{"id":50817,"date":"2022-09-02T00:00:00","date_gmt":"2022-09-02T07:00:00","guid":{"rendered":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/%e6%9c%aa%e5%88%86%e9%a1%9e\/using-griddb-to-analyze-gdp-of-different-countries\/"},"modified":"2025-11-14T07:55:38","modified_gmt":"2025-11-14T15:55:38","slug":"using-griddb-to-analyze-gdp-of-different-countries","status":"publish","type":"post","link":"https:\/\/griddb.net\/ja\/%e6%9c%aa%e5%88%86%e9%a1%9e\/using-griddb-to-analyze-gdp-of-different-countries\/","title":{"rendered":"GridDB\u3092\u4f7f\u3063\u305f\u5404\u56fd\u306eGDP\u5206\u6790"},"content":{"rendered":"<p><a href=\"https:\/\/www.worldometers.info\/gdp\/what-is-gdp\/\">GDP<\/a>\u3068\u306f\u3001\u300c\u56fd\u5185\u7dcf\u751f\u7523\u300d\u306e\u7565\u3067\u3001\u3042\u308b\u671f\u9593\uff08\u901a\u5e381\u5e74\u9593\uff09\u306b\u56fd\u5185\u3067\u751f\u7523\u3055\u308c\u305f\uff08\u5e02\u5834\u3067\u8ca9\u58f2\u3055\u308c\u305f\uff09\u3059\u3079\u3066\u306e\u6700\u7d42\u8ca1\u3068\u30b5\u30fc\u30d3\u30b9\u306e\u8ca8\u5e63\u4fa1\u5024\u306e\u5408\u8a08\u3067\u3059\u3002\u4e00\u56fd\u306e\u7d4c\u6e08\u6210\u9577\u3092\u8868\u3059\u6307\u6a19\u3068\u3057\u3066\u7528\u3044\u3089\u308c\u307e\u3059\u3002<\/p>\n<p>GridDB\u3092\u5229\u7528\u3057\u3066\u3001\u5404\u56fd\u306e\u7d4c\u6e08\u72b6\u6cc1\u3092\u5206\u6790\u3059\u308b\u4e88\u5b9a\u3067\u3059\u3002GridDB\u306f\u3001\u9ad8\u3044\u30b9\u30b1\u30fc\u30e9\u30d3\u30ea\u30c6\u30a3\u3068\u6700\u9069\u5316\u3092\u5b9f\u73fe\u3057\u305f\u30a4\u30f3\u30e1\u30e2\u30eaNoSQL\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u3067\u3001\u7279\u306b\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306b\u304a\u3044\u3066\u3001\u3088\u308a\u9ad8\u3044\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u3068\u52b9\u7387\u6027\u3092\u5b9f\u73fe\u3059\u308b\u305f\u3081\u306b\u4e26\u5217\u51e6\u7406\u3092\u53ef\u80fd\u306b\u3057\u307e\u3059\u3002\u4eca\u56de\u306fGridDB\u306eNode.js\u30af\u30e9\u30a4\u30a2\u30f3\u30c8\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002GridDB\u3068Node.js\u3092\u63a5\u7d9a\u3057\u3001\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u306b\u30c7\u30fc\u30bf\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u307e\u305f\u306f\u30a8\u30af\u30b9\u30dd\u30fc\u30c8\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u3055\u3089\u306b\u3001Danfo.js\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u4f7f\u7528\u3057\u3066\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u3092\u64cd\u4f5c\u3057\u3001\u30c7\u30fc\u30bf\u89e3\u6790\u3092\u884c\u3044\u307e\u3059\u3002<\/p>\n<p>csv\u5f62\u5f0f\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306f<a href=\"https:\/\/www.kaggle.com\/datasets\/alejopaullier\/-gdp-by-country-1999-2022\">Kaggle<\/a>\u304b\u3089\u5165\u624b\u3057\u305f\u3082\u306e\u3067\u3059\u3002\u3053\u306e\u30c7\u30fc\u30bf\u304c\u4f55\u3092\u8868\u3057\u3066\u3044\u308b\u304b\u306f\u3001\u5f8c\u307b\u3069\u300c\u30c7\u30fc\u30bf\u5206\u6790\u300d\u306e\u9805\u3067\u7d39\u4ecb\u3057\u307e\u3059\u3002<\/p>\n<p><a