea-76c5-4fa8-b11b-87446a679a0e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, ' Number of properties')"
            ]
          },
          "metadata": {},
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Result 1.2: By considering number of properties listed:\n",
        "\n",
        "             Host ID = 219517861\n",
        "             Host name = Sonder, listed highest number of properties (327 properties)"
      ],
      "metadata": {
        "id": "VokSq6cgEWv9"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "1.3 Busiest host group wise"
      ],
      "metadata": {
        "id": "2ej3-d4KfaMM"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Grouping the host_name and groups to obatin busiest host list w.r.t group\n",
        "host_area = df.groupby(['host_name','neighbourhood_group'])['calculated_host_listings_count'].count().reset_index()\n",
        "host_areas = host_area.sort_values(by='calculated_host_listings_count',ascending=False).head(20)\n",
        "host_areas"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 677
        },
        "id": "k3JO3wT0fjS_",
        "outputId": "0ab584bd-f844-4beb-c306-4e6984a04085"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
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              "      <th></th>\n",
              "      <th>host_name</th>\n",
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              "    <tr>\n",
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              "      <td>134</td>\n",
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              "      <td>Sarah</td>\n",
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              "      <th>431</th>\n",
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              "      <td>122</td>\n",
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              "    <tr>\n",
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              "      <td>105</td>\n",
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              "    <tr>\n",
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              "    <tr>\n",
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              "      <td>97</td>\n",
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              "    <tr>\n",
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              "      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-8f5b00df-2629-4572-9c40-8b93e9c421b4 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-8f5b00df-2629-4572-9c40-8b93e9c421b4');\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",
              "  "
            ],
            "text/plain": [
              "            host_name neighbourhood_group  calculated_host_listings_count\n",
              "13217    Sonder (NYC)           Manhattan                             327\n",
              "1834       Blueground           Manhattan                             230\n",
              "9742          Michael           Manhattan                             212\n",
              "3250            David           Manhattan                             202\n",
              "9741          Michael            Brooklyn                             159\n",
              "6808             John           Manhattan                             151\n",
              "3249            David            Brooklyn                             142\n",
              "7275             Kara           Manhattan                             135\n",
              "432              Alex           Manhattan                             134\n",
              "9856             Mike           Manhattan                             134\n",
              "12498           Sarah            Brooklyn                             133\n",
              "431              Alex            Brooklyn                             122\n",
              "3115           Daniel           Manhattan                             107\n",
              "9653          Melissa            Brooklyn                             105\n",
              "6807             John            Brooklyn                             104\n",
              "7546              Ken           Manhattan                             100\n",
              "3114           Daniel            Brooklyn                              97\n",
              "6582          Jessica            Brooklyn                              97\n",
              "13216          Sonder           Manhattan                              96\n",
              "6540   Jeremy & Laura           Manhattan                              96"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#ploting the above result using pivot plot\n",
        "host_areas.pivot(index='host_name',columns='neighbourhood_group',values='calculated_host_listings_count').plot(kind='bar',figsize=(15,8))\n",
        "plt.title('Busiest host Name with Respect to group')\n",
        "plt.xlabel('Host Name')\n",
        "plt.ylabel('Host Listing Count')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "WG0EANyef0Ln",
        "outputId": "12b4de1e-a511-48bd-cf0d-86d5b148e4b6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Result 1.3 : From above it is seen that, in Manhattan group Sonder NYC is the busiest host and in Brooklyn group Michael is busiest host"
      ],
      "metadata": {
        "id": "F6kbyaSvgAg-"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Result 1: From above both results it is seen that: \n",
        "\n",
        "         Host ID/Name = 219517861 / Sonder    &   37312959 / Maya \n",
        "         are the busiest host i.e this host has maximum number of airbnb bookings or customers"
      ],
      "metadata": {
        "id": "Fz-I_MDotTRC"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "2. Analysis of neighbourhhood group has max number of listing and its prices according to that."
      ],
      "metadata": {
        "id": "-Wr-DlqVVA40"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "1. Check which neighbourhood group has max number of  airbnb booking"
      ],
      "metadata": {
        "id": "H-s_dqdabZsD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#checking max number of airbnb booking area i.e neighbourhood group by taking value count\n",
        "busy_neighbourhood_group= df[\"neighbourhood_group\"].value_counts()\n",
        "busy_neighbourhood_group"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uVRRygc3ajZB",
        "outputId": "0ace2bd4-270b-48f8-a0d5-e3b9ebc7af13"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Manhattan        21661\n",
              "Brooklyn         20104\n",
              "Queens            5666\n",
              "Bronx             1091\n",
              "Staten Island      373\n",
              "Name: neighbourhood_group, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# now plot the above result by using percentage share and show separate max share area on the pie plot\n",
        "busy_neighbourhood_group.plot.pie(subplots=True,figsize=(12,6),explode=[0.1,0,0,0,0],autopct='%1.1f%%',shadow=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 392
        },
        "id": "QE_77MYqcNLm",
        "outputId": "5821eaea-4b89-4c1c-9de7-403331b9c458"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7fa67ca4d0d0>],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 18
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Result 2.1: From above pie chart it is seen that 'Manhattan' has max number of booking."
      ],
      "metadata": {
        "id": "GBy2T44wf0I2"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "2.2 Check the average booking price in the neighbourhood group"
      ],
      "metadata": {
        "id": "MQLy7F5Af_j8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#grouping the neighbourhood group and price by taking mean of price\n",
        "mean_bookingprice_of_group=df.groupby(\"neighbourhood_group\")[\"price\"].mean().reset_index(name=\"Avg booking price\")\n",
        "mean_bookingprice_of_group"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "LbGuzlUVaDjp",
        "outputId": "963c7f2d-224c-4bc3-836b-d740b8a81dc8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-cfc707d9-5592-4f9c-8ed0-e6a23e51cf0c\">\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>neighbourhood_group</th>\n",
              "      <th>Avg booking price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Bronx</td>\n",
              "      <td>87.496792</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Brooklyn</td>\n",
              "      <td>124.383207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Manhattan</td>\n",
              "      <td>196.875814</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Queens</td>\n",
              "      <td>99.517649</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Staten Island</td>\n",
              "      <td>114.812332</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-cfc707d9-5592-4f9c-8ed0-e6a23e51cf0c')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "      </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",
              "      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",
              "    [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-cfc707d9-5592-4f9c-8ed0-e6a23e51cf0c 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-cfc707d9-5592-4f9c-8ed0-e6a23e51cf0c');\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",
              "  "
            ],
            "text/plain": [
              "  neighbourhood_group  Avg booking price\n",
              "0               Bronx          87.496792\n",
              "1            Brooklyn         124.383207\n",
              "2           Manhattan         196.875814\n",
              "3              Queens          99.517649\n",
              "4       Staten Island         114.812332"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#now plot the above result on bar plot\n",
        "mean_bookingprice_of_group.plot.bar(x=\"neighbourhood_group\", y=\"Avg booking price\", width=0.4,color=\"tomato\")\n",
        "plt.xticks(rotation=30)\n",
        "plt.xlabel(\"Neighbourhood group\")\n",
        "plt.ylabel(\"Avg booking price\")\n",
        "plt.title(\"Average booking price in neighbourhood group\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 399
        },
        "id": "6oyYj9Hkgnum",
        "outputId": "2c87856d-bedf-424c-b431-51dfc8736d1d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Average booking price in neighbourhood group')"
            ]
          },
          "metadata": {},
          "execution_count": 20
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Result 2.2 : From above it is seen that airbnb booking in the 'Manhattan' is the expensive amongs the group."
      ],
      "metadata": {
        "id": "ouMeLWw2l0y2"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "2.3  Now analyse the room type preffered in the neighborhood group."
