{"id":3796,"date":"2023-07-15T11:39:13","date_gmt":"2023-07-15T11:39:13","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%af5%e6%a1%81%e3%81%a6%e3%82%99%e5%86%8d%e9%96%8b\/"},"modified":"2023-07-15T11:39:13","modified_gmt":"2023-07-15T11:39:13","slug":"%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%af5%e6%a1%81%e3%81%a6%e3%82%99%e5%86%8d%e9%96%8b","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%af5%e6%a1%81%e3%81%a6%e3%82%99%e5%86%8d%e9%96%8b\/","title":{"rendered":"Pandas \u3067 5 \u3064\u306e\u6570\u5024\u306e\u8981\u7d04\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>5 \u6841\u306e\u8981\u7d04\u306f<\/strong>\u3001\u6b21\u306e 5 \u3064\u306e\u5024\u3092\u4f7f\u7528\u3057\u3066\u4e00\u9023\u306e\u30c7\u30fc\u30bf\u3092\u8981\u7d04\u3059\u308b\u65b9\u6cd5\u3067\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u6700\u5c0f<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6700\u521d\u306e\u56db\u5206\u4f4d<\/span><\/li>\n<li><span style=\"color: #000000;\">\u4e2d\u592e\u5024<\/span><\/li>\n<li><span style=\"color: #000000;\">\u7b2c 3 \u56db\u5206\u4f4d<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6700\u5927<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">5 \u6841\u306e\u8981\u7d04\u306f\u3001\u6b21\u306e\u3088\u3046\u306b\u30c7\u30fc\u30bf\u5206\u5e03\u306e\u7c21\u6f54\u306a\u8981\u7d04\u3092\u63d0\u4f9b\u3059\u308b\u305f\u3081\u4fbf\u5229\u3067\u3059\u3002<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/ja\/\u4e2d\u5fc3\u50be\u5411\u3092\u6e2c\u5b9a\u3059\u308b\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u4e2d\u592e\u5024\u3092\u4f7f\u7528\u3057\u3066\u3001\u4e2d\u592e\u5024\u304c<\/a>\u3069\u3053\u306b\u3042\u308b\u304b\u3092\u793a\u3057\u307e\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u3053\u308c\u306f\u3001\u7b2c 1 \u56db\u5206\u4f4d\u6570\u3068\u7b2c 3 \u56db\u5206\u4f4d\u6570\u3092\u4f7f\u7528\u3057\u3066\u30c7\u30fc\u30bf\u306e\u5206\u5e03\u3092\u793a\u3057\u307e\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6700\u5c0f\u5024\u3068\u6700\u5927\u5024\u3092\u4f7f\u7528\u3057\u3066\u30c7\u30fc\u30bf\u306e\u7bc4\u56f2\u3092\u793a\u3057\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">pandas DataFrame \u5185\u306e\u5909\u6570\u306e 5 \u3064\u306e\u6570\u5024\u306e\u8981\u7d04\u3092\u8a08\u7b97\u3059\u308b\u6700\u3082\u7c21\u5358\u306a\u65b9\u6cd5\u306f\u3001\u6b21\u306e\u3088\u3046\u306b<strong>description()<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3067\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">describe<\/span> (). <span style=\"color: #3366ff;\">loc<\/span> [[' <span style=\"color: #ff0000;\">min<\/span> ', '25 <span style=\"color: #ff0000;\">%<\/span> ', '50 <span style=\"color: #ff0000;\">%<\/span> ', <span style=\"color: #ff0000;\">'75%<\/span> ', ' <span style=\"color: #ff0000;\">max<\/span> ']]\n<\/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<h2><span style=\"color: #000000;\"><strong>\u4f8b: Pandas DataFrame \u3067 5 \u3064\u306e\u6570\u5024\u306e\u8981\u7d04\u3092\u8a08\u7b97\u3059\u308b<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u3055\u307e\u3056\u307e\u306a\u30d0\u30b9\u30b1\u30c3\u30c8\u30dc\u30fc\u30eb\u9078\u624b\u306b\u95a2\u3059\u308b\u60c5\u5831\u3092\u542b\u3080\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;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],\n                   ' <span style=\"color: #ff0000;\">points<\/span> ': [18, 22, 19, 14, 14, 11, 20, 28],\n                   ' <span style=\"color: #ff0000;\">assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' <span style=\"color: #ff0000;\">rebounds<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n  team points assists rebounds\n0 A 18 5 11\n1 B 22 7 8\n2 C 19 7 10\n3 D 14 9 6\n4 E 14 12 6\n5 F 11 9 5\n6 G 20 9 9\n7:28 4 12<\/strong><\/span><\/pre>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001DataFrame \u5185\u306e\u5404\u6570\u5024\u5909\u6570\u306e 5 \u3064\u306e\u6570\u5024\u306e\u8981\u7d04\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 five number summary for each numeric variable<\/span>\ndf. <span style=\"color: #3366ff;\">describe<\/span> (). <span style=\"color: #3366ff;\">loc<\/span> [[' <span style=\"color: #ff0000;\">min<\/span> ', '25 <span style=\"color: #ff0000;\">%<\/span> ', '50 <span style=\"color: #ff0000;\">%<\/span> ', <span style=\"color: #ff0000;\">'75%<\/span> ', ' <span style=\"color: #ff0000;\">max<\/span> ']]\n\n      points assists rebounds\nmin 11.0 4.0 5.00\n25% 14.0 6.5 6.00\n50% 18.5 8.0 8.50\n75% 20.5 9.0 10.25\nmax 28.0 12.0 