{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "Week13_Assignment.ipynb",
"provenance": [],
"collapsed_sections": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"cell_type": "code",
"metadata": {
"id": "-c2YnvvCei8k",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "19957757-adac-4510-868d-068f17bfc75e"
},
"source": [
"!pip install dimcli networkx pyvis -U --quiet"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"\u001b[K |████████████████████████████████| 307kB 8.6MB/s \n",
"\u001b[K |████████████████████████████████| 51kB 4.3MB/s \n",
"\u001b[?25h"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 299
},
"id": "sDZ3OTw1_KN0",
"outputId": "53042041-cc49-4147-8240-b7b66dbd3e96"
},
"source": [
"import networkx as nx\n",
"from pyvis import network as net\n",
"import pyvis\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import scipy\n",
"from dimcli.core.extras import NetworkViz\n",
"\n",
"lrst = pd.DataFrame({'class': ['Math', 'Math', 'Math', 'Math','English', 'English', 'English', 'PE', 'PE', 'PE', 'PE', 'History', 'History', 'History', 'History', 'History'],\n",
" 'name': ['Carole ', 'Wood', 'Terrence ', 'Bowen','Anne', 'Singleton', 'Yvette','Edwards', 'Terrence ', 'Foster', 'Austin ','Montgomery', 'Lorena', 'Yvette', 'Kirk', 'Alexander']})\n",
"lrst.head(10)"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"application/vnd.google.colaboratory.module+javascript": "\n import \"https://ssl.gstatic.com/colaboratory/data_table/a6224c040fa35dcf/data_table.js\";\n\n window.createDataTable({\n data: [[{\n 'v': 0,\n 'f': \"0\",\n },\n\"Math\",\n\"Carole \"],\n [{\n 'v': 1,\n 'f': \"1\",\n },\n\"Math\",\n\"Wood\"],\n [{\n 'v': 2,\n 'f': \"2\",\n },\n\"Math\",\n\"Terrence \"],\n [{\n 'v': 3,\n 'f': \"3\",\n },\n\"Math\",\n\"Bowen\"],\n [{\n 'v': 4,\n 'f': \"4\",\n },\n\"English\",\n\"Anne\"],\n [{\n 'v': 5,\n 'f': \"5\",\n },\n\"English\",\n\"Singleton\"],\n [{\n 'v': 6,\n 'f': \"6\",\n },\n\"English\",\n\"Yvette\"],\n [{\n 'v': 7,\n 'f': \"7\",\n },\n\"PE\",\n\"Edwards\"],\n [{\n 'v': 8,\n 'f': \"8\",\n },\n\"PE\",\n\"Terrence \"],\n [{\n 'v': 9,\n 'f': \"9\",\n },\n\"PE\",\n\"Foster\"]],\n columns: [[\"number\", \"index\"], [\"string\", \"class\"], [\"string\", \"name\"]],\n columnOptions: [{\"width\": \"1px\", \"className\": \"index_column\"}],\n rowsPerPage: 25,\n helpUrl: \"https://colab.research.google.com/notebooks/data_table.ipynb\",\n suppressOutputScrolling: true,\n minimumWidth: undefined,\n });\n ",
"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>class</th>\n",
" <th>name</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Math</td>\n",
" <td>Carole</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Math</td>\n",
" <td>Wood</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Math</td>\n",
" <td>Terrence</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Math</td>\n",
" <td>Bowen</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>English</td>\n",
" <td>Anne</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>English</td>\n",
" <td>Singleton</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>English</td>\n",
" <td>Yvette</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>PE</td>\n",
" <td>Edwards</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>PE</td>\n",
" <td>Terrence</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>PE</td>\n",
" <td>Foster</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" class name\n",
"0 Math Carole \n",
"1 Math Wood\n",
"2 Math Terrence \n",
"3 Math Bowen\n",
"4 English Anne\n",
"5 English Singleton\n",
"6 English Yvette\n",
"7 PE Edwards\n",
"8 PE Terrence \n",
"9 PE Foster"
]
},
"metadata": {
"tags": []
},
"execution_count": 5
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "1B59dOs5AS9e",
"outputId": "436b0e77-027a-4110-a15a-84db35599e75"
},
"source": [
"df = nx.from_pandas_edgelist(lrst, source = 'class', target = 'name')\n",
"data = nx.adjacency_matrix(df)\n",
"print(data.todense())"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"[[0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0]\n",
" [0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]\n",
" [0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [0 0 0 1 0 0 0 0 0 0 1 1 1 0 0 0 0 0]\n",
" [0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n",
" [0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 1 1]\n",
" [0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]\n",
" [0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]]\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 383
},
"id": "AZi4mVnLAopM",
"outputId": "c55752ff-ce23-4c6b-98e5-bb4fb52c062d"
},
"source": [
"nodes = list(df.nodes())\n",
"documents = lrst['class'].unique().tolist()\n",
"names = lrst['name'].unique().tolist()\n",