      ],
      "metadata": {
        "id": "ROz5P0RFmVp6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# grouping the neighbourhood group and room type by taking count of room type\n",
        "room_type_preffered=df.groupby(\"neighbourhood_group\")[\"room_type\"].value_counts().unstack()\n",
        "room_type_preffered"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "_rXGTeF2mVHw",
        "outputId": "52823791-f0ae-45e6-cb29-dfaca4666060"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>room_type</th>\n",
              "      <th>Entire home/apt</th>\n",
              "      <th>Private room</th>\n",
              "      <th>Shared room</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>neighbourhood_group</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Bronx</th>\n",
              "      <td>379</td>\n",
              "      <td>652</td>\n",
              "      <td>60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Brooklyn</th>\n",
              "      <td>9559</td>\n",
              "      <td>10132</td>\n",
              "      <td>413</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Manhattan</th>\n",
              "      <td>13199</td>\n",
              "      <td>7982</td>\n",
              "      <td>480</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Queens</th>\n",
              "      <td>2096</td>\n",
              "      <td>3372</td>\n",
              "      <td>198</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Staten Island</th>\n",
              "      <td>176</td>\n",
              "      <td>188</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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            ],
            "text/plain": [
              "room_type            Entire home/apt  Private room  Shared room\n",
              "neighbourhood_group                                            \n",
              "Bronx                            379           652           60\n",
              "Brooklyn                        9559         10132          413\n",
              "Manhattan                      13199          7982          480\n",
              "Queens                          2096          3372          198\n",
              "Staten Island                    176           188            9"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# plot the above result neighbourhood group wise using joint bar plot\n",
        "room_type_preffered.plot(kind='bar',figsize=(10,5))\n",
        "plt.xticks(rotation=45)\n",
        "plt.title(\"Room type preffered in neighbourhood group ('groupwise')\")\n",
        "plt.xlabel('Neighbourhood group')\n",
        "plt.ylabel('No of booking')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 411
        },
        "id": "4xSjwIpkoJKh",
        "outputId": "35a3816d-f557-4c4c-a181-4f965060c462"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'No of booking')"
            ]
          },
          "metadata": {},
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# obatain the above result room type wise in diffrent groups\n",
        "ax=sns.countplot(x=\"room_type\",hue=\"neighbourhood_group\",data=df)\n",
        "plt.title(\"Room type preference in neighbourhood groups ('room type wise')\")\n",
        "plt.xlabel(\"Room Type\")\n",
        "plt.ylabel(\"No of bookings\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 367
        },
        "id": "pt4IGQmKR3o_",
        "outputId": "0d3a33ca-6da8-4bc0-8adb-6ecfb5943100"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'No of bookings')"
            ]
          },
          "metadata": {},
          "execution_count": 23
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Result 2.3 : From above graphs it is seen that in Manhattan group of cities,maximum customer prefer to stay in 'Entire home/apt' and in Brooklyn group of cities  maximum customer prefer to stay in 'Private Room' and customer also prefer to stay in 'Shared room' mostly in Manhattan group of cities"
      ],
      "metadata": {
        "id": "EgBTcp9WtKuB"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "2.4 Checking the maximum number of customer based on reviews for neighbourhhood groups\n"
      ],
      "metadata": {
        "id": "MEX8qU-9r9KQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# grouping the number of reviews with respect to  neighbourhood groups\n",
        "traffic_in_group=df.groupby('neighbourhood_group')['number_of_reviews'].sum().sort_values(ascending=False)\n",
        "traffic_in_group"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "u3r_mH-5rxAl",
        "outputId": "65717f37-fb11-4090-ec7e-2d73e65aa1e8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "neighbourhood_group\n",
              "Brooklyn         486574\n",
              "Manhattan        454569\n",
              "Queens           156950\n",
              "Bronx             28371\n",
              "Staten Island     11541\n",
              "Name: number_of_reviews, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#plot the above results using bar plot\n",
        "traffic_in_group.plot.bar()\n",
        "plt.title(\" No of reviews in diffrent neighbourhood_group\")\n",
        "plt.ylabel('Number of reviews')\n",
        "plt.xlabel('Neighbourhood group')\n",
        "plt.xticks(rotation=30)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 399
        },
        "id": "KiVOh5VfstHF",
        "outputId": "3ddfe19f-8fef-4f5f-90b9-d04c12cd927b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([0, 1, 2, 3, 4]), <a list of 5 Text major ticklabel objects>)"
            ]
          },
          "metadata": {},
          "execution_count": 25
