lang_network.ipynb

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  "metadata": {
    "colab": {
      "name": "lang_network.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "BnxtWZu1Kb9b",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "import networkx as nx\n",
        "from tqdm import tqdm"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lt5IiO9xLAsc",
        "colab_type": "code",
        "outputId": "a50e9a80-e010-4a8f-f3a7-95f7a484ed4c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        }
      },
      "source": [
        "df_country = pd.read_csv('node.csv',sep=',')\n",
        "df_country.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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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>id</th>\n",
              "      <th>country</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Afghanistan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>Albania</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Algeria</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>American Samoa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Andorra</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   id         country\n",
              "0   1     Afghanistan\n",
              "1   2         Albania\n",
              "2   3         Algeria\n",
              "3   4  American Samoa\n",
              "4   5         Andorra"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 78
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tifELGsWLj6g",
        "colab_type": "code",
        "outputId": "f8f9dfc0-357d-46bb-e9e5-bcbc1b3f45bb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        }
      },
      "source": [
        "df_lang = pd.read_csv('edge.csv',sep=',',encoding=\"ISO-8859-1\")\n",
        "df_lang.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    }\n",
              "\n",
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              "        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>source</th>\n",
              "      <th>Target</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Dari</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>Pashto</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>Uzbek</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>English</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>Turkmen</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   source   Target\n",
              "0       1     Dari\n",
              "1       1   Pashto\n",
              "2       1    Uzbek\n",
              "3       1  English\n",
              "4       1  Turkmen"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sRtN1bqtaUxn",
        "colab_type": "code",
        "outputId": "bf87858d-7539-4e43-e842-dcc007fb66af",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        }
      },
      "source": [
        "df_lang.tail()"
      ],
      "execution_count": 0,
      "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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              "        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>source</th>\n",
              "      <th>Target</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>4458</th>\n",
              "      <td>236</td>\n",
              "      <td>Sotho</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4459</th>\n",
              "      <td>236</td>\n",
              "      <td>Tonga</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4460</th>\n",
              "      <td>236</td>\n",
              "      <td>Tswana</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4461</th>\n",
              "      <td>236</td>\n",
              "      <td>Venda</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4462</th>\n",
              "      <td>236</td>\n",
              "      <td>Xhosa</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      source  Target\n",
              "4458     236   Sotho\n",
              "4459     236   Tonga\n",
              "4460     236  Tswana\n",
              "4461     236   Venda\n",
              "4462     236   Xhosa"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AaXviSCZL3wv",
        "colab_type": "text"
      },
      "source": [
        "# Creating nodes\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5Lk2tVRaL2Ph",
        "colab_type": "code",
        "outputId": "7b86cabe-62c9-4d72-efb4-9b8210815d60",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 109
        }
      },
      "source": [
        "nodes = list(df_country.country)\n",
        "G = nx.Graph()\n",
        "for i in range(len(df_country)):\n",
        "  G.add_node(nodes[i])\n",
        "print(nx.info(G))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Name: \n",
            "Type: Graph\n",
            "Number of nodes: 236\n",
            "Number of edges: 0\n",
            "Average degree:   0.0000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Jg-SM-5POOXf",
        "colab_type": "text"
      },
      "source": [
        "# Creating edges\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VOtByEwoON2F",
        "colab_type": "code",
        "outputId": "6c377ca3-1b79-42b0-b980-bec2f22dc3e9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 109
        }
      },
      "source": [
        "# create a list of languages per country\n",
        "df_country['lang'] = \"\"\n",
        "df_country.head()\n",
        "for i in range(len(df_country)):\n",
        "  id = df_country['id'][i]\n",
