{
"cells": [
{
"cell_type": "code",
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"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import plotly.express as px\n",
"import plotly.graph_objects as go"
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},
{
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"metadata": {},
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"df = pd.read_csv(r\"..\\weird_fiction_visualizations\\gephi_edges.csv\")\n",
"df = df.dropna()\n",
"df['target'] = df['target'].astype('int')\n",
"df['week_']"
]
},
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"source": [
"fig = px.scatter(df, x='source', y='target', color='semester')\n",
"fig.show()\n",
"\n",
"fig = go.Figure()\n",
"\n",
"fig.add_trace(go.Scatter(x=df['source'], y=df['target'], mode='markers', name='markers'))\n",
"fig.add_trace(go.Scatter(x=df['source'], y=df['target'], mode='lines+markers', name='lines+markers'))\n",
"fig.show()\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" source target semester week_read color\n",
"0 324 342 Fall 2021 15.0 green\n",
"1 347 320 Fall 2021 15.0 green\n",
"2 342 339 Fall 2021 15.0 green\n",
"3 346 339 Fall 2021 15.0 green\n",
"4 329 337 Fall 2021 15.0 green\n",
" source target semester week_read color\n",
"7843 362 108 Spring 2022 15.0 magenta\n",
"7844 381 35 Spring 2022 15.0 magenta\n",
"7845 381 36 Spring 2022 15.0 magenta\n",
"7846 381 90 Spring 2022 15.0 magenta\n",
"7847 158 118 Spring 2022 15.0 magenta\n"
]
}
],
"source": [
"color_dictionary = {'Fall 2019': 'red', 'Fall 2020': 'blue', 'Fall 2021': 'green', 'Spring 2020': 'mediumorchid', 'Spring 2021': 'gold', 'Spring 2022': 'magenta', 'Summer 2020': 'brown', 'Summer 2021': 'purple'}\n",
"\n",
"df['color'] = df['semester'].map(color_dictionary)\n",
"print(df.head())\n",
"print(df.tail())"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"c:\\Users\\KSpicer\\Anaconda3\\envs\\victorian_authorship_env\\lib\\site-packages\\scipy\\__init__.py:146: UserWarning:\n",
"\n",
"A NumPy version >=1.16.5 and <1.23.0 is required for this version of SciPy (detected version 1.23.1\n",
"\n"
]
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'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta', 'magenta']\n"
]
}
],
"source": [
"import networkx as nx\n",
"G = nx.from_pandas_edgelist(df, source='source', target='target', create_using=nx.DiGraph)\n",
"colors = []\n",
"\n",
"for index, row in df.iterrows():\n",
" colors.append(row['color'])\n",
"\n",
"print(colors)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"val_map = dict(zip(df.source, df.target))"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"values = [val_map.get(node, 0.25) for node in G.nodes]"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"nx.draw(G, cmap=plt.get_cmap('viridis'), node_color = values, with_labels=True)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"df_edges = pd.read_csv('gephi_edges.csv')\n",
"df_nodes = pd.read_csv('node_list.csv')\n",
"df_nodes = df_nodes.dropna(axis=0)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"node_colors = {'Fall 2019': 'red', 'Fall 2020': 'blue', 'Fall 2021': 'green', 'Spring 2020': 'mediumorchid', 'Spring 2021': 'gold', 'Spring 2022': 'magenta', 'Summer 2020': 'brown', 'Summer 2021': 'purple', 'all': 'lavender'}"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"df_nodes['node_color'] = df_nodes['semester'].map(node_colors)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"G = nx.from_pandas_edgelist(df_edges, source='source', target='target')\n"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'name': 'ChelseaB', 'semester': 'Fall 2021', 'node_color': 'green'}\n"
]
}
],
"source": [
"nodes_attr = df_nodes.set_index('id').to_dict(orient='index')\n",
"nx.set_node_attributes(G, nodes_attr)\n",
"print(G.nodes[324])"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"ename": "KeyError",
"evalue": "''",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)",