href=\"https:\/\/github.com\/griddbnet\/Blogs\/tree\/analyzing-gdp-countries\">\u30bd\u30fc\u30b9\u30b3\u30fc\u30c9\u3068\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u5168\u5bb9\u306f\u3053\u3061\u3089<\/a><\/p>\n<h2>GridDB\u3078\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u66f8\u304d\u51fa\u3057<\/h2>\n<p>\u306f\u3058\u3081\u306b\u3001GridDB \u30ce\u30fc\u30c9\u30e2\u30b8\u30e5\u30fc\u30eb griddb node\u3001danfojs-node\u3001csv-parser \u3092\u521d\u671f\u5316\u3057\u307e\u3059\u3002 Griddb-node\u306fGridDB\u4e0a\u3067\u4f5c\u696d\u3067\u304d\u308b\u3088\u3046\u306b\u30ce\u30fc\u30c9\u3092\u8d77\u52d5\u3057\u3001Danfojs-node\u306f\u30c7\u30fc\u30bf\u89e3\u6790\u3067\u4f7f\u7528\u3059\u308bdf\u3068\u3044\u3046\u5909\u6570\u3068\u3057\u3066\u521d\u671f\u5316\u3057\u3001csv-parser\u306f\u4ee5\u4e0b\u306e\u3088\u3046\u306bcsv\u30d5\u30a1\u30a4\u30eb\u3092\u8aad\u307f\u8fbc\u3093\u3067GridDB\u306b\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u30a2\u30c3\u30d7\u30ed\u30fc\u30c9\u3057\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-javascript\">var griddb = require('griddb_node');\n\nconst dfd = require(\"danfojs-node\")\nconst csv = require('csv-parser');\nconst fs = require('fs');\nfs.createReadStream('.\/Dataset\/GDP by Country 1999-2022.csv')\n  .pipe(csv())\n  .on('data', (row) => {\n    lst.push(row);\n    console.log(lst);\n  })<\/code><\/pre>\n<\/div>\n<p>\u5909\u6570\u306e\u521d\u671f\u5316\u306b\u7d9a\u3044\u3066\u3001GridDB \u30b3\u30f3\u30c6\u30ca\u3092\u751f\u6210\u3057\u3001\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u30b9\u30ad\u30fc\u30de\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002\u30b3\u30f3\u30c6\u30ca\u5185\u3067\u306f\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u5185\u306e\u30ab\u30e9\u30e0\u306e\u30c7\u30fc\u30bf\u578b\u3092\u5b9a\u7fa9\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u3053\u306e\u30b3\u30f3\u30c6\u30ca\u3092\u5229\u7528\u3057\u3066\u3001\u683c\u7d0d\u3055\u308c\u3066\u3044\u308b\u30c7\u30fc\u30bf\u306b\u30a2\u30af\u30bb\u30b9\u3057\u3001GridDB \u3078\u306e\u30c7\u30fc\u30bf\u633f\u5165\u3092\u5b8c\u4e86\u3057\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-javascript\">const conInfo = new griddb.ContainerInfo({\n    'name': \"gdpanalysis\",\n    'columnInfoList': [\n      [\"name\", griddb.Type.STRING],\n      [\"Country\", griddb.Type.STRING],\n        [\"1999\", griddb.Type.DOUBLE],\n        [\"2000\", griddb.Type.DOUBLE],\n        [\"2001\", griddb.Type.DOUBLE],\n        [\"2002\", griddb.Type.DOUBLE],\n        [\"2003\", griddb.Type.DOUBLE],\n        [\"2004\", griddb.Type.DOUBLE],\n        [\"2005\", griddb.Type.DOUBLE],\n        [\"2006\", griddb.Type.DOUBLE],\n        [\"2007\", griddb.Type.DOUBLE],\n        [\"2008\", griddb.Type.DOUBLE],\n        [\"2009\", griddb.Type.DOUBLE],\n        [\"2010\", griddb.Type.DOUBLE],\n        [\"2011\", griddb.Type.DOUBLE],\n        [\"2012\", griddb.Type.DOUBLE],\n        [\"2013\", griddb.Type.DOUBLE],\n        [\"2014\", griddb.Type.DOUBLE],\n        [\"2015\", griddb.Type.DOUBLE],\n        [\"2016\", griddb.Type.DOUBLE],\n        [\"2017\", griddb.Type.DOUBLE],\n        [\"2018\", griddb.Type.DOUBLE],\n        [\"2019\", griddb.Type.DOUBLE],\n        [\"2020\", griddb.Type.DOUBLE],\n        [\"2021\", griddb.Type.DOUBLE]\n    ],\n    'type': griddb.ContainerType.COLLECTION, 'rowKey': true\n});\n\n\/\/\/ Inserting Data into GridDB\n\n    for(let i=0;i&lt;lst.length;i++){\n\n    store.putContainer(conInfo, false)\n        .then(cont => {\n            container = cont;\n            return container.createIndex({ 'columnName': 'name', 'indexType': griddb.IndexType.DEFAULT });\n        })\n        .then(() => {\n            idx++;\n            container.setAutoCommit(false);\n            return container.put([String(idx), lst[i]['Country'],lst[i][\"1999\"],lst[i][\"2000\"],lst[i][\"2001\"],lst[i][\"2002\"],lst[i][\"2003\"],lst[i][\"2004\"],lst[i][\"2005\"],lst[i][\"2006\"],lst[i][\"2007\"],lst[i][\"2008\"],lst[i][\"2009\"],lst[i][\"2010\"],lst[i][\"2011\"],lst[i][\"2012\"],lst[i][\"2013\"],lst[i][\"2014\"],lst[i][\"2015\"],lst[i][\"2016\"],lst[i][\"2017\"],lst[i][\"2018\"],lst[i][\"2019\"],lst[i][\"2020\"],lst[i][\"2021\"]]);\n        })\n        .then(() => {\n            return container.commit();\n        })      \n        .catch(err => {\n            if (err.constructor.name == \"GSException\") {\n                for (var i = 0; i &lt; err.getErrorStackSize(); i++) {\n                    console.log(\"[\", i, \"]\");\n                    console.log(err.getErrorCode(i));\n                    console.log(err.getMessage(i));\n                }\n            } else {\n                console.log(err);\n            }\n        });    \n    }<\/code><\/pre>\n<\/div>\n<h2>GridDB\u304b\u3089\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b<\/h2>\n<p>\u3059\u3067\u306b\u30b3\u30f3\u30c6\u30ca\u5185\u306b\u3059\u3079\u3066\u306e\u30c7\u30fc\u30bf\u3092\u4fdd\u5b58\u3057\u3066\u3044\u308b\u306e\u3067\u3001\u3042\u3068\u306fGridDB\u306eSQL\u30e9\u30a4\u30af\u306a\u554f\u3044\u5408\u308f\u305b\u8a00\u8a9e\u3067\u3042\u308bTQL\u3092\u4f7f\u3063\u3066\u30c7\u30fc\u30bf\u3092\u53d6\u5f97\u3059\u308b\u3060\u3051\u3067\u3059\u3002\u305d\u3053\u3067\u3001\u307e\u305a\u3001getached_data\u3068\u3044\u3046\u540d\u524d\u3067\u3001\u53d6\u5f97\u3057\u305f\u30c7\u30fc\u30bf\u3092\u683c\u7d0d\u3059\u308b\u30b3\u30f3\u30c6\u30ca\u3092\u69cb\u7bc9\u3057\u307e\u3059\u3002\u6b21\u306b\u3001query \u3068\u3044\u3046\u30ab\u30e9\u30e0\u30aa\u30fc\u30c0\u30fc\u3067\u884c\u3092\u62bd\u51fa\u3057\u3001df \u3068\u3044\u3046\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306b\u4fdd\u5b58\u3057\u3066\u3001\u30c7\u30fc\u30bf\u306e\u53ef\u8996\u5316\u3084\u5206\u6790\u3092\u884c\u3044\u3001\u30c7\u30fc\u30bf\u306e\u30a4\u30f3\u30dd\u30fc\u30c8\u3092\u5b8c\u4e86\u3057\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-javascript\"># Get the containers\nobtained_data = gridstore.get_container(\"gdpanalysis\")\n    \n# Fetch all rows - language_tag_container\nquery = obtained_data.query(\"select *\")\n\n# Creating Data Frame variable\nlet df = await dfd.readCSV(\".