{"id":50743,"date":"2021-05-28T00:00:00","date_gmt":"2021-05-28T07:00:00","guid":{"rendered":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/%e6%9c%aa%e5%88%86%e9%a1%9e\/graphical-analysis-of-nobel-prize-laureates\/"},"modified":"2025-11-14T07:54:37","modified_gmt":"2025-11-14T15:54:37","slug":"graphical-analysis-of-nobel-prize-laureates","status":"publish","type":"post","link":"https:\/\/www.griddb.net\/ja\/%e6%9c%aa%e5%88%86%e9%a1%9e\/graphical-analysis-of-nobel-prize-laureates\/","title":{"rendered":"\u30ce\u30fc\u30d9\u30eb\u8cde\u53d7\u8cde\u8005\u306e\u50be\u5411\u3092\u30b0\u30e9\u30d5\u3067\u5206\u6790\u3059\u308b"},"content":{"rendered":"<h1>\u306f\u3058\u3081\u306b<\/h1>\n<p>\u30ce\u30fc\u30d9\u30eb\u8cde\u306f\u3001\u304a\u305d\u3089\u304f\u4e16\u754c\u3067\u6700\u3082\u3088\u304f\u77e5\u3089\u308c\u305f\u540d\u8a89\u3042\u308b\u8cde\u3067\u3059\u3002\u4e16\u754c\u4e2d\u306e\u5c02\u9580\u5bb6\u3084\u6d3b\u52d5\u5bb6\u304c\u3001\u30ce\u30fc\u30d9\u30eb\u8cde\u53d7\u8cde\u8005\u306b\u306a\u308a\u305d\u308c\u305e\u308c\u306e\u5206\u91ce\u3067\u305d\u306e\u5a01\u5149\u3092\u5206\u304b\u3061\u5408\u3046\u3053\u3068\u3092\u5922\u898b\u3066\u3044\u307e\u3059\u3002\u30d3\u30b8\u30cd\u30b9\u30ea\u30fc\u30c0\u30fc\u3084\u30c7\u30fc\u30bf\u30a2\u30ca\u30ea\u30b9\u30c8\u305f\u3061\u306b\u3068\u3063\u3066\u3001\u3053\u306e\u91cd\u8981\u3067\u5a01\u4fe1\u306e\u3042\u308b\u30ce\u30fc\u30d9\u30eb\u8cde\u306b\u5bfe\u3057\u3066\u63a2\u7d22\u7684\u5206\u6790\u3084\u4e88\u6e2c\u5206\u6790\u3092\u884c\u3044\u6642\u7cfb\u5217\u3067\u306e\u30ce\u30fc\u30d9\u30eb\u8cde\u53d7\u8cde\u8005\u306e\u50be\u5411\u3092\u8abf\u3079\u308b\u3053\u3068\u306f\u3001\u3068\u3066\u3082\u30a8\u30ad\u30b5\u30a4\u30c6\u30a3\u30f3\u30b0\u306a\u3053\u3068\u3067\u3059\u3002<\/p>\n<p>\u7814\u7a76\u8005\u3084\u30a2\u30ca\u30ea\u30b9\u30c8\u304c\u6ce8\u76ee\u3059\u308b\u3053\u306e\u30ce\u30fc\u30d9\u30eb\u8cde\u306b\u95a2\u3059\u308b\u5206\u6790\u306f\u3001\u6642\u7cfb\u5217\u7684\u306a\u6d3b\u52d5\u306b\u95a2\u9023\u3057\u3066\u3044\u308b\u305f\u3081\u3001\u305d\u306e\u3088\u3046\u306a\u6642\u7cfb\u5217\u7684\u306a\u8907\u96d1\u3055\u306b\u5bfe\u5fdc\u3067\u304d\u308b\u3088\u3046\u306b\u8a2d\u8a08\u30fb\u6700\u9069\u5316\u3055\u308c\u3066\u3044\u308bGridDB\u306f\u7406\u60f3\u7684\u306a\u5206\u6790\u30c4\u30fc\u30eb\u3067\u3042\u308b\u3068\u8a00\u3048\u307e\u3059\u3002<\/p>\n<p>GridDB\u3068Python\u306e\u30b7\u30fc\u30e0\u30ec\u30b9\u306a\u7d71\u5408\u306f\u3001\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u8a00\u8a9e\u306e\u30c7\u30d5\u30a1\u30af\u30c8\u30ea\u30fc\u30c0\u30fc\u3092\u6d3b\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u7af6\u4e89\u4e0a\u306e\u512a\u4f4d\u6027\u3092\u3082\u305f\u3089\u3057\u307e\u3059\u3002\u4eca\u56de\u306f\u3001IoT\u3084\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u306b\u6700\u9069\u5316\u3055\u308c\u305f\u62e1\u5f35\u6027\u306e\u9ad8\u3044\u30a4\u30f3\u30e1\u30e2\u30eaNoSQL\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u3067\u3042\u308bGridDB\u3092\u4f7f\u3063\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n<p>The Nobel Foundation\u304c\u63d0\u4f9b\u3059\u308b\u30011901\u5e74\u306e\u30ce\u30fc\u30d9\u30eb\u8cde\u958b\u59cb\u304b\u30892016\u5e74\u307e\u3067\u306e\u5168\u53d7\u8cde\u8005\u306e\u4eba\u53e3\u7d71\u8a08\u30c7\u30fc\u30bf\u3092\u8996\u899a\u7684\u306b\u5206\u6790\u3059\u308b\u3053\u3068\u3092\u76ee\u7684\u3068\u3057\u305f\u7c21\u5358\u306a\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3092\u901a\u3058\u3066\u3001GridDB\u3092\u4f7f\u3044\u59cb\u3081\u308b\u305f\u3081\u306e\u30b9\u30c6\u30c3\u30d7\u30d0\u30a4\u30b9\u30c6\u30c3\u30d7\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