12.00\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\"><strong>\u30dd\u30a4\u30f3\u30c8<\/strong>\u5909\u6570\u306e\u7d50\u679c\u3092\u89e3\u91c8\u3059\u308b\u65b9\u6cd5\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u6700\u5c0f\u5024\u306f<strong>11<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\">25 \u30d1\u30fc\u30bb\u30f3\u30bf\u30a4\u30eb\u306e\u5024\u306f<strong>14<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\">50 \u30d1\u30fc\u30bb\u30f3\u30bf\u30a4\u30eb\u5024\u306f<strong>18.5<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\">75 \u30d1\u30fc\u30bb\u30f3\u30bf\u30a4\u30eb\u5024\u306f<strong>20.5<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6700\u5927\u5024\u306f<strong>28<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\"><strong>\u30d8\u30eb\u30d7<\/strong>\u5909\u6570\u3068<strong>\u30ea\u30d0\u30a6\u30f3\u30c9<\/strong>\u5909\u6570\u306e\u5024\u3082\u540c\u69d8\u306b\u89e3\u91c8\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\">DataFrame \u5185\u306e\u7279\u5b9a\u306e\u5909\u6570\u306e 5 \u3064\u306e\u6570\u5024\u306e\u8981\u7d04\u306e\u307f\u3092\u8a08\u7b97\u3057\u305f\u3044\u5834\u5408\u306f\u3001\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#calculate five number summary for the points variable<\/span>\ndf[' <span style=\"color: #ff0000;\">points<\/span> ']. <span style=\"color: #3366ff;\">describe<\/span> (). <span style=\"color: #3366ff;\">loc<\/span> [[' <span style=\"color: #ff0000;\">min<\/span> ', '25 <span style=\"color: #ff0000;\">%<\/span> ', '50 <span style=\"color: #ff0000;\">%<\/span> ', <span style=\"color: #ff0000;\">'75%<\/span> ', ' <span style=\"color: #ff0000;\">max<\/span> ']]\n\nmin 11.0\n25% 14.0\n50% 18.5\n75% 20.5\nmax 28.0\nName: points, dtype: float64\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u51fa\u529b\u306b\u306f\u3001<strong>\u30dd\u30a4\u30f3\u30c8<\/strong>\u5909\u6570\u306e\u307f\u306e 5 \u6841\u306e\u8981\u7d04\u304c\u8868\u793a\u3055\u308c\u307e\u3059\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001\u4ed6\u306e\u4e00\u822c\u7684\u306a\u30d1\u30f3\u30c0\u306e\u30bf\u30b9\u30af\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\/\u30cf\u309a\u30f3\u30bf\u3099\u306e\u5468\u6ce2\u6570\u30ab\u30a6\u30f3\u30c8\/\" target=\"_blank\" rel=\"noopener\">Pandas: \u5217\u5185\u306e\u5024\u306e\u983b\u5ea6\u6570\u3092\u53d6\u5f97\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u30af\u3099\u30eb\u30fc\u30d5\u309a\u3053\u3099\u3068\u306b\u4e2d\u578b\u306e\u30cf\u309a\u30f3\u30bf\u3099\/\" target=\"_blank\" rel=\"noopener\">\u30d1\u30f3\u30c0: \u30b0\u30eb\u30fc\u30d7\u3054\u3068\u306e\u5e73\u5747\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u30af\u3099\u30eb\u30fc\u30d5\u309a\u3042\u305f\u308a\u306e\u30cf\u309a\u30f3\u30bf\u3099\u306e\u4e2d\u592e\u5024\/\" target=\"_blank\" rel=\"noopener\">\u30d1\u30f3\u30c0: \u30b0\u30eb\u30fc\u30d7\u3054\u3068\u306b\u4e2d\u592e\u5024\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>5 \u6841\u306e\u8981\u7d04\u306f\u3001\u6b21\u306e 5 \u3064\u306e\u5024\u3092\u4f7f\u7528\u3057\u3066\u4e00\u9023\u306e\u30c7\u30fc\u30bf\u3092\u8981\u7d04\u3059\u308b\u65b9\u6cd5\u3067\u3059\u3002 \u6700\u5c0f \u6700\u521d\u306e\u56db\u5206\u4f4d \u4e2d\u592e\u5024 \u7b2c 3 \u56db\u5206\u4f4d \u6700\u5927 5 \u6841\u306e\u8981\u7d04\u306f\u3001\u6b21\u306e\u3088\u3046\u306b\u30c7\u30fc\u30bf\u5206\u5e03\u306e\u7c21\u6f54\u306a\u8981\u7d04\u3092\u63d0\u4f9b\u3059\u308b\u305f\u3081\u4fbf\u5229\u3067\u3059\u3002 \u4e2d\u592e\u5024\u3092\u4f7f\u7528\u3057\u3066\u3001\u4e2d [&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-3796","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>pandas \u3067 5 \u3064\u306e\u6570\u5024\u306e\u8981\u7d04\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5 - Statorials<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001pandas \u3067 5 \u3064\u306e\u6570\u5024\u306e\u8981\u7d04\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5\u3092\u4f8b\u3068\u3068\u3082\u306b\u8aac\u660e\u3057\u307e\u3059\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link 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\u3064\u306e\u6570\u5024\u306e\u8981\u7d04\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5 - Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/ja\/#website\"},\"datePublished\":\"2023-07-15T11:39:13+00:00\",\"dateModified\":\"2023-07-15T11:39:13+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/ja\/#\/schema\/person\/86b92d2dd87368b26360d19d9c6a5d83\"},\"description\":\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001pandas \u3067 5 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