\/out.csv\")<\/code><\/pre>\n<\/div>\n<h2>\u30c7\u30fc\u30bf\u5206\u6790<\/h2>\n<p>\u30c7\u30fc\u30bf\u5206\u6790\u3092\u59cb\u3081\u308b\u306b\u3042\u305f\u308a\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u5217\u3068\u305d\u308c\u3089\u304c\u8868\u3059\u3082\u306e\u3001\u305d\u3057\u3066\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u884c\u3068\u5217\u306e\u7dcf\u6570\u3092\u8abf\u3079\u307e\u3059\u3002<\/p>\n<ul>\n<li>Country : \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u542b\u307e\u308c\u308b\u56fd\u306e\u540d\u524d\u3002<\/li>\n<li>1999 : 1990\u5e74\u306b\u304a\u3051\u308b\u7279\u5b9a\u56fd\u306eGDP\u3002<\/li>\n<li>\n<p>2000 : 2000\u5e74\u306b\u304a\u3051\u308b\u7279\u5b9a\u56fd\u306eGDP\u3002<\/p>\n<p>.<\/p>\n<p>.<\/p>\n<p>.<\/p>\n<\/li>\n<li>\n<p>2021 : 2021\u5e74\u306b\u304a\u3051\u308b\u7279\u5b9a\u56fd\u306eGDP\u3002<\/p>\n<\/li>\n<\/ul>\n<div class=\"clipboard\">\n<pre><code class=\"language-javascript\">console.log(df.shape)\n\n\/\/  Output\n\/\/ [ 180, 24 ]<\/code><\/pre>\n<\/div>\n<p>180\u884c24\u5217\u306a\u306e\u3067\u30011999\u5e74\u304b\u30892021\u5e74\u307e\u3067\u306e180\u7a2e\u985e\u306e\u56fd\u306eGDP\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n<p>\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306bNULL\u5024\u304c\u3042\u308b\u304b\u3069\u3046\u304b\u3092\u78ba\u8a8d\u3057\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-javascript\">for (let column_name in p1_df.columns){\n    column = p1_df[column_name];\n    # Get the count of Zeros in column \n    count = (column == '0').sum();\n    console.log('Count of zeros in column ', column_name, ' is : ', count)\n}\n\/\/ Output \n\/\/ Count of zeroes in column  Country  is :  0\n\/\/ Count of zeroes in column  1999  is :  2\n\/\/ Count of zeroes in column  2000  is :  1\n\/\/ Count of zeroes in column  2001  is :  1\n\/\/ Count of zeroes in column  2002  is :  0\n\/\/ Count of zeroes in column  2003  is :  0\n\/\/ Count of zeroes in column  2004  is :  0\n\/\/ Count of zeroes in column  2005  is :  0\n\/\/ Count of zeroes in column  2006  is :  0\n\/\/ Count of zeroes in column  2007  is :  0\n\/\/ Count of zeroes in column  2008  is :  0\n\/\/ Count of zeroes in column  2009  is :  1\n\/\/ Count of zeroes in column  2010  is :  1\n\/\/ Count of zeroes in column  2011  is :  1\n\/\/ Count of zeroes in column  2012  is :  1\n\/\/ Count of zeroes in column  2013  is :  1\n\/\/ Count of zeroes in column  2014  is :  13\n\/\/ Count of zeroes in column  2015  is :  14\n\/\/ Count of zeroes in column  2016  is :  14\n\/\/ Count