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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "IdeologyAnalyzer.ipynb",
"version": "0.3.2",
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"metadata": {
"id": "iU5O8J5DCKGN",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"from google.colab import drive\n",
"drive.mount('/content/gdrive')"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "fi7ynVsgC8AR",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"df = pd.read_csv('/content/gdrive/PATH/TO/YOUR/VOTES/votes.csv', header=None, usecols=range(2,11)).transpose()\n",
"votes = np.where(df < 0, 0, df)"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "FqCxCZCSEjU7",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"import numpy as np\n",
"from sklearn.decomposition import PCA\n",
"\n",
"pca = PCA(n_components=2)\n",
"reduced = pca.fit_transform(votes)"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "DgN1LIbDsU-W",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"ev_ratio = pca.explained_variance_ratio_\n",
"print(ev_ratio)"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "bbWz67G6FR5m",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"colors = ['#ff2800', '#faf500', '#35a16b', '#0041ff', '#66ccff', '#ff99a0', '#ff9900', '#9a0079', '#663300']\n",
"parties = ['Kashiwa-Seifu', 'Komei-to', 'NihonKyosan-to', 'Hakuai Club', 'Simin Side Net', 'Goken Shimin Kaigi', 'Hiroki Uchida', 'Kamihashi Izumi', 'Kitamura Kazuyuki']\n",
"for i, row in enumerate(reduced):\n",
" plt.scatter(row[0], row[1], color=colors[i], label=parties[i])\n",
"\n",
"plt.legend(loc='upper left')\n"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "JTIk1p8YTKhz",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"import json\n",
"\n",
"class MyEncoder(json.JSONEncoder):\n",
" def default(self, obj):\n",
" if isinstance(obj, np.integer):\n",
" return int(obj)\n",
" elif isinstance(obj, np.ndarray):\n",
" return obj.tolist()\n",
" else:\n",
" return super(MyEncoder, self).default(obj)\n",
"\n",
"party_names = ['柏清風', '公明党', '日本共産党', '柏愛倶楽部', '市民サイド・ネット', '護憲市民会議', '内田博紀', '上橋泉', '北村和之']\n",
"parties = [{'name': name, 'point': reduced[i]} for i, name in enumerate(party_names)]\n",
" \n",
"with open('/content/gdrive/PATH/TO/YOUR/ANALYZED/RESULT/ideology.json', 'w') as out:\n",
" out.write(json.dumps({'ideology': {'parties': parties}}, cls = MyEncoder))"
],
"execution_count": 0,
"outputs": []
}
]
}
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