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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gTpIkaUAM7iRJkgbE4E6SJGlADO4kSZIGxOBOkiRpQAzuJEmSBsTgTpIkaUAM7iRJkgbE4E6SJGlADO4kSZIGxOBOkiRpQAzuJEmSBsTgTpIkaUAM7iRJkgZk1oO7JMsn+XmSr/f1Oyf5aZKzk3w+yUo9feW+fnbfvmDkHK/v6WcmecJI+nY97ewk+4ykT3gNSZKkoVsSJXevAH49sv5u4P1VdVfgcmD3nr47cHlPf3/fjySbA88C7gVsB/xPDxiXBz4KPBHYHNi57zvVNSRJkgZtVoO7JBsB2wMH9vUAjwG+2Hc5BHhKX96pr9O3P7bvvxNweFVdV1XnAmcDW/fb2VV1TlVdDxwO7LSQa0iSJA3abJfcfQB4HXBTX18b+GtV3dDXLwA27MsbAucD9O1X9P1vTh93zGTpU11DkiRp0GYtuEvyZODPVXXKbF3jtkqyZ5KTk5x8ySWXzHV2JEmSbrPZLLl7KLBjkvNoVaaPAT4IrJFkhb7PRsCFfflCYGOAvv2OwKWj6eOOmSz90imucQtVdUBVbVlVW6677rozf6SSJEnzxKwFd1X1+qraqKoW0DpEfLeqngN8D3ha321X4Kt9+ci+Tt/+3aqqnv6s3pv2zsBmwInAScBmvWfsSv0aR/ZjJruGJEnSoM3FOHd7A69Kcjatfdwne/ongbV7+quAfQCq6nTgCOAM4JvAXlV1Y29T9zLgGFpv3CP6vlNdQ5IkadBWWPgut11VHQcc15fPofV0Hb/PtcDTJzn+ncA7J0g/Gjh6gvQJryFJkjR0zlAhSZI0IAZ3kiRJA2JwJ0mSNCAGd5IkSQNicCdJkjQgBneSJEkDYnAnSZI0IAZ3kiRJA2JwJ0mSNCAGd5IkSQNicCdJkjQgBneSJEkDYnAnSZI0IAZ3kiRJA2JwJ0mSNCAGd5IkSQNicCdJkjQgBneSJEkDYnAnSZI0IAZ3kiRJA2JwJ0mSNCAGd5IkSQNicCdJkjQgBneSJEkDYnAnSZI0IAZ3kiRJA7LQ4C7JQ5Pcri8/N8n7kmw6+1mTJEnSoppOyd3HgGuS3A94NfA74NBZzZUkSZJmZDrB3Q1VVcBOwEeq6qPA6rObLUmSJM3ECtPY56okrweeCzwiyXLAirObLUmSJM3EdErunglcB+xeVX8ENgL+e1ZzJUmSpBmZTsnd9sDXquosgKr6A7a5kyRJmpemE9xtAvxvkgXAKcD3ge9X1S9mMV+SJEmagYVWy1bVW6rqMcC9gB8ArwV+NtsZkyRJ0qJbaMldkjcBDwVuD/wceA0tyJMkSdI8M51q2acCNwBHAccDP66q62Y1V5IkSZqR6VTLbgE8DjgReDzwyyQ/nO2MSZIkadFNp1r23sDDgUcCWwLnY7WsJEnSvDSdatn9acHch4CTquofs5slSZIkzdRCg7uqenKSVYFNDOwkSZLmt4W2uUuyA3Aq8M2+fv8kR852xiRJkrTopjP92FuBrYG/AlTVqcCdZzFPkiRJmqHpBHf/qKorxqXVbGRGkiRJt810OlScnuTZwPJJNgP+AzhhdrMlSZKkmZhOyd3LaVOPXQd8DrgSeOXCDkqySpITk/wiyelJ9uvpd07y0yRnJ/l8kpV6+sp9/ey+fcHIuV7f089M8oSR9O162tlJ9hlJn/AakiRJQzedQYyvqao3VtVWVbVlX752Gue+DnhMVd0PuD+wXZJtgHcD76+quwKXA7v3/XcHLu/p7+/7kWRz4Fm0AHM74H+SLJ9keeCjwBOBzYGd+75McQ1JkqRBmzS4S/KBfv+1JEeOvy3sxNX8ra+u2G8FPAb4Yk8/BHhKX96pr9O3PzZJevrhVXVdVZ0LnE3r4LE1cHZVnVNV1wOHAzv1Yya7hiRJ0qBN1ebu0/3+PTM9eS9dOwW4K62U7XfAX6vqhr7LBcCGfXlD2uwXVNUNSa4A1u7pPxk57egx549Lf1A/ZrJrSJIkDdqkwV1VndIX1waOqqrrFvXkVXUjcP8kawBfBu4xo1zOkiR7AnsCbLLJJnOcG0mSpNtuOh0qdgB+m+TTSZ6cZDo9bG+hqv4KfA94MLDGyDk2Ai7syxcCGwP07XcELh1NH3fMZOmXTnGN8fk6oLcj3HLddddd1IclSZI070ynQ8VutGrVLwA7A79LcuDCjkuybi+xo09f9njg17Qg72l9t12Br/blI/s6fft3q6p6+rN6b9o7A5sBJwInAZv1nrEr0TpdHNmPmewakiRJgzatUriq+keSb9A6RKxK66DwwoUctj5wSG93txxwRFV9PckZwOFJ3gH8HPhk3/+TwKeTnA1cRgvWqKrTkxwBnAHcAOzVq3tJ8jLgGGB54KCqOr2fa+9JriFJkjRoCw3ukjwReCbwKOA44EDgGQs7rqpOAx4wQfo5tJ6u49OvBZ4+ybneCbxzgvSjgaOnew1JkqShm07J3S7A54EXzaRThSRJkpac6bS525lWtflwaO3nkqw+2xmTJEnSoltocJdkD9qAwP/bkzYCvjKbmZIkSdLMTGcolL2Ah9LmlKWqzgLuNJuZkiRJ0sxMJ7i7rk/vBdw8Bl3NXpYkSZI0U9MJ7o5P8gZg1SSPp41397XZzZYkSZJmYjrB3d7AJcAvgRfRhh5502xmSpIkSTMz5VAofQDi06vqHsAnlkyWJEmSNFNTltz1mSDOTLLJEsqPJEmSboPpDGK8JnB6khOBq8cSq2rHWcuVJEmSZmQ6wd2+s54LSZIkLRYLDe6q6vglkRFJkiTddtPpLStJkqSlhMGdJEnSgEwa3CX5Tr9/95LLjiRJkm6LqdrcrZ/kIcCOSQ4HMrqxqn42qzmTJEnSIpsquHszrafsRsD7xm0r4DGzlSlJkiTNzKTBXVV9Efhikn2r6u1LME+SJEmaoekMhfL2JDsCj+hJx1XV12c3W5IkSZqJhfaWTfIu4BXAGf32iiT/b7YzJkmSpEU3nRkqtgfuX1U3ASQ5BPg58IbZzJgkSZIW3XTHuVtjZPmOs5ERSZIk3XbTKbl7F/DzJN+jDYfyCGCfWc2VJEmSZmQ6HSo+l+Q4YKuetHdV/XFWcyVJkqQZmU7JHVV1MXDkLOdFkiRJt5Fzy0qSJA2IwZ0kSdKATBncJVk+yW+WVGYkSZJ020wZ3FXVjcCZSTZZQvmRJEnSbTCdDhVrAqcnORG4eiyxqnactVxJkiRpRqYT3O0767mQJEnSYjGdce6OT7IpsFlVfTvJasDys581SZIkLaqF9pZNsgfwReB/e9KGwFdmM1OSJEmamekMhbIX8FDgSoCqOgu402xmSpIkSTMzneDuuqq6fmwlyQpAzV6WJEmSNFPTCe6OT/IGYNUkjwe+AHxtdrMlSZKkmZhOcLcPcAnwS+BFwNHAm2YzU5IkSZqZ6fSWvSnJIcBPadWxZ1aV1bKSJEnz0EKDuyTbAx8HfgcEuHOSF1XVN2Y7c5IkSVo00xnE+L3Ao6vqbIAkdwGOAgzuJEmS5pnptLm7aiyw684Brpql/EiSJOk2mLTkLslT++LJSY4GjqC1uXs6cNISyJskSZIW0VTVsjuMLP8JeGRfvgRYddZyJEmSpBmbNLirqt2WZEYkSZJ0202nt+ydgZcDC0b3r6odZy9bkiRJmonpdKj4CnAe8GFaz9mx25SSbJzke0nOSHJ6klf09LWSHJvkrH6/Zk9Pkg8lOTvJaUm2GDnXrn3/s5LsOpL+wCS/7Md8KEmmuoYkSdLQTSe4u7aqPlRV36uq48du0zjuBuDVVbU5sA2wV5LNaTNefKeqNgO+09cBnghs1m97Ah+DFqgBbwEeBGwNvGUkWPsYsMfIcdv19MmuIUmSNGjTCe4+mOQtSR6cZIux28IOqqqLq+pnffkq4NfAhsBOwCF9t0OAp/TlnYBDq/kJsEaS9YEnAMdW1WVVdTlwLLBd33aHqvpJnzHj0HHnmugakiRJgzadQYzvAzwPeAxwU0+rvj4tSRYAD6BNYbZeVV3cN/0RWK8vbwicP3LYBT1tqvQLJkhnimuMz9eetFJCNtlkk+k+HEmSpHlrOsHd04F/rarrZ3KBJLcHvgS8sqqu7M3iAKiqSjKr89ROdY2qOgA4AGDLLbd0vlxJkrTUm0617K+ANWZy8iQr0gK7z1bV//XkP/UqVfr9n3v6hcDGI4dv1NOmSt9ogvSpriFJkjRo0wnu1gB+k+SYJEeO3RZ2UO+5+kng11X1vpFNRwJjPV53Bb46kr5L7zW7DXBFr1o9Btg2yZq9I8W2wDF925VJtunX2mXcuSa6hiRJ0qBNp1r2LTM890NpbfV+meTUnvYGYH/giCS7A78HntG3HQ08CTgbuAbYDaCqLkvydv455dnbquqyvvxS4GDajBnf6DemuIYkSdKgLTS4m+awJxMd90Mgk2x+7AT7F7DXJOc6CDhogvSTgXtPkH7pRNeQJEkauunMUHEVrXcswErAisDVVXWH2cyYJEmSFt10Su5WH1vubdt2og1KLEmSpHlmOh0qbtYHGP4KbWBhSZIkzTPTqZZ96sjqcsCWwLWzliNJkiTN2HR6y+4wsnwDcB6talaSJEnzzHTa3O22JDIiSZKk227S4C7Jm6c4rqrq7bOQH0mSJN0GU5XcXT1B2u2A3YG1AYM7SZKkeWbS4K6q3ju2nGR14BW0WSMOB9472XGSJEmaO1O2uUuyFvAq4DnAIcAWVXX5ksiYJEmSFt1Ube7+G3gqcABwn6r62xLLlSRJkmZkqkGMXw1sALwJuCjJlf12VZIrl0z2JEmStCimanO3SLNXSJIkae4ZwEmSJA2IwZ0kSdKAGNxJkiQNiMGdJEnSgCx0bllJGpIF+xw111mYVeftv/1cZ0HSHLPkTpIkaUAM7iRJkgbE4E6SJGlADO4kSZIGxOBOkiRpQAzuJEmSBsTgTpIkaUAM7iRJkgbE4E6SJGlADO4kSZIGxOBOkiRpQAzuJEmSBsTgTpIkaUAM7iRJkgbE4E6SJGlADO4kSZIGxOBOkiRpQAzuJEmSBsTgTpIkaUAM7iRJkgbE4E6SJGlADO4kSZIGxOBOkiRpQAzuJEmSBsTgTpIkaUAM7iRJkgZk1oK7JAcl+XOSX42krZXk2CRn9fs1e3qSfCjJ2UlOS7LFyDG79v3PSrLrSPoDk/yyH/OhJJnqGpIkScuC2Sy5OxjYblzaPsB3qmoz4Dt9HeCJwGb9tifwMWiBGvAW4EHA1sBbRoK1jwF7jBy33UKuIUmSNHizFtxV1feBy8Yl7wQc0pcPAZ4ykn5oNT8B1kiyPvAE4NiquqyqLgeOBbbr2+5QVT+pqgIOHXeuia4hSZI0eEu6zd16VXVxX/4jsF5f3hA4f2S/C3raVOkXTJA+1TVuJcmeSU5OcvIll1wyg4cjSZI0v8xZh4pe4lZzeY2qOqCqtqyqLdddd93ZzIokSdISsaSDuz/1KlX6/Z97+oXAxiP7bdTTpkrfaIL0qa4hSZI0eEs6uDsSGOvxuivw1ZH0XXqv2W2AK3rV6jHAtknW7B0ptgWO6duuTLJN7yW7y7hzTXQNSZKkwVthtk6c5HPAo4B1klxA6/W6P3BEkt2B3wPP6LsfDTwJOBu4BtgNoKouS/J24KS+39uqaqyTxktpPXJXBb7Rb0xxDUmSpMGbteCuqnaeZNNjJ9i3gL0mOc9BwEETpJ8M3HuC9EsnuoYkSdKywBkqJEmSBsTgTpIkaUAM7iRJkgbE4E6SJGlADO4kSZIGxOBOkiRpQAzuJEmSBsTgTpIkaUAM7iRJkgbE4E6SJGlADO4kSZIGxOBOkiRpQAzuJEmSBsTgTpIkaUAM7iRJkgbE4E6SJGlADO4kSZIGxOBOkiRpQAzuJEmSBsTgTpIkaUAM7iRJkgbE4E6SJGlADO