{"id":1169,"date":"2023-07-27T10:11:54","date_gmt":"2023-07-27T10:11:54","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e7%9b%b8%e9%96%a2%e3%83%98%e3%82%99%e3%82%a2%e3%83%aa%e3%83%b3%e3%82%af%e3%82%99\/"},"modified":"2023-07-27T10:11:54","modified_gmt":"2023-07-27T10:11:54","slug":"%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e7%9b%b8%e9%96%a2%e3%83%98%e3%82%99%e3%82%a2%e3%83%aa%e3%83%b3%e3%82%af%e3%82%99","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e7%9b%b8%e9%96%a2%e3%83%98%e3%82%99%e3%82%a2%e3%83%aa%e3%83%b3%e3%82%af%e3%82%99\/","title":{"rendered":"\u30d1\u30f3\u30c0\u3067\u30ed\u30fc\u30ea\u30f3\u30b0\u76f8\u95a2\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5: \u4f8b\u4ed8\u304d"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>\u30ed\u30fc\u30ea\u30f3\u30b0\u76f8\u95a2\u306f\u3001<\/strong>\u30b9\u30e9\u30a4\u30c7\u30a3\u30f3\u30b0 \u30a6\u30a3\u30f3\u30c9\u30a6\u306b\u308f\u305f\u308b 2 \u3064\u306e\u6642\u7cfb\u5217\u9593\u306e\u76f8\u95a2\u3067\u3059\u3002\u3053\u306e\u30bf\u30a4\u30d7\u306e\u76f8\u95a2\u95a2\u4fc2\u306e\u5229\u70b9\u306e 1 \u3064\u306f\u30012 \u3064\u306e\u6642\u7cfb\u5217\u9593\u306e\u76f8\u95a2\u95a2\u4fc2\u3092\u7d4c\u6642\u7684\u306b\u8996\u899a\u5316\u3067\u304d\u308b\u3053\u3068\u3067\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Python \u3067 pandas DataFrame \u306e\u30ed\u30fc\u30ea\u30f3\u30b0\u76f8\u95a2\u3092\u8a08\u7b97\u3057\u3066\u8996\u899a\u5316\u3059\u308b\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n<h3><strong>\u30d1\u30f3\u30c0\u3067\u30ed\u30fc\u30ea\u30f3\u30b0\u76f8\u95a2\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5<\/strong><\/h3>\n<p><span style=\"color: #000000;\">15 \u304b\u6708\u9593\u3067 2 \u3064\u306e\u7570\u306a\u308b\u88fd\u54c1 ( <em>x<\/em>\u3068<em>y<\/em> ) \u306e\u8ca9\u58f2\u7dcf\u6570\u3092\u8868\u793a\u3059\u308b\u6b21\u306e\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u304c\u3042\u308b\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd<\/span>\n<span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np<\/span>\n\n#createDataFrame<\/span>\ndf = pd.DataFrame({'month': np. <span style=\"color: #3366ff;\">arange<\/span> (1, 16),\n                   'x': [13, 15, 16, 15, 17, 20, 22, 24, 25, 26, 23, 24, 23, 22, 20],\n                   'y': [22, 24, 23, 27, 26, 26, 27, 30, 33, 32, 27, 25, 28, 26, 28]})\n\n<span style=\"color: #008080;\">#view first six rows\n<\/span>df. <span style=\"color: #3366ff;\">head<\/span> ()\n\n  month xy\n1 1 13 22\n2 2 15 24\n3 3 16 23\n4 4 15 27\n5 5 17 26\n6 6 20 26<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">pandas \u3067\u30ed\u30fc\u30ea\u30f3\u30b0\u76f8\u95a2\u3092\u8a08\u7b97\u3059\u308b\u306b\u306f\u3001 <a href=\"https:\/\/pandas.pydata.org\/pandas-docs\/stable\/reference\/api\/pandas.core.window.rolling.Rolling.corr.html\" target=\"_blank\" rel=\"noopener