"\n",
"row_idx = []\n",
"for name in names:\n",
" temp = np.where(np.array(nodes) == name)\n",
" row_idx.append(temp[0][0])\n",
"\n",
"col_idx = []\n",
"for document in documents:\n",
" temp = np.where(np.array(nodes) == document)\n",
" col_idx.append(temp[0][0])\n",
"\n",
"column_names = lrst['class'].unique().tolist()\n",
"doc_matrix = pd.DataFrame(data[np.ix_(row_idx, col_idx)].todense(), columns = column_names)\n",
"doc_matrix.insert(0, 'name', pd.Series(names)) \n",
"doc_matrix"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"application/vnd.google.colaboratory.module+javascript": "\n import \"https://ssl.gstatic.com/colaboratory/data_table/a6224c040fa35dcf/data_table.js\";\n\n window.createDataTable({\n data: [[{\n 'v': 0,\n 'f': \"0\",\n },\n\"Carole \",\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n }],\n [{\n 'v': 1,\n 'f': \"1\",\n },\n\"Wood\",\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n }],\n [{\n 'v': 2,\n 'f': \"2\",\n },\n\"Terrence \",\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n }],\n [{\n 'v': 3,\n 'f': \"3\",\n },\n\"Bowen\",\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n }],\n [{\n 'v': 4,\n 'f': \"4\",\n },\n\"Anne\",\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n }],\n [{\n 'v': 5,\n 'f': \"5\",\n },\n\"Singleton\",\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n }],\n [{\n 'v': 6,\n 'f': \"6\",\n },\n\"Yvette\",\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n }],\n [{\n 'v': 7,\n 'f': \"7\",\n },\n\"Edwards\",\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n }],\n [{\n 'v': 8,\n 'f': \"8\",\n },\n\"Foster\",\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n }],\n [{\n 'v': 9,\n 'f': \"9\",\n },\n\"Austin \",\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n }],\n [{\n 'v': 10,\n 'f': \"10\",\n },\n\"Montgomery\",\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n }],\n [{\n 'v': 11,\n 'f': \"11\",\n },\n\"Lorena\",\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n }],\n [{\n 'v': 12,\n 'f': \"12\",\n },\n\"Kirk\",\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n }],\n [{\n 'v': 13,\n 'f': \"13\",\n },\n\"Alexander\",\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 0,\n 'f': \"0\",\n },\n{\n 'v': 1,\n 'f': \"1\",\n }]],\n columns: [[\"number\", \"index\"], [\"string\", \"name\"], [\"number\", \"Math\"], [\"number\", \"English\"], [\"number\", \"PE\"], [\"number\", \"History\"]],\n columnOptions: [{\"width\": \"1px\", \"className\": \"index_column\"}],\n rowsPerPage: 25,\n helpUrl: \"https://colab.research.google.com/notebooks/data_table.ipynb\",\n suppressOutputScrolling: true,\n minimumWidth: undefined,\n });\n ",
"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>name</th>\n",
" <th>Math</th>\n",
" <th>English</th>\n",
" <th>PE</th>\n",
" <th>History</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Carole</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Wood</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Terrence</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Bowen</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Anne</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Singleton</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Yvette</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>Edwards</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>Foster</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Austin</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>Montgomery</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>Lorena</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>Kirk</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Alexander</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" name Math English PE History\n",
"0 Carole 1 0 0 0\n",
"1 Wood 1 0 0 0\n",
"2 Terrence 1 0 1 0\n",
"3 Bowen 1 0 0 0\n",
"4 Anne 0 1 0 0\n",
"5 Singleton 0 1 0 0\n",
"6 Yvette 0 1 0 1\n",
"7 Edwards 0 0 1 0\n",
"8 Foster 0 0 1 0\n",
"9 Austin 0 0 1 0\n",
"10 Montgomery 0 0 0 1\n",
"11 Lorena 0 0 0 1\n",
"12 Kirk 0 0 0 1\n",
"13 Alexander 0 0 0 1"
]
},
"metadata": {
"tags": []
},
"execution_count": 7
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "A1jAbNVsKOrB",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 576
},
"outputId": "39dbcf2e-ad14-498a-9636-7816e50aee05"
},
"source": [
"G = NetworkViz(notebook=True)\n",
"G.from_nx(df)\n",
"G.show(\"example.html\")"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": [
"<html>\n",
"<head>\n",
"<link rel=\"stylesheet\" href=\"https://cdnjs.cloudflare.com/ajax/libs/vis/4.16.1/vis.css\" type=\"text/css\" />\n",
"<script type=\"text/javascript\" src=\"https://cdnjs.cloudflare.com/ajax/libs/vis/4.16.1/vis-network.min.js\"> </script>\n",
"<center>\n",