4kSZIGxOBOkiRpQAzuJEmSBsTgTpIkaUAM7iRJkgbE4E6SJGlADO4kSZIGxOBOkiRpQAzuJEmSBsTgTpIkaUBWmOsMSJI0XQv2OWquszBrztt/+7nOggbCkjtJkqQBMbiTJEkaEIM7SZKkATG4kyRJGhCDO0mSpAExuJMkSRoQgztJkqQBMbiTJEkaEAcxliRJs27IA1DD/BqE2pI7SZKkATG4kyRJGpDBBndJtktyZpKzk+wz1/mRJElaEgYZ3J4dNecAABh/SURBVCVZHvgo8ERgc2DnJJvPba4kSZJm3yCDO2Br4OyqOqeqrgcOB3aa4zxJkiTNulTVXOdhsUvyNGC7qnphX38e8KCqetm4/fYE9uyrdwfOXKIZXbLWAf4y15nQjPjaLd18/ZZevnZLt6G/fptW1boTbVimh0KpqgOAA+Y6H0tCkpOrasu5zocWna/d0s3Xb+nla7d0W5Zfv6FWy14IbDyyvlFPkyRJGrShBncnAZsluXOSlYBnAUfOcZ4kSZJm3SCrZavqhiQvA44BlgcOqqrT5zhbc22ZqH4eKF+7pZuv39LL127ptsy+foPsUCFJkrSsGmq1rCRJ0jLJ4E6SJGlADO4kSZIWUZK15joPkzG406T6NG6SlpAkmes8SFq4JHcBPpdk67nOy0QM7nQrSZYDqKobk6yaZJW5zpNum4kCdQOJ+SXJ8tV7uPnHav4a+9wkWaHfPy7Jo+c2V1pSxn4fgXOB44Hnz11uJmdwp5uNfWlV1U19/XnAb4H39WUtZUZe0xv7+nPH/mmWXeXnlf5nasUkHwBePhY8aH4Z+9xU1Q096bnAA+YuR1qSxn4fgYfSYqjNkzxuDrM0IYM73Wyk1GDTJJ8H7gI8Gfg2sEuSe81l/rToRl7TeyX5BrAr8F9JXt/T/Q6YI+Of+yT3Bk4BbgIOHwkeNMfGl6Qm2SvJF5I8Bfg9cOJE+2kYxtdyJHkNcCBwBXADsEeSFecib5Pxi30ZN/qmTbJ6kv2AC4CHAStX1S+AY4HvA6+am1xqUUzwQ/Q84L+BH1bV44FXAK9Lcsequsnq2SUvyXIjJQBj1gcOAz4A3JRkqyRrLPncacxoE5W+vknf9GXg68C/Aa+kl9z10lc/TwMx8vrXSNpqwNbA9lX1YeA/aUHei+Ykk5MwuFsGJVkuyYZwq6q5FWlv2lWA/WjFzlTVVcDhwIZJnraEs6tpGq2CTbJakvv3Td8F/gaslOT2PWA/Cvjo2KFLPrfLth5Ur5/ks0lem+QewF+A+9EChzcAnwX2TrLBXOZ1WTbSROVxSU4BDkuyW1VdVFWHAG8GrgeelOTQJE8H1pnDLGsxGnn9n53kfUnuWlXXACsBY7+F5wDn0d4DG85NTm/N4G4Z0/917AvsnmSVJI8ZCdjWAG4EbqqqA4DVkuzet/0e+ArgD808M9Y2a6QK9j+BHwKvSvJa2r/KrwBrA5v1w14MPDvJVhOUIGkxm6AK9snA24DzgQI+DfwC2AN4YlW9EtiN9pn845LN7bJt9LVKcvs+leVrgOcBbwFekGSbXg13EfAl4E3At4BHASsv8UxrViT5194G9inA7YH/TrIV8GHgkUk2qKqraZ/hNYAd5y63t2RwtwxJskL/1/Eb2hvxobR/IPsmeVJVnQNcB+zcD3kT8JYkd6iq64EDq+pDc5F33VovnXsIcMeR9R2BTYAHAT+gNfbeg1byugKwTZJ1q+pvwLOBS6xGmj3pRgPoJPcFPghcW1X7VNV7aP/89++vy01Jngm8G7gGv6eXiJEquJtGmjasDPwrsFFVnVFV3wF+BDyV9t25ANiyqk6pqs9U1V5VdcEcZF+30QTNWe5Aq2rdsaqeUVV7AmcBj6b1lP0l8NkkhwNPAF5WVR9bwtmelF8aA5fkDkk2hta7K8nqwDdppTkPB46h/St9XJJPAN+g/yZV1Tdp7e0WjB3fz2kwMIdGelFeCzyeVkL3LVqwdgKtquj/AS8EPgdsA9y1Lz+Jf76eh1fVefaanT3VJXlgkg8neQTwK+AjwBpJ7th3fQvwlN6m6260EoA3VtWr7Vgxu0aDur7+CuBbSd4P3A74FPCTJM/qh/wPcE9gO1qThk8lWcHOFEuv/ns31q7yaUk2qaoraW1g/57k8X3Xr9GC/XtW1euAvWnDoTyuqn42F3mfjMHdgPXG2K+mNfgdq5L9JrAW7Q25DvDUqjqWFuCtTasq2myku//uVXXa6HkNBuZOko2AR8DNP0aXAq8Dzq6qA6vqL8DGwDpV9SBaEHF3YO+qOh74r6o6aW5yv2yYoGfdPsCHgJ8DzwTeD3wC2Ah4cNr4dmfQPpP7VtUJVfWcqjp+rORvCT+EZcb4ji29CnY74CU96T3AP2i9YR+eZP2q+gPwY1oJ+XlV9dGqumEsONDSoXdYeim037QkOyX5EfBE2ogCL+3tkw8Cdun7/QD4M7Bdr5I9sao+Nh//gBncDdDIP9G/0r6UbpfkkbT2VpdU1blVdRytIehWSe7Vv+BeQutI8eCMdOv2x2VeWZlWynpwkuNonSU+Cvw2yXp9nzsCT0+yMq366BfACb1a/gdzkellwSQ961YBVquqh9JKWh8G/KFXv36R9qMx9rq9jH8GFWOlCeWfqdnTq2D/JclRSZ5Pa1f19ar6bVX9Z9/t/rT2dNDaQQK8q6re35uraOm0Cm3UgPX7+r2BvYDX0nquv6PXdB0GLJ9kj77fgcBHquqiJZ3hRWFwNzC9FGC0gfxPgN/R/o08nNYDb8wxtHZYj+k/JH+iNcQ/CaixoM4fl7nTC25GP6d/oLX5eDTwiV7icxCwFfAQgKr6MXAIrQphL1pbrk/Ox3+XQzJSrbd9ktcnuXNVXUv7l38usC2wc1W9N8laVfVR2o/Ivfrx1/WmE7cKEnXbJVk+yb5JnpE2dRRJHkPrbPStqjqYVpvxjyS374d9Ddirqs6jlazOq6o3LZrRqvP+R/crwNt70vtopenH0YaO+h7w0aq6uC8/NslKVfWHqjpziWZ8BgzuBqYPg7F2kv17o+zlaO3o1gPeCTy3F0cvV1WnA2f3bf/ST/EK2j/Vm/xxmVsjJTdjpQsPrKp/AC+n/ZtcKckqvdr8F8BDkjwlyStp1eu7VNWDqurXc/gwBm20VDttqr7P0noiXw28O21ojI8CF1bV86vqjCT3Ad7YSwX+vTeLuFnZe3mxS/JCWin3ffvtwL7palobqr/09RNo7Vi37etrAEf35S/0dsgG3kuh/ps31q7uqT35fcAWSR5WVX+njVd4QFV9nfa7+dy0wcUPAp63NJXUGtwt5XLrIRYeTPsyCvBIWiP6q2glcsfSesq+Ejg6ySeBI4A3938n0AbmfKI/MHNv7AckydtpbSV3TfI+WoP8E4EH0jpLQGv0fT6wD/AvVfWnqnIIjVnW2+qMfQbXo7V93AFYl9aJ5VJa6c81ST7VOy0dBvy2qq6qqsvmJOPLkCR3Ag6glcA9HfgYrRnDSlX1U9oP/A4AVfV/wHeAHZMcDzydVrpjQLcUSnLPJGPt5W5KG6/weOAlI+0nD6WNDAGtPfq6aQO/3xt4L3BFVd3Y/1gvNeL7denUSwwyPghL8mzgoVW1V18/jPaP9fvA7sDFVfWBXmqwVlX9vu+3gtV2c6//4Fzfl0Nr3P2Qqto3yYtps4QcDLyL1iP2GlrP56tpgfqN1Ya70SwYK00dWb8X8B+01yO04WcupwUI+1XV5b0j00q0AYq3Bj7W29xpCUlyIHBsVX0+ybG0moqjaK/bHYD9+/aD03qjr0zrEXnynGVat0n/07UD7Ttz16o6rxdofKmqjh7ZZxXae+G9tBqQXWltld80tt/SyOBuKdeLjJ9Dayf3FVqV0HrA+6rqiiTbAh+sqnsmeQ5wD1p7gr/1fzITTYOkJaR/udyJFgi8qKfdB7imqn7XG+SvQhvz7G606oEX9tt1tNf7McDLy16ws6YHcX/p7VJJsqD/WIT2ufs6rWT89bR/+q/r+z2F1q7ukNGg28/dkpXkdsBfgV/T2h0fAvwXbYrFZybZGXgpbUyzy+cup1qckqxDmx5sBVqtxteBM2nzN68J/J3WhGUrWvOJuw6lkMPgbiky/gehl9K9lvZltR2tse/3gecDH6iqHyZZizaa9vNovfYsMZiHklxNC9RWoY159lPaXLDvT3I34DVVtWcP9k6g9bh8Su9A4xAMsyTJprQv/fVp1d5js31sDxxUVSekzTaxC+1P0+q0AYoPA7agted6TVV9bw6yrxFJdgN2qKqn9vUVadXm96H9yD+Z1q7uqrnLpRa3JFvTxv58La0p2hOA39JmldgD+N+q+kavGTkYuG4IVfC2uVuKjPTG2zvJw2jteg6uNsL9zrRed5fT2te9vBdBnwCcVlU3jQV249vpackb67U10iD/2bQgYt2q2ojWRuheSbajDW3ykLQ5Rl9G67l1VD/W0p9Z0psufAL4cVU9kFa9cx2tdO7XtAGh6Y2v/w48q6q+S/sj9QfghKp6oIHdvHEIsHWSu/b1LWjV51dW1Z+r6iADu6VTJhhAeuS79Qzad+beVXV6Vb2vf2Z/Qyu9Wx6gqj5eVdcOIbCDVlSpeap3jrgc+H1V/T3JZrQJxVeiDWOyKfCrJKtV1SVpAzC+uqqemuSrtNKF91YbLuNmVgfNnbEvnJHSto2TXFBVX01yKq2TBLRS2E1ovSn3SPJ5WpXs8rT2I/N6jKWBeABwaVW9E6Cqzkkb5PYbtIA7Sf6tqr4M/B9tpoJv9t6vp46dxCrY+aE3Q3k6cESSr9OC8/+xGnbpNVZzUW2UiA1oY7me1JtAhNYP5m/99d4iybOq6vAkH6e1f/3vHugNjsHdPJRkAa1q7kG0ceqK1hni7sAzaO1CTk3ycODBtEDgVFop3Zq9c8S5tNkJxkrqaij/SJZmIz1g70yrLl8bOJk2vMmLgZOSrNGD9Z/SShpeUVVvT7KmP0RL1A3AXcZW+ufq+iQHA/vSqnpekuRG2nRhh9F6Mt+Cgd38UVU/TnIFfW7tqrpurvOkmat/Dm3yZNr36a+Bi5O8qaouHmm2ci6tvd1LknyZ1gb2xXOW8SXA6rl5pgd25wA/qqrNaY091+lVRN8FPk2bwgha8HY58PokB9FKdn442iC09+5zzLo5NFplkGZ74OPAZ2jtP7ZOsksvYf0srSoQ2iTVR9GqFTCwW+IuAM7oPxyjvkZrs3MabeaClwPfqaqX1T+HFNL89biq+g8Du6VPkuXGaj/6d+mqSX4C/BttkP5n0jrO7A3/DP76CAQ/pA17sny1gd4HzeBunqk2EvpptNHQAV5Ea6T9kF7U/HFgvSSP7QHb2JAYpwBbVdVXx53PoG6O5J8zDYx2eFgB2IA28fiZ1San/gCwQ9qk8S8D/j19UM2q+kqNG+RWS8yFtAD78b3UdOxP0xbAqVV1RlW9p6oeX1WHgVP1LQ3sgLR0Gi2oSHJ3YL1qAw9/BdgSuITW9vUQWnvlbfpxKwBU1fnVZupZJoaKMribn/4N+GGSr9Ha/RwM7Jfk7VV1Kq0Eby9opTlV9Ytqk1dfOlHDUi1ZSdaAW3SAeVySbyV5CW1gzENpbbSe2PcbG2h69/4P82m0qgUDhTnUg4BPAysChyS5b2+z9SnaILevS7IS3KItpX+mpMVo5E9yJVm9N4s4CHhlkv+sqv1p7eu27X/Afktrk/72ftwghjZZVA6FMk8l+QiwflX9e1+/J610br1+exXwX72kb+yY+OMyN/qP+0q0dler0DpCXJtkX+BxwFtpDXi3q6pHp40/+AzgM1V1XNocl8+hdYj565w8CE0oycq0AU5XonVy+QitY8ufl4XqHWkupA0BtXyNTJ+Y5LnAGlX1kbTZXu5Dm2f7abRxCh/WO1csoM3QdCgsm3+6DO7mqbRBN88DNu5BwgrAl4CXAH+0kfb8lOR7wIa0QaQ/nmQLWmeXlwAvoFXLfqmq3pbkjcAC4KW1lE1tsyzKyOwhkmZXkq2A9wAfoo1H9yzaNGGr0wo4bgBe2zsP0jugHV1V+81NjucXq2Xnqaq6mvZGfl+ShwA/Bi6ilRaMVff5+s2xJE9Oct++vBpt3KzDgO2T3KWqfkYrkXsSrWfza4HnJ1mPNqTGD+ltg+fkAWhR/AP83EmzZbRZUbUZdzahlZq/q9donAZsSxtA/GlVdW6SR/emMLsB356LfM9HfknNb5+gDW77X8B/VtVLRtsPWHo3t3qAdiTw4SQb9Ia6Y9OFHQ28su96N+DrvdRnA+B64AVV9bOqOqSqrl8Wqw2WNmOvkZ87afEa7XyWZOUk6/Taq7fRSujGplY8HfgmsE2SNZN8iBb8bdw7OP1oLvI/H1ktO88lWbuqLh1Zd0DUeSTJ/rSSuXcAV9Mmjn83rV3Wa2jjod0H2Ik2h+w/gFdV1a3GQ5OkZcn4duJJXgHsShv+6ZCqOjbJh4E1q+q5fZ9NaUHfnWi92d9QTqt5KwZ3S4k4h+i8lGRV4E+0xrv70b6UrgfeR/uSun9V7ZY2u8gjq+rAOcusJM0DfdzWB1TV90fSXksbqH9P2vBej6YNDXUGrTp2Z9p0YddX1feSrF5OFzcpgzvpNkqbcPoutOrzT/TlrYGNaFUG762q4yc/gyQNX5J/AW6oqr8k+TatN+t2tOG+TqTNxrQfsA3we+C8qto7ybNpAxTfldZE6Vtzkf+lidOPSbfdAcD5/f7fgEcAN9K+nF5QVX+Zw7xJ0pzqHSX2A54O7AN8mTYl2CeAN40Fa0meBKxTVdskeSBwVJJfVNVhSb7nDDDTZ4cK6TbqbSCfBhxazfG9k8T1BnaSlmVJ1qUN2r4Obeq3L/dg73O06tY/jOy+Im0GGIB7AGcC1/S25gZ2i8CSO2kxqDYheSW5b1WdNtf5kaR54g7A7avqxXDzDD5XVNV3eweKTyX5Tv8j/F3gR0lOA/4IvKTanNtaRLa5kxYTO71I0i31IaM+BpxMG4B4Ndo0jN+ltVP+OPAX4P3AjlV1QJIt+hihmiGDO0mSNCv6GHYPowVyvwOOA9anzTLxJ+DDwP/SxgP9RlW9fm5yOiwGd5IkaVaNTd83VsOR5EW0+dPf2kv3rnNe7cXHDhWSJGlW9cBuuR7Y3YU2bt0f+7Y/GdgtXpbcSZKkWZVkBeB+wH/S2tx9xEHdZ4/BnSRJmnVJNgS2BQ6rquvmOj9DZnAnSZI0ILa5kyRJGhCDO0mSpAExuJMkSRoQgztJkqQBMbiTNG/0+XnfO7L+miRvXcgxOybZZyH7PCrJ1yfZdl6SdWaU4Rlecz6eV9JwGNxJmk+uA566KMFWVR1ZVfvPYp4WWR/Ta15Ksvxc50HS7DK4kzSf3AAcQBvo9BaSrJvkS0lO6reH9vTnJ/lIX75Lkp8k+WWSdyT528gpbp/ki0l+k+SzSTKy7XX9mBOT3LWfa0GS7yY5Lcl3kmzS0w9O8rSRfP2t3z8qyQ+SHAmcMdU1kzw2yc/7NQ9KsvJC0rfr5/gZ8NSJnrgkqyU5IskZSb6c5KdJthzLY5L3JvkF8OAkr0ryq3575cjj/dXI+W4uNU1yXJIPJjm1H7P1NF5LSXPE4E7SfPNR4DlJ7jgu/YPA+6tqK+DfgYlGt/8g8MGqug9wwbhtDwBeCWwO/Cvw0JFtV/RjPgJ8oKd9GDikqu4LfBb40DTyvgXwiqq622TXTLIKcDDwzH7NFYCXLCT9E8AOwAOBf5nk2i8FLq+qzYF9+75jbgf8tKruB/wd2A14ELANsEeSB0zjsa1WVffv1zloGvtLmiMGd5Lmlaq6EjgU+I9xmx4HfCTJqcCRwB2S3H7cPg8GvtCXDxu37cSquqCqbgJOBRaMbPvcyP2DR841do5PAw+bRvZPrKpzF3LNuwPnVtVv+z6HAI+YIv0ePf2saqPOf2aSaz8MOBygqn4FnDay7UbgSyP7fbmqrq6qvwH/Bzx8Go/tc/3c36c992tM4xhJc2DetguRtEz7APAz4FMjacsB21TVtaM73rJ2dUqj0x3dyC2//2qS5Ync0PNCkuWAlUa2Xb0I11ySrq2qGxeyz82Pq1tl3Pbxz4vTG0nzlCV3kuadqroMOALYfST5W8DLx1aS3H+CQ39Cq7IFeNYiXPKZI/c/7ssnjJzjOcAP+vJ5/LPKc0dgxUW4DsCZwIKxtn3A84Djp0j/TU+/S0/feZLz/gh4BkCSzYH7TLLfD4Cn9DZ6twP+raf9CbhTkrV7W78njzvumf3cD6NVY18x3Qcsacmy5E7SfPVe4GUj6/8BfDTJabTvru8DLx53zCuBzyR5I/BNYLoByJr9vNfxz+Dp5cCnkrwWuITWTg1a+7ev9s4J3+TWpXVTqqprk+wGfKH3qj0J+HhVXTdF+p7AUUmuoQViq09w6v8BDklyBi0gPH2ix19VP0tyMHBiTzqwqn4OkORtPf3Cfo5R1yb5OS2YfcGiPGZJS1ZaEw5JWvolWQ34e1VVkmcBO1fVTnOdryWhD3GyYg8e7wJ8G7h7VV2/GM59HPCaqjr5tp5L0uyz5E7SkDyQ1ukiwF9ZtkqYVgO+l2RFIMBLF0dgJ2npY8mdJEnSgNihQpIkaUAM7iRJkgbE4E6SJGlADO4kSZIGxOBOkiRpQAzuJEmSBuT/A0Wj+HncaxthAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Result 2.4: From above it is seen that Brooklyn has the max number of reviews correspend to the number of customer."
      ],
      "metadata": {
        "id": "NHsYWcgktNSD"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Result 2 : We found that neighbourhood group 'Manhattan' has 44.3% of the total airbnb listing and higher average listing price as compare to other and has a maximum number of entire home/apt stay prefrence"
      ],
      "metadata": {
        "id": "yxVueFzCNUBy"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "3. Now analyse the cities/neighbourhood which has most airbnb bookings and its relation with other variables i.e columns"
      ],
      "metadata": {
        "id": "pwirnCGbK0Ey"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "  3.1 Obtain the max airbnb booking neighbourhood/cities in neighbourhood group"
      ],
      "metadata": {
        "id": "qoI7J73ULZvh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# grouping the neighbourhood group and neighbourhood to obatin cities count\n",
        "most_visited_city=df.groupby([\"neighbourhood_group\"])[\"neighbourhood\"].value_counts().reset_index(name=\"count\").nlargest(10,\"count\")\n",
        "most_visited_city"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "xH99R73Fra2d",
        "outputId": "0ebc8d56-ed5c-4163-88b1-7770eed0ecb7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-703d9aac-98b2-4ba2-8079-1c00a125e03e\">\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>neighbourhood_group</th>\n",
              "      <th>neighbourhood</th>\n",
              "      <th>count</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>Brooklyn</td>\n",
              "      <td>Williamsburg</td>\n",
              "      <td>3920</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>Brooklyn</td>\n",
              "      <td>Bedford-Stuyvesant</td>\n",
              "      <td>3714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Harlem</td>\n",
              "      <td>2658</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>Brooklyn</td>\n",
              "      <td>Bushwick</td>\n",
              "      <td>2465</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Upper West Side</td>\n",
              "      <td>1971</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>97</th>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Hell's Kitchen</td>\n",
              "      <td>1958</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98</th>\n",
              "      <td>Manhattan</td>\n",
              "      <td>East Village</td>\n",
              "      <td>1853</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Upper East Side</td>\n",
              "      <td>1798</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>Brooklyn</td>\n",
              "      <td>Crown Heights</td>\n",
              "      <td>1564</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>100</th>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Midtown</td>\n",