noreferrer\">Rolling.corr() \u95a2\u6570<\/a>\u3092\u4f7f\u7528\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u95a2\u6570\u306f\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>df[&#8216;x&#8217;].rolling(width).corr(df[&#8216;y&#8217;])<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u91d1\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>df:<\/strong>\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u540d<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>width:<\/strong>\u30b9\u30e9\u30a4\u30c7\u30a3\u30f3\u30b0\u76f8\u95a2\u306e\u30a6\u30a3\u30f3\u30c9\u30a6\u306e\u5e45\u3092\u6307\u5b9a\u3059\u308b\u6574\u6570<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>x\u3001y:<\/strong>\u9593\u306e\u30b9\u30e9\u30a4\u30c9\u76f8\u95a2\u3092\u8a08\u7b97\u3059\u308b\u305f\u3081\u306e 2 \u3064\u306e\u5217\u540d<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u3053\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001\u88fd\u54c1<em>x<\/em>\u3068\u88fd\u54c1<em>y<\/em>\u306e\u9593\u306e\u58f2\u4e0a\u306e 3 \u304b\u6708\u306e\u30ed\u30fc\u30ea\u30f3\u30b0\u76f8\u95a2\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#calculate 3-month rolling correlation between sales for <em>x<\/em> and <em>y<\/em><\/span>\ndf[' <span style=\"color: #008000;\">x<\/span> ']. <span style=\"color: #3366ff;\">rolling<\/span> (3). <span style=\"color: #3366ff;\">corr<\/span> (df[' <span style=\"color: #008000;\">y<\/span> '])\n\n0 NaN\n1 NaN\n2 0.654654\n3 -0.693375\n4 -0.240192\n5 -0.802955\n6 0.802955\n7 0.960769\n8 0.981981\n9 0.654654\n10 0.882498\n11 0.817057\n12 -0.944911\n13 -0.327327\n14 -0.188982\ndtype:float64\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u3053\u306e\u95a2\u6570\u306f\u3001\u904e\u53bb 3 \u304b\u6708\u9593\u306e 2 \u3064\u306e\u88fd\u54c1\u306e\u58f2\u4e0a\u9593\u306e\u76f8\u95a2\u95a2\u4fc2\u3092\u8fd4\u3057\u307e\u3059\u3002\u4f8b\u3048\u3070\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">1 \uff5e 3 \u304b\u6708\u9593\u306e\u58f2\u4e0a\u306e\u76f8\u95a2\u306f<strong>0.654654<\/strong>\u3067\u3057\u305f\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\">2 \uff5e 4 \u304b\u6708\u9593\u306e\u58f2\u4e0a\u76f8\u95a2\u306f<strong>-0.693375 \u3067\u3057\u305f\u3002<\/strong><\/span><\/li>\n<li> <span style=\"color: #000000;\">3 \uff5e 5 \u304b\u6708\u9593\u306e\u58f2\u4e0a\u76f8\u95a2\u306f<strong>-0.240192 \u3067\u3057\u305f\u3002<\/strong><\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u7b49\u3005\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u5f0f\u3092\u7c21\u5358\u306b\u8abf\u6574\u3057\u3066\u3001\u7570\u306a\u308b\u671f\u9593\u306e\u30ed\u30fc\u30ea\u30f3\u30b0\u76f8\u95a2\u3092\u8a08\u7b97\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30012 \u3064\u306e\u88fd\u54c1\u9593\u306e\u58f2\u4e0a\u306e 6 \u304b\u6708\u306e\u30ed\u30fc\u30ea\u30f3\u30b0\u76f8\u95a2\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#calculate 6-month rolling correlation between sales for <em>x<\/em> and <em>y<\/em><\/span>\ndf[' <span style=\"color: #008000;\">x<\/span> ']. <span style=\"color: #3366ff;\">rolling<\/span> (6). <span style=\"color: #3366ff;\">corr<\/span> (df[' <span style=\"color: #008000;\">y<\/span> ']) \n0 NaN\n1 NaN\n2 NaN\n3 NaN\n4 NaN\n5 0.558742\n6 0.485855\n7 0.693103\n8 0.756476\n9 0.895929\n10 0.906772\n11 0.715542\n12 0.717374\n13 0.768447\n14 0.454148\ndtype:float64\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u3053\u306e\u95a2\u6570\u306f\u3001\u904e\u53bb 