First_Assignment_Neighborhood_Segmentation_and_Clustering.ipynb

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      "name": "First Assignment - Neighborhood Segmentation and Clustering.ipynb",
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      "name": "python3",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/redcican/Coursera_Capstone/blob/master/First_Assignment_Neighborhood_Segmentation_and_Clustering.ipynb)"
      ]
    },
    {
      "metadata": {
        "id": "OV32gciL7jGA",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# IBM Coursera Final Project 1: Segmenting and Clustering Neighborhoods in Toronto - First Assignment"
      ]
    },
    {
      "metadata": {
        "id": "p9QtroMV7w0r",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## 1. Import the Libraries"
      ]
    },
    {
      "metadata": {
        "id": "GCNqkUBrm0rl",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "from bs4 import BeautifulSoup\n",
        "import requests\n",
        "import pandas as pd\n",
        "import re"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "MeanQcFnm0rs",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "url = \"https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M\"\n",
        "html = requests.get(url).text"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "RjGQkyJl737o",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Use Beautifulsoup to extract the table content from URL page."
      ]
    },
    {
      "metadata": {
        "id": "CeaC1c0Gm0rx",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "soup = BeautifulSoup(html, 'html.parser')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "LSlOjUzp7-tn",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Find the table, and check the content."
      ]
    },
    {
      "metadata": {
        "id": "FT7zcURqm0r2",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "my_table = soup.find('table',{'class':'wikitable sortable'})\n",
        "my_table"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "9rZMOAG-8DS_",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Only find all cells."
      ]
    },
    {
      "metadata": {
        "scrolled": true,
        "id": "ZIDtMmT4m0r_",
        "colab_type": "code",
        "colab": {},
        "cellView": "both"
      },
      "cell_type": "code",
      "source": [
        "cells = my_table.find_all('td')\n",
        "cells"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "7iHIV6mC8N6L",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Define 3 lists for 3 columns."
      ]
    },
    {
      "metadata": {
        "id": "FWIvbcqwm0sF",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "Postcode = [];\n",
        "Borough = [];\n",
        "Neighbourhood = [];"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "V8Gj8pI48S0I",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "A for loop to iterate all data."
      ]
    },
    {
      "metadata": {
        "id": "Q3Zdpj8vm0sK",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "for row in my_table.findAll(\"tr\"):\n",
        "    cells = row.findAll(\"td\")\n",
        "    #For each \"tr\", assign each \"td\" to a variable.\n",
        "    if len(cells) == 3:\n",
        "        Postcode.append(cells[0].find(text=True))\n",
        "        Borough.append(cells[1].find(text=True))\n",
        "        Neighbourhood.append(cells[2].find(text=True))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "2d_qKLli8YIZ",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Convert the lists to a Pandas Dataframe, and check the first 10 rows."
      ]
    },
    {
      "metadata": {
        "id": "EamuF0Cbm0sO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 343
        },
        "outputId": "258f10f3-698d-4fb4-baca-8e335b5ab65d"
      },
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame({\"Postcode\":Postcode,\n",
        "                  \"Borough\":Borough,\n",
        "                  \"Neighbourhood\":Neighbourhood})\n",
        "df = df[['Postcode','Borough','Neighbourhood']]\n",
        "df.head(10)"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    }\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>Postcode</th>\n",
              "      <th>Borough</th>\n",
              "      <th>Neighbourhood</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>M1A</td>\n",
              "      <td>Not assigned</td>\n",
              "      <td>Not assigned</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>M2A</td>\n",
              "      <td>Not assigned</td>\n",
              "      <td>Not assigned</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>M3A</td>\n",
              "      <td>North York</td>\n",
              "      <td>Parkwoods</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>M4A</td>\n",
              "      <td>North York</td>\n",
              "      <td>Victoria Village</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>M5A</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>Harbourfront</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>M5A</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>Regent Park</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>M6A</td>\n",
              "      <td>North York</td>\n",
              "      <td>Lawrence Heights</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>M6A</td>\n",
              "      <td>North York</td>\n",
              "      <td>Lawrence Manor</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>M7A</td>\n",
              "      <td>Queen's Park</td>\n",
              "      <td>Not assigned</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>M8A</td>\n",
              "      <td>Not assigned</td>\n",
              "      <td>Not assigned</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  Postcode           Borough     Neighbourhood\n",
              "0      M1A      Not assigned     Not assigned\n",
              "\n",
              "1      M2A      Not assigned     Not assigned\n",
              "\n",
              "2      M3A        North York         Parkwoods\n",
              "3      M4A        North York  Victoria Village\n",
              "4      M5A  Downtown Toronto      Harbourfront\n",
              "5      M5A  Downtown Toronto       Regent Park\n",
              "6      M6A        North York  Lawrence Heights\n",
              "7      M6A        North York    Lawrence Manor\n",
              "8      M7A      Queen's Park     Not assigned\n",
              "\n",
              "9      M8A      Not assigned     Not assigned"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "metadata": {
        "id": "L7oOik5l8ecM",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Ignore cells with a borough that is **Not assigned**."