"<h1>None</h1>\n",
"</center>\n",
"\n",
"<!-- <link rel=\"stylesheet\" href=\"../node_modules/vis/dist/vis.min.css\" type=\"text/css\" />\n",
"<script type=\"text/javascript\" src=\"../node_modules/vis/dist/vis.js\"> </script>-->\n",
"\n",
"<style type=\"text/css\">\n",
"\n",
" #mynetwork {\n",
" width: 500px;\n",
" height: 500px;\n",
" background-color: #ffffff;\n",
" border: 1px solid lightgray;\n",
" position: relative;\n",
" float: left;\n",
" }\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" \n",
"</style>\n",
"\n",
"</head>\n",
"\n",
"<body>\n",
"<div id = \"mynetwork\"></div>\n",
"\n",
"\n",
"<script type=\"text/javascript\">\n",
"\n",
" // initialize global variables.\n",
" var edges;\n",
" var nodes;\n",
" var network; \n",
" var container;\n",
" var options, data;\n",
"\n",
" \n",
" // This method is responsible for drawing the graph, returns the drawn network\n",
" function drawGraph() {\n",
" var container = document.getElementById('mynetwork');\n",
" \n",
" \n",
"\n",
" // parsing and collecting nodes and edges from the python\n",
" nodes = new vis.DataSet([{\"id\": \"Math\", \"label\": \"Math\", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"Carole \", \"label\": \"Carole \", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"Wood\", \"label\": \"Wood\", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"Terrence \", \"label\": \"Terrence \", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"Bowen\", \"label\": \"Bowen\", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"PE\", \"label\": \"PE\", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"English\", \"label\": \"English\", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"Anne\", \"label\": \"Anne\", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"Singleton\", \"label\": \"Singleton\", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"Yvette\", \"label\": \"Yvette\", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"History\", \"label\": \"History\", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"Edwards\", \"label\": \"Edwards\", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"Foster\", \"label\": \"Foster\", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"Austin \", \"label\": \"Austin \", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"Montgomery\", \"label\": \"Montgomery\", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"Lorena\", \"label\": \"Lorena\", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"Kirk\", \"label\": \"Kirk\", \"shape\": \"dot\", \"size\": 10}, {\"id\": \"Alexander\", \"label\": \"Alexander\", \"shape\": \"dot\", \"size\": 10}]);\n",
" edges = new vis.DataSet([{\"from\": \"Math\", \"to\": \"Carole \", \"weight\": 1}, {\"from\": \"Math\", \"to\": \"Wood\", \"weight\": 1}, {\"from\": \"Math\", \"to\": \"Terrence \", \"weight\": 1}, {\"from\": \"Math\", \"to\": \"Bowen\", \"weight\": 1}, {\"from\": \"Terrence \", \"to\": \"PE\", \"weight\": 1}, {\"from\": \"English\", \"to\": \"Anne\", \"weight\": 1}, {\"from\": \"English\", \"to\": \"Singleton\", \"weight\": 1}, {\"from\": \"English\", \"to\": \"Yvette\", \"weight\": 1}, {\"from\": \"Yvette\", \"to\": \"History\", \"weight\": 1}, {\"from\": \"PE\", \"to\": \"Edwards\", \"weight\": 1}, {\"from\": \"PE\", \"to\": \"Foster\", \"weight\": 1}, {\"from\": \"PE\", \"to\": \"Austin \", \"weight\": 1}, {\"from\": \"History\", \"to\": \"Montgomery\", \"weight\": 1}, {\"from\": \"History\", \"to\": \"Lorena\", \"weight\": 1}, {\"from\": \"History\", \"to\": \"Kirk\", \"weight\": 1}, {\"from\": \"History\", \"to\": \"Alexander\", \"weight\": 1}]);\n",
"\n",
" // adding nodes and edges to the graph\n",
" data = {nodes: nodes, edges: edges};\n",
"\n",
" var options = {\n",
" \"configure\": {\n",
" \"enabled\": false\n",
" },\n",
" \"edges\": {\n",
" \"color\": {\n",
" \"inherit\": true\n",
" },\n",
" \"smooth\": {\n",
" \"enabled\": false,\n",
" \"type\": \"continuous\"\n",
" }\n",
" },\n",
" \"interaction\": {\n",
" \"dragNodes\": true,\n",
" \"hideEdgesOnDrag\": false,\n",
" \"hideNodesOnDrag\": false\n",
" },\n",
" \"physics\": {\n",
" \"enabled\": true,\n",
" \"stabilization\": {\n",
" \"enabled\": true,\n",
" \"fit\": true,\n",
" \"iterations\": 1000,\n",
" \"onlyDynamicEdges\": false,\n",
" \"updateInterval\": 50\n",
" }\n",
" }\n",
"};\n",
" \n",
" \n",
"\n",
" \n",
"\n",
" network = new vis.Network(container, data, options);\n",
"\n",
" \n",
"\n",
"\n",
" \n",
"\n",
" return network;\n",
"\n",
" }\n",
"\n",
" drawGraph();\n",
"\n",
"</script>\n",
"</body>\n",
"</html>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
},
"execution_count": 8
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "Ih6-1VeHBzzv"
},
"source": [
""
],
"execution_count": null,
"outputs": []
}
]
}