{"id":2822,"date":"2023-07-20T12:54:32","date_gmt":"2023-07-20T12:54:32","guid":{"rendered":"https:\/\/statorials.org\/ja\/python%e3%81%ae%e7%b4%af%e7%a9%8d%e5%b9%b3%e5%9d%87\/"},"modified":"2023-07-20T12:54:32","modified_gmt":"2023-07-20T12:54:32","slug":"python%e3%81%ae%e7%b4%af%e7%a9%8d%e5%b9%b3%e5%9d%87","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/python%e3%81%ae%e7%b4%af%e7%a9%8d%e5%b9%b3%e5%9d%87\/","title":{"rendered":"Python \u3067\u7d2f\u7a4d\u5e73\u5747\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>\u7d2f\u7a4d\u5e73\u5747\u306f\u3001<\/strong>\u3042\u308b\u6642\u70b9\u307e\u3067\u306e\u4e00\u9023\u306e\u5024\u306e\u5e73\u5747\u3092\u793a\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u306e\u5217\u306e\u5024\u306e\u7d2f\u7a4d\u5e73\u5747\u3092\u8a08\u7b97\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df[' <span style=\"color: #ff0000;\">column_name<\/span> ']. <span style=\"color: #3366ff;\">expanding<\/span> (). <span style=\"color: #3366ff;\">mean<\/span> ()<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u4f8b\u306f\u3001\u3053\u306e\u69cb\u6587\u3092\u5b9f\u969b\u306b\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u4f8b: Python \u3067\u7d2f\u7a4d\u5e73\u5747\u3092\u8a08\u7b97\u3059\u308b<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u9023\u7d9a 16 \u65e5\u9593\u306e\u5e97\u8217\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;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">day<\/span> ': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16],\n                   ' <span style=\"color: #ff0000;\">sales<\/span> ': [3, 6, 0, 2, 4, 1, 0, 1, 4, 7, 3, 3, 8, 3, 5, 5]})\n\n<span style=\"color: #008080;\">#view first five rows of DataFrame\n<\/span>df. <span style=\"color: #3366ff;\">head<\/span> ()\n\n\tday sales\n0 1 3\n1 2 6\n2 3 0\n3 4 2\n4 5 4<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001sales \u5217\u306e\u79fb\u52d5\u5e73\u5747\u3092\u8a08\u7b97\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#calculate average of 'sales' column\n<\/span>df[' <span style=\"color: #ff0000;\">sales<\/span> ']. <span style=\"color: #3366ff;\">expanding<\/span> (). <span style=\"color: #3366ff;\">mean<\/span> ()\n\n0 3.000000\n1 4.500000\n2 3.000000\n3 2.750000\n4 3.000000\n5 2.666667\n6 2.285714\n7 2.125000\n8 2.333333\n9 2.800000\n10 2.818182\n11 2.833333\n12 3.230769\n13 3.214286\n14 3.333333\n15 3.437500\nName: sales, dtype: float64\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u7d2f\u7a4d\u5e73\u5747\u5024\u306f\u6b21\u306e\u3088\u3046\u306b\u89e3\u91c8\u3055\u308c\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u521d\u58f2\u984d\u306e\u7d2f\u7a4d\u5e73\u5747\u306f<strong>3<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6700\u521d\u306e 2 \u3064\u306e\u58f2\u4e0a\u5024\u306e\u7d2f\u7a4d\u5e73\u5747\u306f<strong>4.5<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6700\u521d\u306e 3 \u3064\u306e\u58f2\u4e0a\u5024\u306e\u7d2f\u7a4d\u5e73\u5747\u306f<strong>3<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6700\u521d\u306e 4 \u3064\u306e\u58f2\u4e0a\u5024\u306e\u7d2f\u7a4d\u5e73\u5747\u306f<strong>2.75<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u7b49\u3005\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u3092\u4f7f\u7528\u3057\u3066\u3001\u7d2f\u7a4d\u5e73\u5747\u58f2\u4e0a\u5024\u3092 DataFrame \u306e\u65b0\u3057\u3044\u5217\u3068\u3057\u3066\u8ffd\u52a0\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#add cumulative average sales as new column\n<\/span>df[' <span style=\"color: #ff0000;\">cum_avg_sales<\/span> '] = df[' <span style=\"color: #ff0000;\">sales<\/span> ']. <span style=\"color: #3366ff;\">expanding<\/span> (). <span style=\"color: #3366ff;\">mean<\/span> ()\n\n<span style=\"color: #008080;\">#view updated DataFrame\n<\/span>df\n\n\tday sales cum_avg_sales\n0 1 3 3.000000\n1 2 6 4.500000\n2 3 0 3.000000\n3 4 2 2.750000\n4 5 4 3.000000\n5 6 1 2.666667\n6 7 0 2.285714\n7 8 1 2.125000\n8 9 4 2.333333\n9 10 7 2.800000\n10 11 3 2.818182\n11 12 3 2.833333\n12 13 8 3.230769\n13 14 3 3.214286\n14 15 5 3.333333\n15 16 5 3.437500\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>Cum_avg_sales<\/strong>\u5217\u306b\u306f\u3001\u300csales\u300d\u5217\u306e\u5024\u306e\u7d2f\u7a4d\u5e73\u5747\u304c\u8868\u793a\u3055\u308c\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\u30e1\u30c8\u30ea\u30af\u30b9\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5\u3092\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ja\/python\u306e\u4e2d\u7a0b\u5ea6\u306e\u30b5\u30a4\u30b9\u3099\/\" target=\"_blank\" rel=\"noopener\">Python \u3067\u30c8\u30ea\u30df\u30f3\u30b0\u5e73\u5747\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u5e7e\u4f55\u5e73\u5747\u30cf\u309a\u30a4\u30bd\u30f3\/\" target=\"_blank\" rel=\"noopener\">Python \u3067\u5e7e\u4f55\u5e73\u5747\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u79fb\u52d5\u5e73\u5747python\/\" target=\"_blank\" rel=\"noopener\">Python \u3067\u79fb\u52d5\u5e73\u5747\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u7d2f\u7a4d\u5e73\u5747\u306f\u3001\u3042\u308b\u6642\u70b9\u307e\u3067\u306e\u4e00\u9023\u306e\u5024\u306e\u5e73\u5747\u3092\u793a\u3057\u307e\u3059\u3002 \u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u306e\u5217\u306e\u5024\u306e\u7d2f\u7a4d\u5e73\u5747\u3092\u8a08\u7b97\u3067\u304d\u307e\u3059\u3002 df[&#8216; column_name &#8216;]. expanding (). mea [&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-2822","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 GPA 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