3092\u3054\u7d39\u4ecb\u3057\u307e\u3059\u3002\u305d\u308c\u3067\u306f\u3001\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u8fbc\u3093\u3067\u898b\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n<h2>Ubuntu\u4e0a\u3067GridDB\u3092\u8a2d\u5b9a\u3059\u308b<\/h2>\n<p>\u5b9f\u969b\u306e\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3068\u305d\u306e\u5b9f\u88c5\u4f5c\u696d\u306b\u5165\u308b\u524d\u306b\u3001\u304a\u4f7f\u3044\u306e\u30b7\u30b9\u30c6\u30e0\u3067GridDB\u304c\u7a3c\u50cd\u3057\u3066\u3044\u308b\u3053\u3068\u3092\u78ba\u8a8d\u3057\u3066\u304f\u3060\u3055\u3044\u3002Ubuntu\u3084CentOS\u3067\u306eGridDB\u306e\u8a2d\u5b9a\u306b\u3064\u3044\u3066\u306e\u8a73\u7d30\u306f\u3001<a href=\"https:\/\/griddb.net\/en\/blog\/griddb-quickstart\/\">GridDB\u306e\u30af\u30a4\u30c3\u30af\u30b9\u30bf\u30fc\u30c8\u30ac\u30a4\u30c9<\/a>\u3092\u3054\u53c2\u7167\u304f\u3060\u3055\u3044\u3002<\/p>\n<h2>\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8<\/h2>\n<p>\u4eca\u56de\u306e\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3067\u306f\u3001Kaggle\u3067\u516c\u958b\u3055\u308c\u3066\u3044\u308b<a href=\"https:\/\/www.kaggle.com\/nobelfoundation\/nobel-laureates\">Nobel Laureates \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8<\/a>\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/p>\n<h2>\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306b\u30d5\u30a1\u30a4\u30eb\u3092\u8aad\u307f\u8fbc\u3080<\/h2>\n<p>Python\u306b\u306f\u3001\u30c7\u30fc\u30bf\u95a2\u9023\u306e\u8907\u96d1\u306a\u30bf\u30b9\u30af\u3092\u5b9f\u884c\u3059\u308b\u305f\u3081\u306b\u7279\u5225\u306b\u8a2d\u8a08\u3001\u5b9f\u88c5\u3001\u6700\u9069\u5316\u3055\u308c\u305fPandas\u3068\u3044\u3046\u512a\u308c\u305f\u30e9\u30a4\u30d6\u30e9\u30ea\u304c\u7528\u610f\u3055\u308c\u3066\u304a\u308a\u3001\u63a2\u7d22\u5206\u6790\u3084\u4e88\u6e2c\u5206\u6790\u3092\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002Pandas\u306b\u306f\u3001\u30a2\u30ca\u30ea\u30b9\u30c8\u3084\u79d1\u5b66\u8005\u304cCSV\u30d5\u30a1\u30a4\u30eb\u304b\u3089\u306e\u30c7\u30fc\u30bf\u62bd\u51fa\u3092\u542b\u3080\u30a8\u30f3\u30c9\u30fb\u30c4\u30fc\u30fb\u30a8\u30f3\u30c9\u306e\u30d7\u30ed\u30bb\u30b9\u3092\u30b9\u30e0\u30fc\u30ba\u306b\u5b9f\u884c\u3059\u308b\u305f\u3081\u306e\u69d8\u3005\u306a\u30e2\u30b8\u30e5\u30fc\u30eb\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">\n# Read CSV file\nnobelprize_data = pd.read_CSV(\"nobel.CSV\")\n<\/code><\/pre>\n<\/div>\n<p>\u4e0a\u306e\u30b3\u30fc\u30c9\u30b9\u30cb\u30da\u30c3\u30c8\u3067\u306f\u3001CSV\u30d5\u30a1\u30a4\u30eb\u3092\u8aad\u307f\u8fbc\u3093\u3067Pandas\u306e\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u3092\u4f5c\u6210\u3057\u3001\u30c7\u30fc\u30bf\u306e\u7ba1\u7406\u3001\u5909\u63db\u3001\u524d\u51e6\u7406\u3092\u884c\u3063\u3066\u3044\u307e\u3059\u3002<\/p>\n<h2>\u30c7\u30fc\u30bf\u306e\u524d\u51e6\u7406<\/h2>\n<p>\u5148\u307b\u3069Pandas\u306e\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306b\u683c\u7d0d\u3057\u305f\u30c7\u30fc\u30bf\u3092\u4f7f\u3063\u3066\u3001\u524d\u51e6\u7406\u3092\u884c\u3044\u307e\u3059\u3002\u524d\u51e6\u7406\u30b9\u30af\u30ea\u30d7\u30c8\u3092\u4f55\u5ea6\u3082\u5b9f\u884c\u3057\u306a\u304f\u3066\u6e08\u3080\u3088\u3046\u306b\u3001\u30e6\u30fc\u30b9\u30b1\u30fc\u30b9\u306b\u95a2\u9023\u3059\u308b\u30c7\u30fc\u30bf\u30dd\u30a4\u30f3\u30c8\u3092\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u3057\u3001\u30c7\u30fc\u30bf\u3092\u30af\u30ea\u30fc\u30cb\u30f3\u30b0\u3057\u3001\u51e6\u7406\u3057\u305f\u30c7\u30fc\u30bf\u3092\u65b0\u3057\u3044CSV\u30d5\u30a1\u30a4\u30eb\u306b\u4fdd\u5b58\u3057\u307e\u3059\u3002<\/p>\n<p>\u3053\u306eCSV\u306b\u306f\u3001\u79c1\u305f\u3061\u306e\u5206\u6790\u306b\u3068\u3063\u3066\u91cd\u8981\u3067\u306f\u306a\u3044\u591a\u304f\u306e\u5217\u304c\u542b\u307e\u308c\u3066\u3044\u308b\u305f\u3081\u3001\u3053\u306e\u521d\u5fc3\u8005\u306e\u6bb5\u968e\u3067\u30c7\u30fc\u30bf\u3092\u3088\u308a\u6df1\u304f\u7406\u89e3\u3059\u308b\u305f\u3081\u306b\u306f\u3001\u5217\u6570\u306f\u5c11\u306a\u304f\u6e1b\u3089\u3059\u65b9\u304c\u826f\u3044\u3067\u3057\u3087\u3046\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">\n# Drop