{"id":2361,"date":"2023-07-22T14:41:49","date_gmt":"2023-07-22T14:41:49","guid":{"rendered":"https:\/\/statorials.org\/ja\/python%e3%83%aa%e3%82%b5%e3%83%b3%e3%83%95%e3%82%9a%e3%83%ab%e6%99%82%e7%b3%bb%e5%88%97\/"},"modified":"2023-07-22T14:41:49","modified_gmt":"2023-07-22T14:41:49","slug":"python%e3%83%aa%e3%82%b5%e3%83%b3%e3%83%95%e3%82%9a%e3%83%ab%e6%99%82%e7%b3%bb%e5%88%97","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/python%e3%83%aa%e3%82%b5%e3%83%b3%e3%83%95%e3%82%9a%e3%83%ab%e6%99%82%e7%b3%bb%e5%88%97\/","title":{"rendered":"Python \u3067\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u30ea\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u3059\u308b\u65b9\u6cd5 (\u4f8b\u4ed8\u304d)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e<strong>\u30ea\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u3068\u306f<\/strong>\u3001\u65b0\u3057\u3044\u671f\u9593\u306e\u30c7\u30fc\u30bf\u3092\u8981\u7d04\u307e\u305f\u306f\u96c6\u8a08\u3059\u308b\u3053\u3068\u3092\u610f\u5473\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u57fa\u672c\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001Python \u3067\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u30ea\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#find sum of values in column1 by month<\/span>\nweekly_df[' <span style=\"color: #ff0000;\">column1<\/span> '] = df[' <span style=\"color: #ff0000;\">column1<\/span> ']. <span style=\"color: #3366ff;\">resample<\/span> (' <span style=\"color: #ff0000;\">M<\/span> '). <span style=\"color: #3366ff;\">sum<\/span> ()\n\n<span style=\"color: #008080;\">#find mean of values in column1 by week<\/span>\nweekly_df[' <span style=\"color: #ff0000;\">column1<\/span> '] = df[' <span style=\"color: #ff0000;\">column1<\/span> ']. <span style=\"color: #3366ff;\">resample<\/span> (' <span style=\"color: #ff0000;\">W<\/span> '). <span style=\"color: #3366ff;\">mean<\/span> () \n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u6b21\u306e\u3088\u3046\u306a\u7570\u306a\u308b\u671f\u9593\u306b\u30ea\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u3067\u304d\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>S<\/strong> : \u79d2<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>min<\/strong> : \u5206<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>H<\/strong> : \u6642\u9593<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>J<\/strong> \uff1a\u65e5<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>W<\/strong> : \u9031<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>M<\/strong> \uff1a\u6708<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>Q<\/strong> : \u56db\u534a\u671f<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>A<\/strong> : \u5e74<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u4f8b\u306f\u3001\u5b9f\u969b\u306b\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u30ea\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u4f8b: Python \u3067\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u30ea\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u3059\u308b<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">1 \u5e74\u9593\u306b\u308f\u305f\u308b\u4f01\u696d\u306e 1 \u6642\u9593\u3054\u3068\u306e\u7dcf\u58f2\u4e0a\u9ad8\u3092\u793a\u3059\u6b21\u306e\u30d1\u30f3\u30c0 \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: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n<span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n\n<span style=\"color: #008080;\">#make this example reproducible\n<\/span>n.p. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">seeds<\/span> (0)\n\n<span style=\"color: #008080;\">#create DataFrame with hourly index\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> (index= <span style=\"color: #3366ff;\">pd.date_range<\/span> (' <span style=\"color: #ff0000;\">2020-01-06<\/span> ', ' <span style=\"color: #ff0000;\">2020-12-27<\/span> ', freq=' <span style=\"color: #ff0000;\">h<\/span> '))\n\n<span style=\"color: #008080;\">#add column to show sales by hour\n<\/span>df[' <span style=\"color: #ff0000;\">sales<\/span> '] = np. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">randint<\/span> (low=0, high=20, size= <span style=\"color: #008000;\">len<\/span> (df. <span style=\"color: #3366ff;\">index<\/span> ))\n\n<span style=\"color: #008080;\">#view first five rows of DataFrame\n<\/span>df. <span style=\"color: #3366ff;\">head<\/span> ()\n\n\t             dirty\n2020-01-06 00:00:00 12\n2020-01-06 01:00:00 15\n2020-01-06 02:00:00 0\n2020-01-06 03:00:00 3\n2020-01-06 04:00:00 3\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u8ca9\u58f2\u30c7\u30fc\u30bf\u3092\u8996\u899a\u5316\u3059\u308b\u305f\u3081\u306b\u6298\u308c\u7dda\u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3059\u308b\u3068\u3001\u6b21\u306e\u3088\u3046\u306b\u306a\u308a\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> matplotlib. <span style=\"color: #3366ff;\">pyplot<\/span> <span style=\"color: #008000;\">as<\/span> plt\n<\/span>\n#plot time series data\n<span style=\"color: #000000;\">plt. <span style=\"color: #3366ff;\">plot<\/span> (df. <span style=\"color: #3366ff;\">index<\/span> , df. <span style=\"color: #3366ff;\">sales<\/span> , linewidth= <span style=\"color: #008000;\">3<\/span> )<\/span><\/span><\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-21395 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/heures1.png\" alt=\"\" width=\"575\" height=\"376\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u30b0\u30e9\u30d5\u306f\u89e3\u91c8\u304c\u96e3\u3057\u3044\u305f\u3081\u3001\u9031\u3054\u3068\u306e\u58f2\u4e0a\u30c7\u30fc\u30bf\u3092\u8981\u7d04\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create new DataFrame\n<span style=\"color: #000000;\">weekly_df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ()\n\n<span style=\"color: #008080;\">#create 'sales' column that summarizes total sales by week\n<\/span>weekly_df[' <span style=\"color: #ff0000;\">sales<\/span> '] = df[' <span style=\"color: #ff0000;\">sales<\/span> ']. <span style=\"color: #3366ff;\">resample<\/span> (' <span style=\"color: #ff0000;\">W<\/span> '). <span style=\"color: #3366ff;\">sum<\/span> ()\n\n<span style=\"color: #008080;\">#view first five rows of DataFrame\n<\/span>weekly_df. <span style=\"color: #3366ff;\">head<\/span> ()\n\n                dirty\n2020-01-12 1519\n2020-01-19 1589\n2020-01-26 1540\n2020-02-02 1562\n2020-02-09 1614<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u3053\u306e\u65b0\u3057\u3044\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306f\u3001\u9031\u3054\u3068\u306e\u58f2\u4e0a\u306e\u5408\u8a08\u3092\u793a\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306b\u3001\u3053\u306e\u9031\u6b21\u30c7\u30fc\u30bf\u3092\u4f7f\u7528\u3057\u3066\u6642\u7cfb\u5217\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3067\u304d\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> matplotlib. <span style=\"color: #3366ff;\">pyplot<\/span> <span style=\"color: #008000;\">as<\/span> plt\n<\/span>\n#plot weekly sales data\n<span style=\"color: #000000;\">plt. <span style=\"color: #3366ff;\">plot<\/span> ( <span style=\"color: #3366ff;\">weekly_df.index<\/span> , <span style=\"color: #3366ff;\">weekly_df.sales<\/span> , linewidth= <span style=\"color: #008000;\">3<\/span> )<\/span><\/span><\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-21396 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/fois2.png\" alt=\"\" width=\"556\" height=\"328\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u6700\u521d\u306e\u4f8b\u306e 8,545 \u6642\u9593\u3054\u3068\u306e\u58f2\u4e0a\u30c7\u30fc\u30bf\u3068\u306f\u5bfe\u7167\u7684\u306b\u300151 \u9031\u3054\u3068\u306e\u58f2\u4e0a\u30c7\u30fc\u30bf\u306e\u307f\u3092\u8868\u3057\u3066\u3044\u308b\u305f\u3081\u3001\u3053\u306e\u30b0\u30e9\u30d5\u306f\u975e\u5e38\u306b\u8aad\u307f\u3084\u3059\u304f\u306a\u3063\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u6ce8<\/strong>: \u3053\u306e\u4f8b\u3067\u306f\u3001\u8ca9\u58f2\u30c7\u30fc\u30bf\u3092\u9031\u3054\u3068\u306b\u8981\u7d04\u3057\u307e\u3057\u305f\u304c\u3001\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u306e\u6570\u3092\u3055\u3089\u306b\u5c11\u306a\u304f\u3057\u305f\u3044\u5834\u5408\u306f\u3001\u6708\u307e\u305f\u306f\u56db\u534a\u671f\u3054\u3068\u306b\u8981\u7d04\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Python \u3067\u4ed6\u306e\u4e00\u822c\u7684\u306a\u64cd\u4f5c\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ja\/matplotlib-\u6642\u7cfb\u5217\/\" target=\"_blank\" rel=\"noopener\">Matplotlib \u3067\u6642\u7cfb\u5217\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u30b7\u30fc\u30db\u3099\u30fc\u30f3\u30bf\u30a4\u30e0\u30e9\u30a4\u30f3\/\" target=\"_blank\" rel=\"noopener\">Seaborn \u3067\u6642\u7cfb\u5217\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u30cf\u309a\u30a4\u30bd\u30f3\u30ab\u30fc\u30c8\u3099\/\" target=\"_blank\" rel=\"noopener\">Python \u3067\u6642\u7cfb\u5217\u304b\u3089 MAPE \u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u306e\u30ea\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u3068\u306f\u3001\u65b0\u3057\u3044\u671f\u9593\u306e\u30c7\u30fc\u30bf\u3092\u8981\u7d04\u307e\u305f\u306f\u96c6\u8a08\u3059\u308b\u3053\u3068\u3092\u610f\u5473\u3057\u307e\u3059\u3002 \u6b21\u306e\u57fa\u672c\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001Python \u3067\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u30ea\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u3067\u304d\u307e\u3059\u3002 #find sum of values in c [&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-2361","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>Python \u3067\u6642\u7cfb\u5217\u30c7\u30fc\u30bf\u3092\u30ea\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u3059\u308b\u65b9\u6cd5 (\u4f8b\u3042\u308a) - \u7d71\u8a08<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Python 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