"File \u001b[1;32mc:\\Users\\KSpicer\\Anaconda3\\envs\\victorian_authorship_env\\lib\\site-packages\\pandas\\core\\indexes\\base.py:3621\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[1;34m(self, key, method, tolerance)\u001b[0m\n\u001b[0;32m 3620\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m-> 3621\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_engine\u001b[39m.\u001b[39;49mget_loc(casted_key)\n\u001b[0;32m 3622\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mKeyError\u001b[39;00m \u001b[39mas\u001b[39;00m err:\n",
"File \u001b[1;32mc:\\Users\\KSpicer\\Anaconda3\\envs\\victorian_authorship_env\\lib\\site-packages\\pandas\\_libs\\index.pyx:136\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[1;34m()\u001b[0m\n",
"File \u001b[1;32mc:\\Users\\KSpicer\\Anaconda3\\envs\\victorian_authorship_env\\lib\\site-packages\\pandas\\_libs\\index.pyx:163\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[1;34m()\u001b[0m\n",
"File \u001b[1;32mpandas\\_libs\\hashtable_class_helper.pxi:5198\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[1;34m()\u001b[0m\n",
"File \u001b[1;32mpandas\\_libs\\hashtable_class_helper.pxi:5206\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[1;34m()\u001b[0m\n",
"\u001b[1;31mKeyError\u001b[0m: ''",
"\nThe above exception was the direct cause of the following exception:\n",
"\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32mc:\\Users\\KSpicer\\Documents\\GitHub\\solo_projects\\weird_fiction_visualizations\\short_scatter.ipynb Cell 14\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[39mfor\u001b[39;00m index, row \u001b[39min\u001b[39;00m df_nodes\u001b[39m.\u001b[39miterrows():\n\u001b[1;32m----> 2\u001b[0m G\u001b[39m.\u001b[39mnodes[row[\u001b[39m'\u001b[39m\u001b[39msource\u001b[39m\u001b[39m'\u001b[39m]][\u001b[39m'\u001b[39m\u001b[39mnode_color\u001b[39m\u001b[39m'\u001b[39m] \u001b[39m=\u001b[39m row[\u001b[39m'\u001b[39;49m\u001b[39m'\u001b[39;49m]\n",
"File \u001b[1;32mc:\\Users\\KSpicer\\Anaconda3\\envs\\victorian_authorship_env\\lib\\site-packages\\pandas\\core\\series.py:958\u001b[0m, in \u001b[0;36mSeries.__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m 955\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_values[key]\n\u001b[0;32m 957\u001b[0m \u001b[39melif\u001b[39;00m key_is_scalar:\n\u001b[1;32m--> 958\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_get_value(key)\n\u001b[0;32m 960\u001b[0m \u001b[39mif\u001b[39;00m is_hashable(key):\n\u001b[0;32m 961\u001b[0m \u001b[39m# Otherwise index.get_value will raise InvalidIndexError\u001b[39;00m\n\u001b[0;32m 962\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m 963\u001b[0m \u001b[39m# For labels that don't resolve as scalars like tuples and frozensets\u001b[39;00m\n",
"File \u001b[1;32mc:\\Users\\KSpicer\\Anaconda3\\envs\\victorian_authorship_env\\lib\\site-packages\\pandas\\core\\series.py:1069\u001b[0m, in \u001b[0;36mSeries._get_value\u001b[1;34m(self, label, takeable)\u001b[0m\n\u001b[0;32m 1066\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_values[label]\n\u001b[0;32m 1068\u001b[0m \u001b[39m# Similar to Index.get_value, but we do not fall back to positional\u001b[39;00m\n\u001b[1;32m-> 1069\u001b[0m loc \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mindex\u001b[39m.\u001b[39;49mget_loc(label)\n\u001b[0;32m 1070\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mindex\u001b[39m.\u001b[39m_get_values_for_loc(\u001b[39mself\u001b[39m, loc, label)\n",
"File \u001b[1;32mc:\\Users\\KSpicer\\Anaconda3\\envs\\victorian_authorship_env\\lib\\site-packages\\pandas\\core\\indexes\\base.py:3623\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[1;34m(self, key, method, tolerance)\u001b[0m\n\u001b[0;32m 3621\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_engine\u001b[39m.\u001b[39mget_loc(casted_key)\n\u001b[0;32m 3622\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mKeyError\u001b[39;00m \u001b[39mas\u001b[39;00m err:\n\u001b[1;32m-> 3623\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mKeyError\u001b[39;00m(key) \u001b[39mfrom\u001b[39;00m \u001b[39merr\u001b[39;00m\n\u001b[0;32m 3624\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mTypeError\u001b[39;00m:\n\u001b[0;32m 3625\u001b[0m \u001b[39m# If we have a listlike key, _check_indexing_error will raise\u001b[39;00m\n\u001b[0;32m 3626\u001b[0m \u001b[39m# InvalidIndexError. Otherwise we fall through and re-raise\u001b[39;00m\n\u001b[0;32m 3627\u001b[0m \u001b[39m# the TypeError.\u001b[39;00m\n\u001b[0;32m 3628\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_check_indexing_error(key)\n",