irrelevant columns\nnobelprize_data = nobelprize_data.drop(labels = \n    [\"Motivation\",\"Full Name\", \"Birth Date\",\n    \"Birth City\" , \"Birth Country\",\n    \"Death Date\", \"Death City\" , \"Death Country\" ,\n    \"Organization City\", \"Organization Country\",\n    \"Organization Name\"], axis = 1)\n<\/code><\/pre>\n<\/div>\n<p>\u3044\u304f\u3064\u304b\u306e\u5217\u3092\u524a\u9664\u3059\u308b\u3068\u3001\u4ee5\u4e0b\u306e\u3088\u3046\u306a\u5217\u304c\u6b8b\u308a\u307e\u3059\u3002<\/p>\n<ul>\n<li>Year\uff08\u53d7\u8cde\u5e74\uff09<\/li>\n<li>Category\uff08\u53d7\u8cde\u90e8\u9580\uff09<\/li>\n<li>Prize\uff08\u53d7\u8cde\u3057\u305f\u8cde\u306e\u30bf\u30a4\u30c8\u30eb\uff09<\/li>\n<li>Prize Share\uff08\u53d7\u8cde\u767a\u8868\u65e5\uff09<\/li>\n<li>Laureate ID\uff08\u30ce\u30fc\u30d9\u30eb\u8cde\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u304c\u4ed8\u4e0e\u3059\u308b\u53d7\u8cde\u8005ID\uff09<\/li>\n<li>Laureate Type\uff08\u53d7\u8cde\u8005\u304c\u500b\u4eba\u304b\u56e3\u4f53\u304b\uff09<\/li>\n<li>Sex\uff08\u6027\u5225\uff09<\/li>\n<\/ul>\n<p>\u3055\u3089\u306b\u3001\u5217\u304c\u975enull\u3068\u3057\u3066\u8b58\u5225\u3055\u308c\u3066\u3057\u307e\u3046\u5834\u5408\u304c\u3042\u308a\u3001\u300c\u6027\u5225\u300d\u306e\u5217\u3067null\u304c\u300c\u975e\u516c\u8868\u300d\u3092\u8868\u3057\u3066\u3044\u308b\u3088\u3046\u306a\u5834\u5408\u306b\u3001\u305d\u306e\u884c\u3092\u7dad\u6301\u3059\u308b\u305f\u3081\u306b\u8a2d\u5b9a\u5909\u66f4\u3092\u884c\u3046\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">\nnobelprize_data['Sex'] = nobelprize_data['Sex'].fillna(\"Not disclosed\")\n<\/code><\/pre>\n<\/div>\n<p>\u3055\u3089\u306b\u3001\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306e\u4e3b\u30ad\u30fc\u3068\u3057\u3066\u53c2\u7167\u3059\u308b\u305f\u3081\u306b\u3001ID\u3068\u3044\u3046\u30ab\u30e9\u30e0\u3092\u5c0e\u5165\u3057\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">\n# Add auto incremental ID\nnobelprize_data.index.name = 'ID'\n<\/code><\/pre>\n<\/div>\n<p>\u3053\u3053\u3067\u3001\u3088\u308a\u5206\u304b\u308a\u3084\u3059\u304f\u306a\u308b\u3088\u3046\u306b\u30ab\u30e9\u30e0\u540d\u3092\u5909\u66f4\u3057\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">\n# Rename columns\nfixColNames = nobelprize_data.rename(columns = \n    {\"Year\": \"year\",\n    \"Category\":\"category\",\n    \"Prize\": \"prize\",\n    \"Prize Share\":\"prize_share\",\n    \"Laureate ID\":\"laureate_id\",\n    \"Laureate Type\":\"laureate_type\",\n    \"Sex\":\"sex\"})\n<\/code><\/pre>\n<\/div>\n<p>\u51e6\u7406\u3057\u305f\u30c7\u30fc\u30bf\u3092\u65b0\u3057\u3044CSV\u30d5\u30a1\u30a4\u30eb\u306b\u4fdd\u5b58\u3057\u305f\u5f8c\u3001CSV\u30d5\u30a1\u30a4\u30eb\u304b\u3089Pandas\u306e\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306b\u30c7\u30fc\u30bf\u3092\u30ed\u30fc\u30c9\u3059\u308b\u624b\u9806\u3092\u518d\u5ea6\u884c\u3044\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">\n# Generate a new processed