              "      <td>1545</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-703d9aac-98b2-4ba2-8079-1c00a125e03e')\"\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",
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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",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      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",
              "    [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",
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              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-703d9aac-98b2-4ba2-8079-1c00a125e03e 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-703d9aac-98b2-4ba2-8079-1c00a125e03e');\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",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "    neighbourhood_group       neighbourhood  count\n",
              "48             Brooklyn        Williamsburg   3920\n",
              "49             Brooklyn  Bedford-Stuyvesant   3714\n",
              "95            Manhattan              Harlem   2658\n",
              "50             Brooklyn            Bushwick   2465\n",
              "96            Manhattan     Upper West Side   1971\n",
              "97            Manhattan      Hell's Kitchen   1958\n",
              "98            Manhattan        East Village   1853\n",
              "99            Manhattan     Upper East Side   1798\n",
              "51             Brooklyn       Crown Heights   1564\n",
              "100           Manhattan             Midtown   1545"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#plot the above most airbnb booked city in top 2 group using strip plot\n",
        "ax=sns.stripplot(x=\"neighbourhood_group\", y=\"count\",hue=\"neighbourhood\", data=most_visited_city)\n",
        "ax.set(title=\"Most airbnb booking City with respect to top 2 group\", xlabel=\"Neighbourhood Group\",ylabel=\"No of bookings\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        },
        "id": "5a04OIv7eYDu",
        "outputId": "d036c4aa-2900-45ad-8ef3-698327b63f8f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[Text(0, 0.5, 'No of bookings'),\n",
              " Text(0.5, 0, 'Neighbourhood Group'),\n",
              " Text(0.5, 1.0, 'Most airbnb booking City with respect to top 2 group')]"
            ]
          },
          "metadata": {},
          "execution_count": 27
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Result 3.1  : From above results it is seen that Williamsburg city has max number of booking and its belongs to Brooklyn neighbourhood group and  from Manhattan group harlem is the max number of booking"
      ],
      "metadata": {
        "id": "uFyLNgizL76c"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "3.2 check which room type are prefer in top 10 neighbourhood/cities"
      ],
      "metadata": {
        "id": "2PHLugELXnPS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        " #take top 10 neighbourhood\n",
        "city=df[\"neighbourhood\"].value_counts().nlargest(10).reset_index(name='count')  \n",
        "\n",
        "# to find neighbourhood_group present in neighbourhood\n",
        "group=df[df['neighbourhood'].isin(city['index'])]    \n",
        "top=group[['host_id','neighbourhood_group','neighbourhood','number_of_reviews','room_type']].sort_values(by='number_of_reviews',ascending=False)\n",
        "top\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "rLX65tfXZvLJ",
        "outputId": "d89ce672-6318-439d-a330-9d6ca50d8075"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-459c2c18-792a-401d-8887-74caac02b54a\">\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>host_id</th>\n",
              "      <th>neighbourhood_group</th>\n",
              "      <th>neighbourhood</th>\n",
              "      <th>number_of_reviews</th>\n",
              "      <th>room_type</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2031</th>\n",
              "      <td>4734398</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Harlem</td>\n",
              "      <td>607</td>\n",
              "      <td>Private room</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2030</th>\n",
              "      <td>4734398</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Harlem</td>\n",
              "      <td>597</td>\n",
              "      <td>Private room</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015</th>\n",
              "      <td>4734398</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Harlem</td>\n",
              "      <td>594</td>\n",
              "      <td>Private room</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>471</th>\n",
              "      <td>792159</td>\n",
              "      <td>Brooklyn</td>\n",
              "      <td>Bushwick</td>\n",
              "      <td>480</td>\n",
              "      <td>Private room</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>225</th>\n",
              "      <td>277379</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Harlem</td>\n",
              "      <td>458</td>\n",
              "      <td>Private room</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9637</th>\n",
              "      <td>3911807</td>\n",
              "      <td>Brooklyn</td>\n",
              "      <td>Williamsburg</td>\n",
              "      <td>0</td>\n",
              "      <td>Private room</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9644</th>\n",
              "      <td>38796373</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Midtown</td>\n",
              "      <td>0</td>\n",
              "      <td>Entire home/apt</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34702</th>\n",
              "      <td>7098693</td>\n",