"\u001b[1;31mKeyError\u001b[0m: ''"
]
}
],
"source": [
"for index, row in df_nodes.iterrows():\n",
" G.nodes[row['source']]['node_color'] = row['']"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"ename": "KeyError",
"evalue": "'node_color'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32mc:\\Users\\KSpicer\\Documents\\GitHub\\solo_projects\\weird_fiction_visualizations\\short_scatter.ipynb Cell 14\u001b[0m in \u001b[0;36m| \u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m plt\u001b[39m.\u001b[39mfigure(figsize\u001b[39m=\u001b[39m(\u001b[39m15\u001b[39m, \u001b[39m8\u001b[39m))\n\u001b[0;32m 2\u001b[0m nx\u001b[39m.\u001b[39mdraw_networkx(G,\n\u001b[0;32m 3\u001b[0m pos\u001b[39m=\u001b[39mnx\u001b[39m.\u001b[39mkamada_kawai_layout(G),\n\u001b[0;32m 4\u001b[0m node_size\u001b[39m=\u001b[39m\u001b[39m200\u001b[39m,\n\u001b[1;32m----> 5\u001b[0m node_color\u001b[39m=\u001b[39m[G\u001b[39m.\u001b[39mnodes[n][\u001b[39m'\u001b[39m\u001b[39mnode_color\u001b[39m\u001b[39m'\u001b[39m] \u001b[39mfor\u001b[39;00m n \u001b[39min\u001b[39;00m G\u001b[39m.\u001b[39mnodes],\n\u001b[0;32m 6\u001b[0m with_labels\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m)\n\u001b[0;32m 7\u001b[0m plt\u001b[39m.\u001b[39mplot()\n",
"\u001b[1;32mc:\\Users\\KSpicer\\Documents\\GitHub\\solo_projects\\weird_fiction_visualizations\\short_scatter.ipynb Cell 14\u001b[0m in \u001b[0;36m\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m 1\u001b[0m plt\u001b[39m.\u001b[39mfigure(figsize\u001b[39m=\u001b[39m(\u001b[39m15\u001b[39m, \u001b[39m8\u001b[39m))\n\u001b[0;32m 2\u001b[0m nx\u001b[39m.\u001b[39mdraw_networkx(G,\n\u001b[0;32m 3\u001b[0m pos\u001b[39m=\u001b[39mnx\u001b[39m.\u001b[39mkamada_kawai_layout(G),\n\u001b[0;32m 4\u001b[0m node_size\u001b[39m=\u001b[39m\u001b[39m200\u001b[39m,\n\u001b[1;32m----> 5\u001b[0m node_color\u001b[39m=\u001b[39m[G\u001b[39m.\u001b[39;49mnodes[n][\u001b[39m'\u001b[39;49m\u001b[39mnode_color\u001b[39;49m\u001b[39m'\u001b[39;49m] \u001b[39mfor\u001b[39;00m n \u001b[39min\u001b[39;00m G\u001b[39m.\u001b[39mnodes],\n\u001b[0;32m 6\u001b[0m with_labels\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m)\n\u001b[0;32m 7\u001b[0m plt\u001b[39m.\u001b[39mplot()\n",
"\u001b[1;31mKeyError\u001b[0m: 'node_color'"
]
},
{
"data": {
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(15, 8))\n",
"nx.draw_networkx(G,\n",
" pos=nx.kamada_kawai_layout(G),\n",
" node_size=200,\n",
" node_color=[G.nodes[n]['node_color'] for n in G.nodes],\n",
" with_labels=True)\n",
"plt.plot()"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import networkx as nx\n",
"import pandas as pd\n",
"df_edges = pd.read_csv('gephi_edges.csv')\n",
"df_edges = df_edges.dropna(axis=0)\n",
"df_nodes = pd.read_csv('node_list.csv')\n",
"df_nodes = df_nodes.dropna(axis=0)\n",
"df_edges['target'] = df_edges['target'].astype('int')"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" id name semester\n",
"0 1 Lovecrafts Supernatural Horror all\n",
"1 2 Lois Tyson all\n",
"2 3 Michael Moorcock all\n",
"3 4 Jeff VanderMeers Introduction all\n",
"4 5 Sigmund Freud all\n",
" source target semester week_read\n",
"0 324 342.0 Fall 2021 15.0\n",
"1 347 320.0 Fall 2021 15.0\n",
"2 342 339.0 Fall 2021 15.0\n",
"3 346 339.0 Fall 2021 15.0\n",
"4 329 337.0 Fall 2021 15.0\n"
]
}
],
"source": [
"print(df_nodes.head())\n",
"print(df_edges.head())"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.9.12 ('victorian_authorship_env')",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.12"
},
"orig_nbformat": 4,
"vscode": {
"interpreter": {
"hash": "ef5d861bb1be136369da2a14d97f47e042662aed23f513481be9d838db3326bb"
}
}
},
"nbformat": 4,
"nbformat_minor": 2
}
| |