file\nfixColNames.to_CSV(\"preprocessed.CSV\")\n<\/code><\/pre>\n<\/div>\n<p>Pandas\u306e\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306b\u30c7\u30fc\u30bf\u304c\u8aad\u307f\u8fbc\u307e\u308c\u305f\u3089\u3001\u305d\u308c\u3092GridDB\u306b\u633f\u5165\u3057\u3066\u3001\u30c7\u30fc\u30bf\u306b\u5bfe\u3057\u3066\u6700\u9069\u5316\u3055\u308c\u305f\u5206\u6790\u64cd\u4f5c\u3092\u884c\u3046\u6e96\u5099\u304c\u6574\u3044\u307e\u3057\u305f\u3002<\/p>\n<h2>GridDB\u3078\u30c7\u30fc\u30bf\u3092\u633f\u5165\u3059\u308b<\/h2>\n<p>GridDB\u304c\u30c7\u30fc\u30bf\u3092\u633f\u5165\u3059\u308b\u305f\u3081\u306b\u8a2d\u5b9a\u3057\u3066\u3044\u308b\u6a19\u6e96\u7684\u306a\u65b9\u6cd5\u306f\u3001\u30b3\u30f3\u30c6\u30ca\u3092\u4f5c\u6210\u3057\u3001put\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3067\u3059\u3002\u3053\u3053\u3067\u306f\u3001\u3053\u306e\u65b9\u6cd5\u3068Panda\u306e\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u3078\u306e\u30c7\u30fc\u30bf\u633f\u5165\u65b9\u6cd5\u3092\u7d44\u307f\u5408\u308f\u305b\u3066\u307f\u307e\u3059\u3002<\/p>\n<p>\u307e\u305a\u3001GridDB\u3067\u30b3\u30f3\u30c6\u30canobelprize_1901\u3092\u30a4\u30f3\u30b9\u30bf\u30f3\u30b9\u5316\u3057\u3001\u30c7\u30fc\u30bf\u30bf\u30a4\u30d7\u3092\u5b9a\u7fa9\u3057\u307e\u3059\u3002\u30c7\u30fc\u30bf\u30bf\u30a4\u30d7\u304c\u6b63\u3057\u3044\u3053\u3068\u3092\u78ba\u8a8d\u3057\u3066\u304a\u304b\u306a\u3044\u3068\u3001\u89e3\u6790\u6642\u306b\u30d0\u30ea\u30c7\u30fc\u30b7\u30e7\u30f3\u30a8\u30e9\u30fc\u304c\u767a\u751f\u3059\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">\n# Create Collection circuits\nnobelprize_containerInfo = GridDB.ContainerInfo(nobelprize_container,\n    [[\"ID\", GridDB.Type.INTEGER],\n    [\"year\", GridDB.Type.INTEGER],\n    [\"category\", GridDB.Type.STRING],\n    [\"prize\", GridDB.Type.STRING],\n    [\"prize_share\", GridDB.Type.STRING],\n    [\"laureate_id\", GridDB.Type.INTEGER],\n    [\"laureate_type\", GridDB.Type.STRING],\n    [\"sex\", GridDB.Type.STRING]],\n    GridDB.ContainerType.COLLECTION, True)\nnobelprize_columns = gridstore.put_container(nobelprize_containerInfo)\n<\/code><\/pre>\n<\/div>\n<p>\u30b3\u30f3\u30c6\u30ca\u306e\u6e96\u5099\u304c\u3067\u304d\u305f\u306e\u3067\u3001\u30ec\u30b3\u30fc\u30c9\u3092\u3053\u306e\u30b3\u30f3\u30c6\u30ca\u306b\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u307e\u3059\u3002GridDB\u306e<code>put_rows<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u3046\u3068\u3001\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u304b\u3089\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">\n# Put rows\nnobelprize_columns.put_rows(nobelprize_data)\n<\/code><\/pre>\n<\/div>\n<p>CSV\u306e\u30c7\u30fc\u30bf\u3068\u69cb\u9020\u304cnobelprize_1901\u306b\u53d6\u308a\u8fbc\u307e\u308c\u3001GridDB\u306e\u69cb\u9020\u5316\u3055\u308c\u305f\u30d5\u30a9\u30fc\u30de\u30c3\u30c8\u306b\u9069\u5fdc\u3055\u308c\u307e\u3057\u305f\u3002<\/p>\n<h2>GridDB\u304b\u3089\u30c7\u30fc\u30bf\u306b\u30a2\u30af\u30bb\u30b9\u3059\u308b<\/h2>\n<p>\u30c7\u30fc\u30bf\u304c GridDB \u30b3\u30f3\u30c6\u30ca\u306b\u30a4\u30f3\u30dd\u30fc\u30c8\u3055\u308c\u305f\u306e\u3067\u3001\u30c7\u30fc\u30bf\u3092\u53d6\u5f97\u3057\u307e\u3059\u3002GridDB \u306b\u306f\u72ec\u81ea\u306e\u30af\u30a8\u30ea\u8a00\u8a9e\u3067\u3042\u308b TQL \u304c\u3042\u308a\u3001\u3053\u306e\u30bd\u30fc\u30b9\u304b\u3089\u5b66\u7fd2\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002TQL \u306f GridDB \u30b3\u30f3\u30c6\u30ca\u304b\u3089\u30c7\u30fc\u30bf\u3092\u7167\u4f1a\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u3001\u6a19\u6e96\u7684\u306a SQL \u30d7\u30ed\u30c8\u30b3\u30eb\u306b\u4f3c\u305f\u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002\u3053\u3053\u3067\u306f\u3001\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u304b\u3089\u30c7\u30fc\u30bf\u3092\u53d6\u5f97\u3059\u308b\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3059\u3002GridDB \u306b\u306f\u30af\u30a8\u30ea\u6a5f\u80fd\u304c\u3042\u308a\u3001\u30e6\u30fc\u30b6\u306f\u30b3\u30f3\u30c6\u30ca\u306b\u30af\u30a8\u30ea\u3092\u767a\u884c\u3057\u3066 Database \u304b\u3089\u30c7\u30fc\u30bf\u3092\u53d6\u5f97\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u4ee5\u4e0b\u306e\u30b3\u30fc\u30c9\u30d6\u30ed\u30c3\u30af\u3092\u898b\u3066\u304f\u3060\u3055\u3044\u3002\u3053\u3053\u3067\u306f\u3001<code>get_container<\/code>\u95a2\u6570\u3092\u4f7f\u3063\u3066\u30b3\u30f3\u30c6\u30ca\u3092\u53d6\u5f97\u3057\u3001\u30b3\u30ec\u30af\u30b7\u30e7\u30f3\u3092\u7167\u4f1a\u3057\u3066\u5fc5\u8981\u306a\u30c7\u30fc\u30bf\u3092\u53d6\u308a\u51fa\u3057\u3066\u3044\u307e\u3059\u3002<code>get_container<\/code>\u95a2\u6570\u3092\u4f7f\u3063\u3066\u30b3\u30f3\u30c6\u30ca\u3092\u53d6\u5f97\u3057\u3001\u30af\u30a8\u30ea\u3092\u4f7f\u3063\u3066\u30c7\u30fc\u30bf\u3092\u62bd\u51fa\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3057\u305fTQL\u306e\u7c21\u5358\u306a\u4f8b\u3092\u7d39\u4ecb\u3057\u307e\u3059\u3002\u3053\u306e\u4f8b\u3067\u306f\u3001\u30b3\u30f3\u30c6\u30ca\u304b\u3089\u3059\u3079\u3066\u306e\u30ec\u30b3\u30fc\u30c9\u3092\u9078\u629e\u3059\u308b\u305f\u3081\u306b<code>select *<\/code>\u3092\u4f7f\u3044\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">\n# Fetch all rows - circuits_container\nquery = nobelprize_data.query(\"select *\")\n<\/code><\/pre>\n<\/div>\n<p>\u3053\u306e\u30d6\u30ed\u30b0\u306f\u3001\u3059\u3079\u3066\u306e\u30ec\u30b3\u30fc\u30c9\u3092\u9078\u629e\u3059\u308b\u30b7\u30f3\u30d7\u30eb\u306a\u30af\u30a8\u30ea\u3092\u8a18\u8ff0\u3057\u3066\u3044\u307e\u3059\u304c\u3001\u3055\u3089\u306b\u8e0f\u307f\u8fbc\u3093\u3067\u3001\u6ce8\u6587\u3001\u5236\u9650\u3001\u6761\u4ef6\u306b\u6cbf\u3063\u3066\u30c7\u30fc\u30bf\u3092\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u3059\u308b\u305f\u3081\u306b\u3001\u3055\u307e\u3056\u307e\u306a\u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002\u5148\u306b\u8ff0\u3079\u305fGridDB\u306e\u516c\u5f0f\u30da\u30fc\u30b8\u304b\u3089\u3001\u81ea\u7531\u306b\u69cb\u6587\u3092\u8abf\u3079\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n<p>GridDB\u30b3\u30f3\u30c6\u30ca\u304b\u3089\u30c7\u30fc\u30bf\u3092\u53d6\u5f97\u3057\u305f\u5f8c\u306f\u3001\u5206\u6790\u306e\u305f\u3081\u306bPandas\u306e\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306b\u30c7\u30fc\u30bf\u3092\u623b\u3057\u307e\u3059\u3002\u3053\u308c\u306b\u306f<code>pd.DataFrame()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u3063\u3066\u3001GridDB\u30b3\u30f3\u30c6\u30ca\u306e\u30ea\u30b9\u30c8\u3092\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306b\u5909\u63db\u3057\u307e\u3059\u3002<\/p>\n<p>\u3053\u308c\u3067\u3001GridDB\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u304b\u3089\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u3092\u53d6\u5f97\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\u3002<\/p>\n<h2>GridDB\u3067\u89e3\u6790\u3059\u308b<\/h2>\n<p>\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u304cGridDB\u30b3\u30f3\u30c6\u30ca\u306b\u8aad\u307f\u8fbc\u307e\u308c\u305f\u3068\u3053\u308d\u3067\u3001\u3044\u3088\u3044\u3088\u5206\u6790\u306b\u5165\u308a\u307e\u3059\u3002\u307e\u305a\u3001\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u307e\u3059\u3002<code>numpy<\/code>\u3001 <code>matplotlib<\/code>\u3001 <code>pandas<\/code> \u306e3\u3064\u3067\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">\nimport numpy as np\nimport GridDB_python as GridDB\nimport sys\nimport pandas as pd\nimport matplotlib.pyplot as