              "      <td>Brooklyn</td>\n",
              "      <td>Bedford-Stuyvesant</td>\n",
              "      <td>0</td>\n",
              "      <td>Private room</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34700</th>\n",
              "      <td>21858263</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>East Village</td>\n",
              "      <td>0</td>\n",
              "      <td>Private room</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48894</th>\n",
              "      <td>68119814</td>\n",
              "      <td>Manhattan</td>\n",
              "      <td>Hell's Kitchen</td>\n",
              "      <td>0</td>\n",
              "      <td>Private room</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>23446 rows × 5 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-459c2c18-792a-401d-8887-74caac02b54a')\"\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",
              "      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",
              "    [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-459c2c18-792a-401d-8887-74caac02b54a 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-459c2c18-792a-401d-8887-74caac02b54a');\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",
              "  "
            ],
            "text/plain": [
              "        host_id neighbourhood_group  ... number_of_reviews        room_type\n",
              "2031    4734398           Manhattan  ...               607     Private room\n",
              "2030    4734398           Manhattan  ...               597     Private room\n",
              "2015    4734398           Manhattan  ...               594     Private room\n",
              "471      792159            Brooklyn  ...               480     Private room\n",
              "225      277379           Manhattan  ...               458     Private room\n",
              "...         ...                 ...  ...               ...              ...\n",
              "9637    3911807            Brooklyn  ...                 0     Private room\n",
              "9644   38796373           Manhattan  ...                 0  Entire home/apt\n",
              "34702   7098693            Brooklyn  ...                 0     Private room\n",
              "34700  21858263           Manhattan  ...                 0     Private room\n",
              "48894  68119814           Manhattan  ...                 0     Private room\n",
              "\n",
              "[23446 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Using catplot plot the above result\n",
        "viz=sns.catplot(x='neighbourhood', hue='neighbourhood_group', col='room_type', data=top, kind='count')\n",
        "viz.set_xticklabels(rotation=90)\n",
        "plt.title(\"Room type preferences in diffrent cities\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 466
        },
        "id": "N6oo-QGcXmdD",
        "outputId": "bfeb66ca-a623-4fef-fa36-f07652f08c4f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Room type preferences in diffrent cities')"
            ]
          },
          "metadata": {},
          "execution_count": 29
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1197.38x360 with 3 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Result 3.2: From above result it is seen that,\n",
        "\n",
        "1. In Manhattan group of cities, max room type prefrence cities are =  private  rooms mostly prefer in 'Harlem', entire home/apt mostly prefer in 'Upper East  side', shared rooms are prefer in 'Hell's Kitchen'.\n",
        "2. In Brooklyn group of cities, max room type prefrence cities are =  private  rooms mostly prefer in 'Bedford-Stuyvesant', entire home/apt mostly prefer in 'Williamsburg', shared rooms are prefer in 'Bedford-Stuyvesant'.\n"
      ],
      "metadata": {
        "id": "0jRjoBGeCPJh"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Result 3: We found that Williamsburg from Brooklyn group has maximum airbnb bookings and room type mostly prefer is private rooms and Harlem from Manhattam group also pefer private rooms mostly."
      ],
      "metadata": {
        "id": "JtKr7ZHoOjNN"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "4. Price distribution analysis in different areas"
      ],
      "metadata": {
        "id": "3K-J9OM8Gl7d"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "4.1 Price distribution in neighbourhood group"
      ],
      "metadata": {
        "id": "zevu7RbCHBNH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#plot price distribution amongs the groups using violin plot\n",
        "sns.violinplot(x=\"neighbourhood_group\",y=\"price\", data=df[df[\"price\"]<300])\n",
        "plt.title(\"Price distribution in neighbourhood groups\")\n",
        "plt.xlabel(\"Neighbourhood Group\")\n",
        "plt.ylabel(\"Price\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 367
        },
        "id": "3wy-xk1YEaHd",
        "outputId": "74ebc436-ddf5-4565-96a6-4aeb8f1638df"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Price')"
            ]
          },
          "metadata": {},
          "execution_count": 30
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Result 4.1: From the graph its shows that 'Manhattan' has booking price is higher. Also 'Manhattan' has a wide variety of price ranges avaliable and it has a moderate bandwidth in higher price range as compared to other group. 'Bronx' group has a higher bandwidth with lower price range. so that it is seen that for luxurious stay people preffered 'manhattan' while for budget stay people preffers other group like Brooklyn,Queens,Staten Island,Bronx"
      ],
      "metadata": {
        "id": "m_j0rSCGI3vW"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "4.2 Prices distribution according to geometrical location."