        "  temp = []\n",
        "  for j in range(len(df_lang)):\n",
        "    if df_lang['source'][j] == id:\n",
        "      temp.append(df_lang['Target'][j])\n",
        "  df_country['lang'][i] = temp"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:9: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  if __name__ == '__main__':\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ePzgYQ0UQ9-Z",
        "colab_type": "code",
        "outputId": "4b770705-f08c-42eb-f5ff-614573adfee2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        }
      },
      "source": [
        "df_country.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>id</th>\n",
              "      <th>country</th>\n",
              "      <th>lang</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>[Dari, Pashto, Uzbek, English, Turkmen, Urdu, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>Albania</td>\n",
              "      <td>[Albanian, Greek, Macedonian, Romani, Vlach, T...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Algeria</td>\n",
              "      <td>[Arabic, French, Berber, Tacawit, MzabBerber, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>American Samoa</td>\n",
              "      <td>[Samoan, English, Tongan, Pacificislander]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Andorra</td>\n",
              "      <td>[Catalan, French, Castilian, Portuguese]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   id         country                                               lang\n",
              "0   1     Afghanistan  [Dari, Pashto, Uzbek, English, Turkmen, Urdu, ...\n",
              "1   2         Albania  [Albanian, Greek, Macedonian, Romani, Vlach, T...\n",
              "2   3         Algeria  [Arabic, French, Berber, Tacawit, MzabBerber, ...\n",
              "3   4  American Samoa         [Samoan, English, Tongan, Pacificislander]\n",
              "4   5         Andorra           [Catalan, French, Castilian, Portuguese]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VrNrQMcJaB_S",
        "colab_type": "code",
        "outputId": "86b97a4f-b5fe-4ba2-b9b5-5e98e4b1f8c5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        }
      },
      "source": [
        "df_country.tail()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "\n",
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              "    }\n",
              "\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>id</th>\n",
              "      <th>country</th>\n",
              "      <th>lang</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>231</th>\n",
              "      <td>232</td>\n",
              "      <td>West Bank</td>\n",
              "      <td>[Arabic, Hebrew, English]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>232</th>\n",
              "      <td>233</td>\n",
              "      <td>Western Sahara</td>\n",
              "      <td>[Arabic, HassaniyaArabic, MoroccanArabic, Berb...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>233</th>\n",
              "      <td>234</td>\n",
              "      <td>Yemen</td>\n",
              "      <td>[Arabic, Socotri, Mahri]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>234</th>\n",
              "      <td>235</td>\n",
              "      <td>Zambia</td>\n",
              "      <td>[Bemba, Nyanja, Tonga, Lozi, Chewa, Nsenga, Tu...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>235</th>\n",
              "      <td>236</td>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>[Shona, Ndebele, English, Chewa, Chibarwe, Kal...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      id         country                                               lang\n",
              "231  232       West Bank                          [Arabic, Hebrew, English]\n",
              "232  233  Western Sahara  [Arabic, HassaniyaArabic, MoroccanArabic, Berb...\n",
              "233  234           Yemen                           [Arabic, Socotri, Mahri]\n",
              "234  235          Zambia  [Bemba, Nyanja, Tonga, Lozi, Chewa, Nsenga, Tu...\n",
              "235  236        Zimbabwe  [Shona, Ndebele, English, Chewa, Chibarwe, Kal..."
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3x4rRdMFRwm1",
        "colab_type": "code",
        "outputId": "3b8f10db-a9f0-4587-8bda-ca76e677d057",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 164
        }
      },
      "source": [
        "list(set(df_country['lang'][1])&set(df_country['lang'][1]))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Greek',\n",
              " 'Turkish',\n",
              " 'Albanian',\n",
              " 'Italian',\n",
              " 'Macedonian',\n",
              " 'Serbo-Croatian',\n",
              " 'Vlach',\n",
              " 'Romani']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pa4s4uZTRCq_",
        "colab_type": "code",
        "outputId": "2ffd0303-ee03-48f3-bdb6-1a5a1ccb2204",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "for i in tqdm(range(len(df_country))):\n",
        "  for j in range(len(df_country)):\n",
        "    if (i!=j):\n",
        "      cl = list(set(df_country['lang'][i])&set(df_country['lang'][j]))\n",
        "      c = len(cl)\n",
        "      if (c!=0):\n",
        "        G.add_edge(nodes[i],nodes[j], weight = c)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 236/236 [00:02<00:00, 88.01it/s]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-bsBzaQQUHjD",
        "colab_type": "code",