plt\n<\/code><\/pre>\n<\/div>\n<p>\u3053\u3053\u3067\u306f\u3001\u30ce\u30fc\u30d9\u30eb\u8cde\u53d7\u8cde\u8005\u306e\u6027\u5225\u6b04\u3092\u898b\u3066\u3001\u6027\u5225\u3068\u30ce\u30fc\u30d9\u30eb\u8cde\u306e\u6bd4\u7387\u3092\u68d2\u30b0\u30e9\u30d5\u306b\u3057\u3066\u8003\u3048\u3066\u307f\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">\n# Analysis on Gender\ngender_wise = nobelprize_dataframe['sex'].value_counts()\n \ngenderplot = gender_wise.plot(kind='bar')\ngenderplot.figure.tight_layout()\ngenderplot.figure.savefig('gender_wise.png')\n<\/code><\/pre>\n<\/div>\n<p><a href=\"https:\/\/griddb.net\/wp-content\/uploads\/2021\/05\/analysis_1.png\"><img fetchpriority=\"high\" decoding=\"async\" src=\"https:\/\/griddb.net\/wp-content\/uploads\/2021\/05\/analysis_1.png\" alt=\"\" width=\"468\" height=\"314\" class=\"aligncenter size-full wp-image-27489\" srcset=\"\/wp-content\/uploads\/2021\/05\/analysis_1.png 468w, \/wp-content\/uploads\/2021\/05\/analysis_1-300x201.png 300w\" sizes=\"(max-width: 468px) 100vw, 468px\" \/><\/a><\/p>\n<p>\u898b\u3066\u5206\u304b\u308b\u3088\u3046\u306b\u3001\u30ce\u30fc\u30d9\u30eb\u8cde\u53d7\u8cde\u8005\u306f\u5727\u5012\u7684\u306b\u7537\u6027\u304c\u591a\u6570\u3067\u3059\u3002\u6570\u3042\u308b\u7406\u7531\u306e\u3046\u3061\u306e\uff11\u3064\u3068\u3057\u3066\u300120\u4e16\u7d00\u524d\u534a\u306b\u5973\u6027\u306e\u5730\u4f4d\u5411\u4e0a\u304c\u9032\u3093\u3067\u3044\u306a\u304b\u3063\u305f\u3053\u3068\u304c\u6319\u3052\u3089\u308c\u307e\u3059\u3002\u307e\u305f\u3001\u5973\u6027\u306b\u6bd4\u3079\u3066\u7537\u6027\u306e\u624d\u80fd\u306e\u65b9\u304c\u8a8d\u3081\u3089\u308c\u3084\u3059\u3044\u3068\u3044\u3046\u504f\u308a\u304c\u3042\u3063\u305f\u3068\u3044\u3046\u3053\u3068\u3082\u3042\u308b\u3067\u3057\u3087\u3046\u30022018\u5e74\u306b\u30ce\u30fc\u30d9\u30eb\u7269\u7406\u5b66\u8cde\u3092\u53d7\u8cde\u3057\u305f\u30c9\u30ca\u30fb\u30b9\u30c8\u30ea\u30c3\u30af\u30e9\u30f3\u30c9\u306f\u3001\u308f\u305a\u304b3\u4eba\u76ee\u306e\u5973\u6027\u53d7\u8cde\u8005\u3067\u3059\u3002<\/p>\n<p>\u5f93\u6765\u306e\u30b9\u30c6\u30ec\u30aa\u30bf\u30a4\u30d7\u3067\u306f\u3001\u5973\u6027\u306f\u300c\u6570\u5b66\u304c\u5acc\u3044\u300d\u300c\u79d1\u5b66\u304c\u82e6\u624b\u300d\u3068\u3044\u3046\u7406\u7531\u3067STEM\u5206\u91ce\u3092\u907f\u3051\u3088\u3046\u3068\u3057\u304c\u3061\u3067\u3059\u3002\u3053\u308c\u306f\u73fe\u5728\u3082\u7d9a\u3044\u3066\u3044\u308b\u554f\u984c\u3067\u3059\u304c\u3001\u3053\u3053\u6570\u5341\u5e74\u3001\u3053\u306e\u898b\u65b9\u3092\u514b\u670d\u3059\u308b\u305f\u3081\u306b\u591a\u304f\u306e\u52aa\u529b\u304c\u306a\u3055\u308c\u3066\u3044\u307e\u3059\u3002<\/p>\n<p>\u5206\u91ce\u5225\u306b\u898b\u3066\u307f\u308b\u3068\u3001\u79d1\u5b66\u5206\u91ce\u3067\u306e\u53d7\u8cde\u304c\u591a\u304f\u3001\u4e2d\u3067\u3082\u533b\u5b66\u3068\u7269\u7406\u5b66\u306e\u53d7\u8cde\u304c\u591a\u3044\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002\u3053\u308c\u306f\u300120\u4e16\u7d00\u306b\u975e\u79d1\u5b66\u7684\u306a\u5206\u91ce\u304c\u3042\u307e\u308a\u8a55\u4fa1\u3055\u308c\u306a\u304b\u3063\u305f\u3053\u3068\u3084\u3001\u3042\u308b\u5206\u91ce\u306e\u30ce\u30fc\u30d9\u30eb\u8cde\u304c\u5b58\u5728\u3057\u306a\u304b\u3063\u305f\u308a\u3001\u5f8c\u304b\u3089\u8ffd\u52a0\u3055\u308c\u305f\u308a\u3057\u305f\u3053\u3068\u306b\u3088\u308b\u3068\u601d\u308f\u308c\u307e\u3059\u3002\u7279\u306b\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u306f\u3001\u73fe\u5728\u306e\u3068\u3053\u308d\u30ce\u30fc\u30d9\u30eb\u8cde\u306e\u5bfe\u8c61\u3068\u306a\u3063\u3066\u304a\u3089\u305a\u3001\u4ee3\u308f\u308a\u306b\u30c1\u30e5\u30fc\u30ea\u30f3\u30b0\u8cde\u3068\u3044\u3046\u5225\u306e\u8cde\u304c\u8a2d\u3051\u3089\u308c\u3066\u3044\u307e\u3059\u3002\u5206