6 \u304b\u6708\u9593\u306e 2 \u3064\u306e\u88fd\u54c1\u58f2\u4e0a\u9593\u306e\u76f8\u95a2\u95a2\u4fc2\u3092\u8fd4\u3057\u307e\u3059\u3002\u4f8b\u3048\u3070\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">1 \u304b\u6708\u76ee\u304b\u3089 6 \u304b\u6708\u76ee\u306e\u58f2\u4e0a\u306e\u76f8\u95a2\u306f<strong>0.558742<\/strong>\u3067\u3057\u305f\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\">2 \uff5e 7 \u304b\u6708\u9593\u306e\u58f2\u4e0a\u76f8\u95a2\u306f<strong>0.485855 \u3067\u3057\u305f\u3002<\/strong><\/span><\/li>\n<li> <span style=\"color: #000000;\">3 \uff5e 8 \u304b\u6708\u9593\u306e\u58f2\u4e0a\u76f8\u95a2\u306f<strong>0.693103 \u3067\u3057\u305f\u3002<\/strong><\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u7b49\u3005\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u30b3\u30e1\u30f3\u30c8<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u3053\u308c\u3089\u306e\u4f8b\u3067\u4f7f\u7528\u3055\u308c\u3066\u3044\u308b\u95a2\u6570\u306b\u95a2\u3059\u308b\u3044\u304f\u3064\u304b\u306e\u6ce8\u610f\u4e8b\u9805\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u76f8\u95a2\u95a2\u4fc2\u3092\u8a08\u7b97\u3059\u308b\u306b\u306f\u3001<strong>\u5e45<\/strong>(\u3064\u307e\u308a\u3001\u30c9\u30ed\u30c3\u30d7\u30c0\u30a6\u30f3 \u30a6\u30a3\u30f3\u30c9\u30a6) \u304c 3 \u4ee5\u4e0a\u3067\u3042\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\">Rolling.corr() \u95a2\u6570\u306e\u5b8c\u5168\u306a\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u306f<a href=\"https:\/\/pandas.pydata.org\/pandas-docs\/stable\/reference\/api\/pandas.core.window.rolling.Rolling.corr.html\" target=\"_blank\" rel=\"noopener noreferrer\">\u3053\u3053\u306b<\/a>\u3042\u308a\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<h3><span style=\"color: #000000;\"><strong>\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h3>\n<p><a href=\"https:\/\/statorials.org\/ja\/r-\u306e\u30ed\u30fc\u30ea\u30f3\u30af\u3099\u76f8\u95a2\/\" target=\"_blank\" rel=\"noopener noreferrer\">R \u3067\u30b9\u30e9\u30a4\u30c9\u76f8\u95a2\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u30ed\u30fc\u30ea\u30f3\u30af\u3099\u76f8\u95a2\u30a8\u30af\u30bb\u30eb\/\" target=\"_blank\" rel=\"noopener noreferrer\">Excel \u3067\u30ed\u30fc\u30ea\u30f3\u30b0\u76f8\u95a2\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u30ed\u30fc\u30ea\u30f3\u30b0\u76f8\u95a2\u306f\u3001\u30b9\u30e9\u30a4\u30c7\u30a3\u30f3\u30b0 \u30a6\u30a3\u30f3\u30c9\u30a6\u306b\u308f\u305f\u308b 2 \u3064\u306e\u6642\u7cfb\u5217\u9593\u306e\u76f8\u95a2\u3067\u3059\u3002\u3053\u306e\u30bf\u30a4\u30d7\u306e\u76f8\u95a2\u95a2\u4fc2\u306e\u5229\u70b9\u306e 1 \u3064\u306f\u30012 \u3064\u306e\u6642\u7cfb\u5217\u9593\u306e\u76f8\u95a2\u95a2\u4fc2\u3092\u7d4c\u6642\u7684\u306b\u8996\u899a\u5316\u3067\u304d\u308b\u3053\u3068\u3067\u3059\u3002 \u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Python  [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-1169","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u30d1\u30f3\u30c0\u3067\u30ed\u30fc\u30ea\u30f3\u30b0\u76f8\u95a2\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5: 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