      ]
    },
    {
      "metadata": {
        "id": "z_osDsMUm0sT",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 343
        },
        "outputId": "0ffb7f15-6a64-4994-98ce-cceb17fb107a"
      },
      "cell_type": "code",
      "source": [
        "df = df[df['Borough']!='Not assigned'].reset_index(drop=True)\n",
        "df.head(10)"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\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>Postcode</th>\n",
              "      <th>Borough</th>\n",
              "      <th>Neighbourhood</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>M3A</td>\n",
              "      <td>North York</td>\n",
              "      <td>Parkwoods</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>M4A</td>\n",
              "      <td>North York</td>\n",
              "      <td>Victoria Village</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>M5A</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>Harbourfront</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>M5A</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>Regent Park</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>M6A</td>\n",
              "      <td>North York</td>\n",
              "      <td>Lawrence Heights</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>M6A</td>\n",
              "      <td>North York</td>\n",
              "      <td>Lawrence Manor</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>M7A</td>\n",
              "      <td>Queen's Park</td>\n",
              "      <td>Not assigned</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>M9A</td>\n",
              "      <td>Etobicoke</td>\n",
              "      <td>Islington Avenue</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>M1B</td>\n",
              "      <td>Scarborough</td>\n",
              "      <td>Rouge</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>M1B</td>\n",
              "      <td>Scarborough</td>\n",
              "      <td>Malvern</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  Postcode           Borough     Neighbourhood\n",
              "0      M3A        North York         Parkwoods\n",
              "1      M4A        North York  Victoria Village\n",
              "2      M5A  Downtown Toronto      Harbourfront\n",
              "3      M5A  Downtown Toronto       Regent Park\n",
              "4      M6A        North York  Lawrence Heights\n",
              "5      M6A        North York    Lawrence Manor\n",
              "6      M7A      Queen's Park     Not assigned\n",
              "\n",
              "7      M9A         Etobicoke  Islington Avenue\n",
              "8      M1B       Scarborough             Rouge\n",
              "9      M1B       Scarborough           Malvern"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "metadata": {
        "id": "IizyvRgO8ll5",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Using Pandas `groupby`function to combine two rows into one row with the neighborhoods separated with a comma."