of zeroes in column  2017  is :  14\n\/\/ Count of zeroes in column  2018  is :  14\n\/\/ Count of zeroes in column  2019  is :  14\n\/\/ Count of zeroes in column  2020  is :  15\n\/\/ Count of zeroes in column  2021  is :  16<\/code><\/pre>\n<\/div>\n<p>GDP\u306e\u5024\u306f\u3059\u3079\u3066object\u30c7\u30fc\u30bf\u578b\u306a\u306e\u3067\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u30c7\u30fc\u30bf\u578b\u3092float\u306b\u5909\u66f4\u3057\u3001GDP\u304c\u30bc\u30ed\u306b\u306a\u308b\u3053\u3068\u306f\u306a\u3044\u306e\u3067\u3001\u30bc\u30ed\u306e\u5024\u3092\u5404\u56fd\u306eGDP\u4e2d\u592e\u5024\u306b\u7f6e\u304d\u63db\u3048\u308b\u3053\u3068\u306b\u3057\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-javascript\">for (let column_name in p1_df.columns){\n\n  if(column_name == 'Country'){\n  \n  continue;\n}\nelse{\n\n  df = df.asType(column_name, \"float64\")\n}\n\nfor (let column_name in p1_df.columns){\n\n  df[column_name]=df[column_name].replace(0, df[column_name].median())\n\n}<\/code><\/pre>\n<\/div>\n<p>\u3053\u308c\u3067\u30c7\u30fc\u30bf\u304c\u7dba\u9e97\u306b\u306a\u3063\u305f\u306e\u3067\u3001\u5206\u6790\u3092\u9032\u3081\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n<p>\u307e\u305a\u3001\u4e16\u754c\u306eGDP\u306e\u63a8\u79fb\u3092\u898b\u308b\u305f\u3081\u306b\u3001\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u5168180\u30ab\u56fd\u306eGDP\u30921\u3064\u306b\u307e\u3068\u3081\u3066\u7b97\u51fa\u3057\u305f\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u3092\u30d7\u30ed\u30c3\u30c8\u3057\u307e\u3059\u3002<\/p>\n<p><a href=\"https:\/\/griddb.net\/wp-content\/uploads\/2022\/08\/LineChart.png\"><img fetchpriority=\"high\" decoding=\"async\" src=\"https:\/\/griddb.net\/wp-content\/uploads\/2022\/08\/LineChart.png\" alt=\"\" width=\"465\" height=\"306\" class=\"aligncenter size-full wp-image-28713\" srcset=\"\/wp-content\/uploads\/2022\/08\/LineChart.png 465w, \/wp-content\/uploads\/2022\/08\/LineChart-300x197.png 300w\" sizes=\"(max-width: 465px) 100vw, 465px\" \/><\/a><\/p>\n<p>\u6b21\u306b\u30011999\u5e74\u304b\u30892021\u5e74\u307e\u3067\u306e\u5404\u56fd\u306e\u9032\u6357\u3092\u3001\u30b5\u30de\u30ea\u30fc\u7d71\u8a08\u3067\u6bd4\u8f03\u3057\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-javascript\">df.loc({columns:['2016', '2017', '2018', '2019', '2020', '2021']}).describe().round(2).print()\n\n\n\n\/\/ Output\n\/\/ \u2554\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2557\n\/\/ \u2551            \u2502 2016              \u2502 2017              \u2502 2018              \u2502 2019              \u2502 2020              \u2502 2021              \u2551\n\/\/ \u255f\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2562\n\/\/ \u2551 count      \u2502 180               \u2502 180               \u2502 180               \u2502 180               \u2502 180               \u2502 180               \u2551\n\/\/ \u255f\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2562\n\/\/ \u2551 mean       \u2502 111.26            \u2502 112.58            \u2502 119.30            \u2502 126.77            \u2502 119.70            \u2502 127.74            \u2551\n\/\/ \u255f\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2562\n\/\/ \u2551 std        \u2502 179.68            \u2502 176.69            \u2502 186.00            \u2502 196.63            \u2502 186.40            \u2502 199.65            \u2551\n\/\/ \u255f\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2562\n\/\/ \u2551 min        \u2502 0.16              \u2502 0.17              \u2502 0.17              \u2502 0.18              \u2502 0.23              \u2502 0.25              \u2551\n\/\/ \u255f\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2562\n\/\/ \u2551 median     \u2502 2657.38           \u2502 2868.33           \u2502 2978.95           \u2502 3207.04           \u2502 2689.55           \u2502 2899.29           \u2551\n\/\/ \u255f\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2562\n\/\/ \u2551 max        \u2502 19555.87          \u2502 20493.25          \u2502 21404.19          \u2502 22294.11          \u2502 22939.58          \u2502 24796.08          \u2551\n\/\/ \u255f\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2562\n\/\/ \u2551 variance   \u2502 32286.52          \u2502 31220.07          \u2502 34596.34          \u2502 38661.75          \u2502 34743.69          \u2502 39862.26          \u2551\n\/\/ \u255a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255d<\/code><\/pre>\n<\/div>\n<p>\u4e2d\u592e\u5024\u3068\u5206\u6563\u3092\u898b\u308b\u3068\u3001\u4e2d\u592e\u5024\u3067\u3055\u3048\u3082\u304b\u306a\u308a\u4f4e\u304f\u3001\u5206\u6563\u3082\u5927\u304d\u3044\u306e\u3067\u3001\u4e16\u754c\u306e\u307b\u3068\u3093\u3069\u306e\u56fd\u304c\u7d4c\u6e08\u7684\u306b\u82e6\u3057\u3093\u3067\u3044\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u3001\u7b2c\u4e00\u4e16\u754c\u306e\u56fd\u3068\u7b2c\u4e09\u4e16\u754c\u306e\u56fd\u306e\u9055\u3044\u3092\u6c7a\u5b9a\u3065\u3051\u307e\u3059\u3002 \u3053\u306e\u82e6\u3057\u307f\u306f\u30012018\u5e74\u304b\u30892020\u5e74\u306b\u304b\u3051\u3066\u306eCovid-19\u304c\u3001\u3042\u3089\u3086\u308b\u56fd\u306b\u5927\u6253\u6483\u3092\u4e0e\u3048\u3001\u7d4c\u6e08\u5168\u4f53\u3092\u6df7\u4e71\u3055\u305b\u305f\u305f\u3081\u306b\u767a\u751f\u3057\u307e\u3057\u305f\u3002\u3057\u304b\u3057\u3001Covid-19\u306e\u75c7\u4f8b\u304c\u6e1b\u3063\u3066\u304b\u3089\u306f\u3001\u4e0a\u306e\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u306e\u3088\u3046\u306b\u3001\u5404\u56fd\u304c\u56de\u5fa9\u306b\u5411\u304b\u3044\u307e\u3057\u305f\u3002\u4e00\u65b9\u3001\u3053\u308c\u3060\u3051\u82e6\u60a9\u3057\u3066\u3082\u30012016\u5e74\u304b\u30892021\u5e74\u307e\u3067\u306e\u904e\u53bb6\u5e74\u9593\u3067GDP\u304c\u6700\u5927\u306b\u306a\u3063\u305f\u56fd\u306f\u3069\u3053\u304b\u3001\u898b\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-javascript\">console.log(df.loc(df[df['2016'].max()]))\nconsole.log(df.loc(df[df['2017'].max()]))\nconsole.log(df.loc(df[df['2018'].max()]))\nconsole.log(df.loc(df[df['2019'].max()]))\nconsole.log(df.loc(df[df['2020'].max()]))\nconsole.log(df.loc(df[df['2021'].max()]))\n\n\/\/ Output\n\/\/ United States\n\/\/ United States\n\/\/ United States\n\/\/ United States\n\/\/ United States\n\/\/ United States<\/code><\/pre>\n<\/div>\n<p>\u7c73\u56fd\u304cGDP\u30c1\u30e3\u30fc\u30c8\u3067\u30c8\u30c3\u30d7\u306b\u306a\u3063\u305f\u306e\u306f\u5f53\u7136\u3067\u3059\u304c\u3001\u4e2d\u56fd\u3082\u9060\u304f\u53ca\u3073\u307e\u305b\u3093\u3002\u4e2d\u56fd\u3082\u7c73\u56fd\u3068\u7af6\u3046\u3088\u3046\u306b\u53f0\u982d\u3057\u3066\u304a\u308a\u3001\u305d\u306e\u5dee\u306f\u4e0b\u306e\u68d2\u30b0\u30e9\u30d5\u3067\u898b\u308b\u307b\u3069\u5927\u304d\u304f\u306f\u3042\u308a\u307e\u305b\u3093\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-javascript\">## Distribution of Column Values\nconst { Plotly } = require('node-kernel');\nlet cols = df.columns\nfor(let i = 0; i &lt; cols.length; i++)\n{\n    let data = [{\n        x: cols[i],\n        y: df[cols[i]].values,\n        type: 'bar'}];\n    let layout = {\n        height: 400,\n        width: 700,\n        title: 'GDP for United States of America and China (2016 - 2021)' +cols[i],\n        xaxis: {title: cols[i]}};\n    \/\/ There is no HTML element named `myDiv`, hence the plot is displayed below.\n    Plotly.newPlot('myDiv', data, layout);\n}\ndf.plot(\"plot_div\").bar()<\/code><\/pre>\n<\/div>\n<p><a href=\"https:\/\/griddb.net\/wp-content\/uploads\/2022\/08\/Barplot.png\"><img decoding=\"async\" src=\"https:\/\/griddb.net\/wp-content\/uploads\/2022\/08\/Barplot.png\" alt=\"\" width=\"481\" height=\"306\" class=\"aligncenter size-full wp-image-28715\" srcset=\"\/wp-content\/uploads\/2022\/08\/Barplot.png 481w, \/wp-content\/uploads\/2022\/08\/Barplot-300x191.png 300w\" sizes=\"(max-width: 481px) 100vw, 481px\" \/><\/a><\/p>\n<h2>\u7d50\u8ad6<\/h2>\n<p>2021\u5e74\u306bCovid-19\u306e\u898f\u5236\u304c\u6291\u3048\u3089\u308c\u3001Covid-19\u306e\u640d\u5931\u304b\u3089\u56de\u5fa9\u3057\u59cb\u3081\u305f\u56fd\u3082\u3042\u308a\u307e\u3057\u305f\u304c\u3001\u30ed\u30b7\u30a2\u306e\u30a6\u30af\u30e9\u30a4\u30ca\u4fb5\u653b\u304c\u518d\u3073\u4e16\u754c\u7d4c\u6e08\u3092\u76f4\u6483\u3057\u307e\u3057\u305f\u3002 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GridDB\u3092\u5229\u7528\u3057\u3066\u3001\u5404\u56fd\u306e\u7d4c\u6e08 [&hellip;]<\/p>\n","protected":false},"author":41,"featured_media":49490,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1005],"tags":[],"class_list":["post-50817","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>GridDB\u3092\u4f7f\u3063\u305f\u5404\u56fd\u306eGDP\u5206\u6790 | GridDB: Open Source Time Series Database for IoT<\/title>\n<meta name=\"description\" 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