      ],
      "metadata": {
        "id": "5DDm7q-LR9Dz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# taking the df of prices w.r.t location(longitude, latitude)\n",
        "location=df.loc[df['price']<300,['latitude','longitude','price']]\n",
        "location"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "G8jR0UJmABkr",
        "outputId": "7325e683-c6fe-4c17-da20-4684330e5b35"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f414010c-57cc-4f51-86cd-0043fdd2a6d1');\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",
              "  "
            ],
            "text/plain": [
              "       latitude  longitude  price\n",
              "0      40.64749  -73.97237    149\n",
              "1      40.75362  -73.98377    225\n",
              "2      40.80902  -73.94190    150\n",
              "3      40.68514  -73.95976     89\n",
              "4      40.79851  -73.94399     80\n",
              "...         ...        ...    ...\n",
              "48890  40.67853  -73.94995     70\n",
              "48891  40.70184  -73.93317     40\n",
              "48892  40.81475  -73.94867    115\n",
              "48893  40.75751  -73.99112     55\n",
              "48894  40.76404  -73.98933     90\n",
              "\n",
              "[44977 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Import url calling library\n",
        "import urllib     \n",
        "\n",
        "#initializing the figure size\n",
        "plt.figure(figsize=(10,8))\n",
        "\n",
        "#loading the png NYC image found on Google and saving to my local folder along with the project\n",
        "i=urllib.request.urlopen('https://upload.wikimedia.org/wikipedia/commons/e/ec/Neighbourhoods_New_York_City_Map.PNG')\n",
        "nyc_img=plt.imread(i)\n",
        "\n",
        "#scaling the image based on the latitude and longitude max and mins for proper output\n",
        "plt.imshow(nyc_img,zorder=0,extent=[-74.258, -73.7, 40.49,40.92])\n",
        "ax=plt.gca()\n",
        "\n",
        "#ploting the above result\n",
        "sns.scatterplot(data=location, y='latitude', x='longitude', hue='price', color='red')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 509
        },
        "id": "QW1xi5h5_N4W",
        "outputId": "bc0ca8f5-8c79-4bd7-ca6e-aba1f0a58239"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa67cac1450>"
            ]
          },
          "metadata": {},
          "execution_count": 32
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Result 4.2 : From above it seen that prices of rooms are higher in Manhattan and area of Brooklyn near to the Manhattan. "
      ],
      "metadata": {
        "id": "nBswy6Ky45Io"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "4.3 Average room prices for room types"
      ],
      "metadata": {
        "id": "8WCeuj-wSz4S"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# group the room type with price by taking the mean of price\n",
        "room_avg_price=df.groupby('room_type')['price'].mean().reset_index().set_index('room_type')\n",
        "room_avg_price"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "IOxl5rAYTqUG",
        "outputId": "6ed51c90-ef47-421e-b2ac-f2274834f5e6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-a60120c7-4d8d-457d-adf8-044603d845c0\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>price</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>room_type</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Entire home/apt</th>\n",
              "      <td>211.794246</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Private room</th>\n",
              "      <td>89.780973</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Shared room</th>\n",
              "      <td>70.127586</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "      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-a60120c7-4d8d-457d-adf8-044603d845c0 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-a60120c7-4d8d-457d-adf8-044603d845c0');\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",
              "  "
            ],
            "text/plain": [
              "                      price\n",
              "room_type                  \n",
              "Entire home/apt  211.794246\n",
              "Private room      89.780973\n",
              "Shared room       70.127586"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#plot the avove result using bar plot\n",
        "room_avg_price.plot.bar()\n",
        "plt.title('Average price according to room types')\n",
        "plt.ylabel('Price in dollar')\n",
        "plt.xlabel('Room type')\n",
        "plt.xticks(rotation=30)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 405
        },
        "id": "30YwetfeTB6C",
        "outputId": "9fb2651c-8460-4eca-8b95-74aa5616a6ec"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([0, 1, 2]), <a list of 3 Text major ticklabel objects>)"
            ]
          },
          "metadata": {},
          "execution_count": 34
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Result 4.3 : Average room price for entire room/apt is higher than private rooms and shared rooms and as we seen above customers are prefere to stay in entire room/apt."
      ],
      "metadata": {
        "id": "9aGVHPPEUNHB"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "5. Price distributon box plot"
      ],
      "metadata": {
        "id": "y8StjR4JV3vd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# average price amongs the group by rooms type\n",
        "price_box=df.groupby(['neighbourhood_group','room_type'])['price'].mean().unstack()\n",
        "price_box"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "rTbVbXL6V2Zp",
        "outputId": "7489c5eb-84db-47b5-dcca-aeadde748208"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-06503005-7764-4041-adf2-eb5db75c472d\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>room_type</th>\n",
              "      <th>Entire home/apt</th>\n",
              "      <th>Private room</th>\n",
              "      <th>Shared room</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>neighbourhood_group</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Bronx</th>\n",
              "      <td>127.506596</td>\n",
              "      <td>66.788344</td>\n",
              "      <td>59.800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Brooklyn</th>\n",
              "      <td>178.327545</td>\n",
              "      <td>76.500099</td>\n",
              "      <td>50.527845</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Manhattan</th>\n",
              "      <td>249.239109</td>\n",
              "      <td>116.776622</td>\n",
              "      <td>88.977083</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Queens</th>\n",
              "      <td>147.050573</td>\n",
              "      <td>71.762456</td>\n",
              "      <td>69.020202</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Staten Island</th>\n",
              "      <td>173.846591</td>\n",
              "      <td>62.292553</td>\n",
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              "      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-06503005-7764-4041-adf2-eb5db75c472d 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-06503005-7764-4041-adf2-eb5db75c472d');\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",
              "  "
            ],
            "text/plain": [
              "room_type            Entire home/apt  Private room  Shared room\n",
              "neighbourhood_group                                            \n",
              "Bronx                     127.506596     66.788344    59.800000\n",
              "Brooklyn                  178.327545     76.500099    50.527845\n",
              "Manhattan                 249.239109    116.776622    88.977083\n",
              "Queens                    147.050573     71.762456    69.020202\n",
              "Staten Island             173.846591     62.292553    57.444444"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# plot the above results by box plot\n",
        "price_box.plot(kind=\"box\")\n",
        "plt.title('price distribution by room_type')\n",
        "plt.ylabel('Average Price')\n",
        "plt.xlabel('room_type')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 367
        },
        "id": "HxQAASIcV2LK",
        "outputId": "b5626280-b2b9-4d10-f01b-023a6cf6ff8a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 0, 'room_type')"
            ]
          },
          "metadata": {},
          "execution_count": 36
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Result 5 : From above it is seen that max price range is available for entrire home/apt as compared to other room type and average lower price for entire home/apt is also higher than other room types."
      ],
      "metadata": {
        "id": "FJDCfmJAXBQ-"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "6. Check the relation between the price and reviews"
      ],
      "metadata": {
        "id": "GNUC9uJDYdxh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#checking for correlation between price and reviews\n",
        "correlation_df=df[['price','number_of_reviews']]\n",
        "corr_df = correlation_df.corr()\n",
        "plt.figure(figsize=(10,5))\n",
        "sns.heatmap(corr_df,vmin=-1, cmap=\"Blues\", annot=True, )"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 343
        },
        "id": "RVc9nZx7Zrct",
        "outputId": "620c662d-f59d-404e-dadf-5d1169ef4630"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa671f4a7d0>"
            ]
          },
          "metadata": {},
          "execution_count": 37
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Results 6 : As seen above, therevis negative values thats means price to the reviews relation is inversly proportional. As prices of booking increases less people refere to stay."
      ],
      "metadata": {
        "id": "vXed_tDOYoV0"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Conclusion**: \n",
        "Data from Airbnb NYC 2019 provides detailed information about the prices, locations, customer preferences for staying, and properties available in various New York cities.We began our EDA by performing a basic check to determine the number of rows (i.e records) and columns (i.e variables), followed by a through examination of the columns to be used in our analysis. Then, we perform data wrangling to check and replace any null values present in the data and also drop some columns.\n",
        "\n",
        "\n",
        "First, we analysed the host who has the maximum number of customers or bookings by using the number of reviews and the maximum number of properties listed in the host's name by using the count of properties. We found that host names like Maya and Sonder (NYC) have the maximum number of bookings, i.e., 2273, and the maximum number of properties, i.e., 327, respectively. Both hosts belong to the Manhattan group, and in the Brooklyn group, Michael is the busiest host with 159 properties listed.\n",
        "\n",
        "\n",
        "Then, we explored which neighbourhood group has the maximum number of customers and their preferences for staying and average prices. So we found that Manhattan has the maximum share of customers amongst all other groups, which is 44.3%, and most of the customers prefer to stay in an entire home or apartment. The reasons behind that are that it is a tourist attraction, a commercial centre, a cultural centre, media and entertainment center. In further analysis, we found that Brooklyn has the maximum number of reviews and the corresponding maximum number of customers. After that, we found the maximum number of booking cities from the top groups. As a result of that, in Brooklyn group Williamsburg has the maximum number of customers ( 3920) and in Manhattan  group Harlem has the maximum number of customers (2658). We also analysed the room type preferences. According to that, in Williamsburg and Harlem, entire home or apartments are mostly booked. Business clients prefer to stay in luxurious rooms or apartments, as this city has many industrial areas.\n",
        "\n",
        "\n",
        "We, also performed the price analysis. We found that staying in Manhattan is expensive as compared to other groups and the average price for the entire home or apartment is more costly than staying in a private room or shared room.\n",
        "We performed some additional analysis on the correlation between the prices and the number of reviews and property preferences. We found that a higher number of customers preferred to stay in entire home or apartments than private rooms and shared rooms. The relationship between the price and the number of reviews is also inversely proportional, i.e. the higher the price, the fewer people prefer to stay.\n",
        "\n",
        "\n",
        "Broad view of above data is that, by considering prices and luxuries, Manhattan is the top group because of its financial centre, but most of the customers give good reviews to the Brooklyn group and customers prefer to stay in the area of Brooklyn which is nearer to Manhattan because of the price structure is quite high in Manhattan, aslo room type prefer is entire home or apartment and max number of properties listed owners are Maya, Sonder (NYC) and Michael.\n",
        "\n",
        "\n",
        "We mined good insights from Airbnb data, and further, this analysis will help in the development of business strategies, correcting decisions, and much more...."
      ],
      "metadata": {
        "id": "b4LpnR4YZMbn"
      }
    }
  ]
}