      ]
    },
    {
      "metadata": {
        "id": "8mwSdSowy3N-",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 343
        },
        "outputId": "a38af8b1-49cc-4d35-8f8d-042e768ae634"
      },
      "cell_type": "code",
      "source": [
        "df['Neighbourhood'] = df[['Postcode','Borough','Neighbourhood']].groupby(['Postcode','Borough'])['Neighbourhood'].transform(lambda x: ', '.join(x))\n",
        "df = df.drop_duplicates()\n",
        "df = df.replace(r'\\n','', regex=True) \n",
        "df.head(10)"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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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>Postcode</th>\n",
              "      <th>Borough</th>\n",
              "      <th>Neighbourhood</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>M3A</td>\n",
              "      <td>North York</td>\n",
              "      <td>Parkwoods</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>M4A</td>\n",
              "      <td>North York</td>\n",
              "      <td>Victoria Village</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>M5A</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>Harbourfront, Regent Park</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>M6A</td>\n",
              "      <td>North York</td>\n",
              "      <td>Lawrence Heights, Lawrence Manor</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>M7A</td>\n",
              "      <td>Queen's Park</td>\n",
              "      <td>Not assigned</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>M9A</td>\n",
              "      <td>Etobicoke</td>\n",
              "      <td>Islington Avenue</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>M1B</td>\n",
              "      <td>Scarborough</td>\n",
              "      <td>Rouge, Malvern</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>M3B</td>\n",
              "      <td>North York</td>\n",
              "      <td>Don Mills North</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>M4B</td>\n",
              "      <td>East York</td>\n",
              "      <td>Woodbine Gardens, Parkview Hill</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>M5B</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>Ryerson, Garden District</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Postcode           Borough                     Neighbourhood\n",
              "0       M3A        North York                         Parkwoods\n",
              "1       M4A        North York                  Victoria Village\n",
              "2       M5A  Downtown Toronto         Harbourfront, Regent Park\n",
              "4       M6A        North York  Lawrence Heights, Lawrence Manor\n",
              "6       M7A      Queen's Park                      Not assigned\n",
              "7       M9A         Etobicoke                  Islington Avenue\n",
              "8       M1B       Scarborough                    Rouge, Malvern\n",
              "10      M3B        North York                   Don Mills North\n",
              "11      M4B         East York   Woodbine Gardens, Parkview Hill\n",
              "13      M5B  Downtown Toronto          Ryerson, Garden District"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "metadata": {
        "id": "X68Vl4bd82tn",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "If a cell has a borough but a **Not assigned** neighborhood, then the neighborhood will be the same as the borough."
      ]
    },
    {
      "metadata": {
        "id": "o7o1lZrI3B4r",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "for i in range(len(df['Neighbourhood'])):\n",
        "    if df['Neighbourhood'].iloc[i] == 'Not assigned':\n",
        "        df['Neighbourhood'].iloc[i] = df['Borough'].iloc[i]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "7v1pOJGr6I67",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 343
        },
        "outputId": "df6e1aa0-3f33-4598-e4cf-e9b459735999"
      },
      "cell_type": "code",
      "source": [
        "df.head(10)"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Postcode</th>\n",
              "      <th>Borough</th>\n",
              "      <th>Neighbourhood</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>M3A</td>\n",
              "      <td>North York</td>\n",
              "      <td>Parkwoods</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>M4A</td>\n",
              "      <td>North York</td>\n",
              "      <td>Victoria Village</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>M5A</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>Harbourfront, Regent Park</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>M6A</td>\n",
              "      <td>North York</td>\n",
              "      <td>Lawrence Heights, Lawrence Manor</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>M7A</td>\n",
              "      <td>Queen's Park</td>\n",
              "      <td>Queen's Park</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>M9A</td>\n",
              "      <td>Etobicoke</td>\n",
              "      <td>Islington Avenue</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>M1B</td>\n",
              "      <td>Scarborough</td>\n",
              "      <td>Rouge, Malvern</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>M3B</td>\n",
              "      <td>North York</td>\n",
              "      <td>Don Mills North</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>M4B</td>\n",
              "      <td>East York</td>\n",
              "      <td>Woodbine Gardens, Parkview Hill</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>M5B</td>\n",
              "      <td>Downtown Toronto</td>\n",
              "      <td>Ryerson, Garden District</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Postcode           Borough                     Neighbourhood\n",
              "0       M3A        North York                         Parkwoods\n",
              "1       M4A        North York                  Victoria Village\n",
              "2       M5A  Downtown Toronto         Harbourfront, Regent Park\n",
              "4       M6A        North York  Lawrence Heights, Lawrence Manor\n",
              "6       M7A      Queen's Park                      Queen's Park\n",
              "7       M9A         Etobicoke                  Islington Avenue\n",
              "8       M1B       Scarborough                    Rouge, Malvern\n",
              "10      M3B        North York                   Don Mills North\n",
              "11      M4B         East York   Woodbine Gardens, Parkview Hill\n",
              "13      M5B  Downtown Toronto          Ryerson, Garden District"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "metadata": {
        "id": "t95BuMSV9Gsd",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Use the **.shape** method to print the number of rows."
      ]
    },
    {
      "metadata": {
        "id": "wEIaYWLZ7Ur9",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "d359d525-d096-409e-9894-ff0baea52d31"
      },
      "cell_type": "code",
      "source": [
        "df.shape"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(103, 3)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "metadata": {
        "id": "WRWW1O8W9NDK",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}