\u6790\u306e\u76ee\u7684\u304c\u5206\u91ce\u306e\u8a8d\u77e5\u5ea6\u3068\u4eba\u6c17\u3092\u6bd4\u8f03\u3059\u308b\u3053\u3068\u3067\u3042\u308b\u306a\u3089\u3070\u3001\u30c1\u30e5\u30fc\u30ea\u30f3\u30b0\u8cde\u3092\u542b\u3081\u308b\u3053\u3068\u3067\u3001\u5225\u306e\u610f\u5473\u306e\u3042\u308b\u6d1e\u5bdf\u3092\u5f97\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u3067\u3057\u3087\u3046\uff08\u672c\u30d6\u30ed\u30b0\u3067\u306f\u53d6\u308a\u4e0a\u3052\u3066\u3044\u307e\u305b\u3093\uff09\u3002<\/p>\n<p>\u3055\u3089\u306b\u3001\u5148\u307b\u3069\u306e2\u3064\u306e\u5206\u91ce\u3092\u4f7f\u3063\u3066\u30c7\u30fc\u30bf\u3092\u5206\u6790\u3057\u30011\u3064\u306e\u30b0\u30e9\u30d5\u306b\u3057\u307e\u3057\u305f\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">\n# Analysis on Category\ncategory_wise = nobelprize_dataframe['category'].value_counts()\n \nnobelprize_dataframe.groupby(['category','sex']).size().unstack().plot(kind='bar',stacked=True)\nplt.tight_layout()\nplt.savefig('Category+Gender.png', orientation = 'landscape')\nplt.show()\n<\/code><\/pre>\n<\/div>\n<p><a href=\"https:\/\/griddb.net\/wp-content\/uploads\/2021\/05\/analysis_2.png\"><img decoding=\"async\" src=\"https:\/\/griddb.net\/wp-content\/uploads\/2021\/05\/analysis_2.png\" alt=\"\" width=\"436\" height=\"290\" class=\"aligncenter size-full wp-image-27488\" srcset=\"\/wp-content\/uploads\/2021\/05\/analysis_2.png 436w, \/wp-content\/uploads\/2021\/05\/analysis_2-300x200.png 300w\" sizes=\"(max-width: 436px) 100vw, 436px\" \/><\/a><\/p>\n<p>\u5973\u6027\u306e\u30ce\u30fc\u30d9\u30eb\u8cde\u53d7\u8cde\u8005\u304c\u6700\u3082\u591a\u3044\u306e\u306f\u5e73\u548c\u8cde\u3067\u3042\u308b\u306e\u306b\u5bfe\u3057\u3001STEM\u5206\u91ce\u3067\u5973\u6027\u306e\u6d3b\u8e8d\u304c\u76ee\u7acb\u3064\u306e\u306f\u533b\u5b66\u8cde\u3060\u3051\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/p>\n<p>\u307e\u305f\u3001\u5404\u5206\u91ce\u306b\u4e0e\u3048\u3089\u308c\u305f\u8cde\u3092\u7570\u306a\u308b\u671f\u9593\u306b\u6e21\u3063\u3066\u5206\u6790\u3057\u3001\u305d\u308c\u304c\u3069\u306e\u3088\u3046\u306b\u5909\u5316\u3057\u3066\u304d\u305f\u304b\u3092\u77e5\u308b\u3053\u3068\u3067\u3001\u4f55\u3089\u304b\u306e\u30d2\u30f3\u30c8\u304c\u5f97\u3089\u308c\u308b\u3067\u3057\u3087\u3046\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">\n# Time series analysis on Year Group\nnobelprize_dataframe[\"Year_Group\"] = pd.cut(nobelprize_dataframe[\"year\"],[1900,1910,1920,1930,1940,1950,1960,1970,1980,1990,2000,2010,2016], precision=0, labels=['1900-1910','1910-1920','1920-1930','1930-1940','1940-1950','1950-1960','1960-1970','1970-1980','1980-1990','1990-2000','2000-2010','2010-2016'])   \n \nnobelprize_dataframe.groupby(['Year_Group','category']).size().unstack().plot(kind='bar',stacked=True)\nplt.tight_layout()\nplt.savefig('Change_over_years.png')\nplt.show()\n<\/code><\/pre>\n<\/div>\n<p><a href=\"https:\/\/griddb.net\/wp-content\/uploads\/2021\/05\/analysis_3.png\"><img decoding=\"async\" src=\"https:\/\/griddb.net\/wp-content\/uploads\/2021\/05\/analysis_3.png\" alt=\"\" width=\"468\" height=\"312\" class=\"aligncenter size-full wp-image-27490\" srcset=\"\/wp-content\/uploads\/2021\/05\/analysis_3.png 468w, \/wp-content\/uploads\/2021\/05\/analysis_3-300x200.png 300w\" sizes=\"(max-width: 468px) 100vw, 