        "outputId": "f95e61d3-3a4b-4143-f0ce-1b72a93681c4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 109
        }
      },
      "source": [
        "print(nx.info(G))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Name: \n",
            "Type: Graph\n",
            "Number of nodes: 236\n",
            "Number of edges: 14482\n",
            "Average degree: 122.7288\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5UiuweQ7cSlc",
        "colab_type": "code",
        "outputId": "d38bc8d3-20ae-4a0d-b555-4f866bd01bb6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 319
        }
      },
      "source": [
        "nx.draw(G)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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EeJSKgw1dWyoOxqmJ8RaPCNpH+IA4vG9XTE2WY2To6T4SRoYGYmqyHIf2OqWB/mGTaiAi\nPt5o2ukMbHeOJQI2uDK3EGfOz8a5a/NRiIeL09etn8f34oGxODUx7psefUn4gE90Z2k5zr4xF5Wb\n92OxuhKjpaEo79kZJ444gZ3+JnwApGJyCwCpCB8AqQgfAKkIHwCpCB8AqQgfAKkIHwCpCB8AqQgf\nAKkIHwCpCB8AqQgfAKkIHwCpCB8AqfwfF3uZORjgwR4AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8ZZuMrhYYxkq",
        "colab_type": "code",
        "outputId": "c6612918-65cd-4288-afb7-cb27e6453240",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 55
        }
      },
      "source": [
        "G.nodes"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "NodeView(('Afghanistan', 'Albania', 'Algeria', 'American Samoa', 'Andorra', 'Angola', 'Anguilla', 'Antigua and Barbuda', 'Argentina', 'Armenia', 'Aruba', 'Australia', 'Austria', 'Azerbaijan', 'Bahamas, The', 'Bahrain', 'Bangladesh', 'Barbados', 'Belarus', 'Belgium', 'Belize', 'Benin', 'Bermuda', 'Bhutan', 'Bolivia', 'Bosnia and Herzegovina', 'Botswana', 'Brazil', 'British Virgin Islands', 'Brunei', 'Bulgaria', 'Burkina Faso', 'Burundi', 'Cabo Verde', 'Cambodia', 'Cameroon', 'Canada', 'Cayman Islands', 'Central African Republic', 'Chad', 'Chile', 'China', 'Christmas Island', 'Cocos (Keeling) Islands', 'Colombia', 'Comoros', 'Cook Islands', 'Costa Rica', \"Cote d'Ivoire\", 'Croatia', 'Cuba', 'Curacao', 'Cyprus', 'Czechia', 'Democratic Republic of the Congo', 'Denmark', 'Djibouti', 'Dominica', 'Dominican Republic', 'Ecuador', 'Egypt', 'El Salvador', 'Equatorial Guinea', 'Eritrea', 'Estonia', 'Eswatini', 'Ethiopia', 'Falkland Islands (Islas Malvinas)', 'Faroe Islands', 'Fiji', 'Finland', 'France', 'French Polynesia', 'Gabon', 'Gaza Strip', 'Georgia', 'Germany', 'Ghana', 'Gibraltar', 'Greece', 'Greenland', 'Grenada', 'Guam', 'Guatemala', 'Guernsey', 'Guinea', 'Guinea-Bissau', 'Guyana', 'Haiti', 'Holy See (Vatican City)', 'Honduras', 'Hong Kong', 'Hungary', 'Iceland', 'India', 'Indonesia', 'Iran', 'Iraq', 'Ireland', 'Isle of Man', 'Israel', 'Italy', 'Jamaica', 'Japan', 'Jersey', 'Jordan', 'Kazakhstan', 'Kenya', 'Kiribati', 'North Korea', 'South Korea', 'Kosovo', 'Kuwait', 'Kyrgyzstan', 'Laos', 'Latvia', 'Lebanon', 'Lesotho', 'Liberia', 'Libya', 'Liechtenstein', 'Lithuania', 'Luxembourg', 'Macau', 'Madagascar', 'Malawi', 'Malaysia', 'Maldives', 'Mali', 'Malta', 'Marshall Islands', 'Mauritania', 'Mauritius', 'Mayanmar', 'Mexico', 'Micronesia, Federated States of', 'Moldova', 'Monaco', 'Mongolia', 'Montenegro', 'Montserrat', 'Morocco', 'Mozambique', 'Namibia', 'Nauru', 'Nepal', 'Netherlands', 'New Caledonia', 'New Zealand', 'Nicaragua', 'Niger', 'Nigeria', 'Niue', 'Norfolk Island', 'North Macedonia', 'Northern Mariana Islands', 'Norway', 'Oman', 'Pakistan', 'Palau', 'Panama', 'Papua New Guinea', 'Paraguay', 'Peru', 'Philippines', 'Pitcairn Islands', 'Poland', 'Portugal', 'Puerto Rico', 'Qatar', 'Republic of the Congo', 'Romania', 'Russia', 'Rwanda', 'Saint Barthelemy', 'Saint Helena, Ascension, and Tristan da Cunha', 'Saint Kitts and Nevis', 'Saint Lucia', 'Saint Martin', 'Saint Pierre and Miquelon', 'Saint Vincent and the Grenadines', 'Samoa', 'San Marino', 'Sao Tome and Principe', 'Saudi Arabia', 'Senegal', 'Serbia', 'Seychelles', 'Sierra Leone', 'Singapore', 'Sint Maarten', 'Slovakia', 'Slovenia', 'Solomon Islands', 'Somalia', 'South Africa', 'South Sudan', 'Spain', 'Sri Lanka', 'Sudan', 'Suriname', 'Sweden', 'Switzerland', 'Syria', 'Taiwan', 'Tajikistan', 'Tanzania', 'Thailand', 'The Gambia', 'Timor-Leste', 'Togo', 'Tokelau', 'Tonga', 'Trinidad and Tobago', 'Tunisia', 'Turkey', 'Turkmenistan', 'Turks and Caicos Islands', 'Tuvalu', 'Uganda', 'Ukraine', 'United Arab Emirates', 'United Kingdom', 'United States', 'Uruguay', 'Uzbekistan', 'Vanuatu', 'Venezuela', 'Vietnam', 'Virgin Islands', 'Wallis and Futuna', 'West Bank', 'Western Sahara', 'Yemen', 'Zambia', 'Zimbabwe'))"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 75
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "c-SOe749YFAv",
        "colab_type": "code",
        "outputId": "4a20e89d-c18e-468d-a659-159cf9c9b59d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "nx.is_weighted(G)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 74
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jMHIg0n_k8vK",
        "colab_type": "code",
        "outputId": "0c492f92-08bf-4937-cb51-5f475af007bc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "nx.is_directed (G)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 96
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OyNDyb7qf0H9",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "G1 = G.to_undirected()\n",
        "# nx.write_gexf(G, \"test_undirected.gexf\")\n",
        "nx.write_gml(G1, \"test_undirected.gml\")"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yh5LYmwthe7x",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}