468px\" \/><\/a><\/p>\n<p>\u4e0b\u306e\u30b0\u30e9\u30d5\u3092\u898b\u308b\u3068\u3001\u904e\u53bb120\u5e74\u9593\u3067\u5168\u4f53\u306e\u6bd4\u7387\u304c\u5909\u308f\u3089\u306a\u3044\u5206\u91ce\u304c\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002\u4f8b\u3048\u3070\u3001\u5e73\u548c\u8cde\u3068\u6587\u5b66\u8cde\u3067\u3059\u3002\u4e00\u65b9\u3001\u533b\u5b66\u8cde\u3084\u7269\u7406\u5b66\u8cde\u306a\u3069\u306eSTEM\u5206\u91ce\u3067\u306f\u3001\u30ce\u30fc\u30d9\u30eb\u8cde\u306e\u53d7\u8cde\u6570\u304c\u5e74\u3005\u5897\u52a0\u3057\u3066\u3044\u308b\u3053\u3068\u304c\u660e\u3089\u304b\u306b\u306a\u3063\u3066\u3044\u307e\u3059\u3002\u30b0\u30e9\u30d5\u304b\u3089\u5f97\u3089\u308c\u308b\u6700\u3082\u91cd\u8981\u306a\u6d1e\u5bdf\u3068\u3057\u3066\u3001\u7d4c\u6e08\u5b66\u8cde\u306f1900\u5e74\u4ee3\u521d\u982d\u306b\u306f\u76ee\u7acb\u305f\u306a\u304b\u3063\u305f\u3082\u306e\u306e\u30011970\u5e74\u4ee5\u964d\u306b\u7d4c\u6e08\u5b66\u8cde\u53d7\u8cde\u8005\u6570\u304c\u5927\u5e45\u306b\u5897\u52a0\u3057\u3066\u3044\u308b\u3053\u3068\u304c\u5206\u304b\u308a\u307e\u3059\u3002<\/p>\n<p>\u3053\u306e\u3088\u3046\u306b\u3001GridDB\u3068Python\u3092\u4f7f\u3063\u3066\u3001\u30c7\u30fc\u30bf\u306e\u8aad\u307f\u8fbc\u307f\u3001\u633f\u5165\u3001\u53d6\u308a\u51fa\u3057\u3001\u5206\u6790\u3092\u884c\u3046\u65b9\u6cd5\u306b\u3064\u3044\u3066\u7d39\u4ecb\u3057\u307e\u3057\u305f\u3002<\/p>\n<h2>\u307e\u3068\u3081<\/h2>\n<p>\u3053\u306e\u30d6\u30ed\u30b0\u3067\u306f\u3001GridDB\u3092\u4f7f\u3044\u59cb\u3081\u308b\u305f\u3081\u306e\u7c21\u5358\u306a\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u6210\u3057\u3001CSV\u30d5\u30a1\u30a4\u30eb\u306e\u524d\u51e6\u7406\u3068\u8aad\u307f\u8fbc\u307f\u3001GridDB\u30b3\u30f3\u30c6\u30ca\u304b\u3089\u306e\u30c7\u30fc\u30bf\u306e\u633f\u5165\u3068\u53d6\u5f97\u3001matplotlib\u3001pandas\u3001numpy\u3092\u4f7f\u3063\u305f\u30c7\u30fc\u30bf\u5206\u6790\u306e\u65b9\u6cd5\u3092\u7d39\u4ecb\u3057\u307e\u3057\u305f\u3002\u307e\u305f\u3001GridDB\u304b\u3089\u306e\u30c7\u30fc\u30bf\u306e\u554f\u3044\u5408\u308f\u305b\u3084\u3001\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u3078\u306e\u30a4\u30f3\u30dd\u30fc\u30c8\u306e\u57fa\u672c\u306b\u3064\u3044\u3066\u3082\u8aac\u660e\u3057\u307e\u3057\u305f\u3002\u3053\u308c\u306fGridDB\u3067\u3067\u304d\u308b\u6a5f\u80fd\u306e\u307b\u3093\u306e\u4e00\u90e8\u306b\u904e\u304e\u307e\u305b\u3093\u3002TQL\u30d5\u30a3\u30eb\u30bf\u3084GridDB\u30b3\u30f3\u30c6\u30ca\u3092\u81ea\u7531\u306b\u4f7f\u3063\u3066\u3001\u3088\u308a\u5145\u5b9f\u3057\u305f\u5b66\u7fd2\u4f53\u9a13\u3092\u3057\u3066\u307f\u3066\u304f\u3060\u3055\u3044\u3002Happy coding!<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u306f\u3058\u3081\u306b \u30ce\u30fc\u30d9\u30eb\u8cde\u306f\u3001\u304a\u305d\u3089\u304f\u4e16\u754c\u3067\u6700\u3082\u3088\u304f\u77e5\u3089\u308c\u305f\u540d\u8a89\u3042\u308b\u8cde\u3067\u3059\u3002\u4e16\u754c\u4e2d\u306e\u5c02\u9580\u5bb6\u3084\u6d3b\u52d5\u5bb6\u304c\u3001\u30ce\u30fc\u30d9\u30eb\u8cde\u53d7\u8cde\u8005\u306b\u306a\u308a\u305d\u308c\u305e\u308c\u306e\u5206\u91ce\u3067\u305d\u306e\u5a01\u5149\u3092\u5206\u304b\u3061\u5408\u3046\u3053\u3068\u3092\u5922\u898b\u3066\u3044\u307e\u3059\u3002\u30d3\u30b8\u30cd\u30b9\u30ea\u30fc\u30c0\u30fc\u3084\u30c7\u30fc\u30bf\u30a2\u30ca\u30ea\u30b9\u30c8\u305f\u3061\u306b\u3068\u3063\u3066 [&hellip;]<\/p>\n","protected":false},"author":41,"featured_media":49241,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1005],"tags":[],"class_list":["post-50743","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-1005"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.1.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>\u30ce\u30fc\u30d9\u30eb\u8cde\u53d7\u8cde\u8005\u306e\u50be\u5411\u3092\u30b0\u30e9\u30d5\u3067\u5206\u6790\u3059\u308b | GridDB: Open Source Time Series Database for IoT<\/title>\n<meta name=\"description\" content=\"\u306f\u3058\u3081\u306b\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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