{"id":3270,"date":"2023-07-18T08:36:45","date_gmt":"2023-07-18T08:36:45","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e5%af%be%e3%83%ad%e3%83%83%e3%82%af\/"},"modified":"2023-07-18T08:36:45","modified_gmt":"2023-07-18T08:36:45","slug":"%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e5%af%be%e3%83%ad%e3%83%83%e3%82%af","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e5%af%be%e3%83%ad%e3%83%83%e3%82%af\/","title":{"rendered":"\u30d1\u30f3\u30c0 vs \u30ed\u30c3\u30af: \u9055\u3044\u306f\u4f55\u3067\u3059\u304b?"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">pandas DataFrame \u306e\u884c\u3068\u5217\u3092\u9078\u629e\u3059\u308b\u5834\u5408\u3001 <b>.loc<\/b>\u3068<strong>.at<\/strong>\u306e 2 \u3064\u306e\u95a2\u6570\u304c\u3088\u304f\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\">2 \u3064\u306e\u95a2\u6570\u306e\u5fae\u5999\u306a\u9055\u3044\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>.loc \u306f<\/strong>\u5165\u529b\u5f15\u6570\u3068\u3057\u3066\u8907\u6570\u306e\u884c\u3068\u5217\u3092\u53d6\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>.at \u306f<\/strong>\u5165\u529b\u5f15\u6570\u3068\u3057\u3066\u5358\u4e00\u306e\u884c\u3068\u5217\u306e\u307f\u3092\u53d6\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u4f8b\u306f\u3001\u6b21\u306e pandas DataFrame \u3067\u5404\u95a2\u6570\u3092\u5b9f\u969b\u306b\u4f7f\u7528\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: #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\n<\/strong><\/pre>\n<h2><span style=\"color: #000000;\"><strong>\u4f8b 1: Pandas \u3067 loc \u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001 <strong>.loc \u3092<\/strong>\u4f7f\u7528\u3057\u3066\u3001\u30dd\u30a4\u30f3\u30c8\u5217\u306e\u30a4\u30f3\u30c7\u30c3\u30af\u30b9\u4f4d\u7f6e 0 \u306b\u3042\u308b DataFrame \u5185\u306e\u5024\u306b\u30a2\u30af\u30bb\u30b9\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;\">#select value located at index position 0 of the points column\n<span style=\"color: #000000;\">df. <span style=\"color: #3366ff;\">loc<\/span> [0, ' <span style=\"color: #ff0000;\">points<\/span> ']\n\n18<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u3053\u308c\u306b\u3088\u308a\u3001\u5024<strong>18<\/strong>\u304c\u8fd4\u3055\u308c\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001 <strong>.loc<\/strong>\u3092\u4f7f\u7528\u3057\u3066\u30a4\u30f3\u30c7\u30c3\u30af\u30b9\u5024 0 \u304b\u3089 4 \u307e\u3067\u306e\u884c\u3001\u304a\u3088\u3073\u30dd\u30a4\u30f3\u30c8\u3068\u30a2\u30b7\u30b9\u30c8\u5217\u306b\u30a2\u30af\u30bb\u30b9\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#select rows between index values 0 and 4 and columns 'points' and 'assists'\n<span style=\"color: #000000;\">df. <span style=\"color: #3366ff;\">loc<\/span> [0:4, [' <span style=\"color: #ff0000;\">points<\/span> ', ' <span style=\"color: #ff0000;\">assists<\/span> ']]\n\n        assist points\n0 18 5\n1 22 7\n2 19 7\n3 14 9\n4 14 12<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u5358\u4e00\u306e\u5024\u306b\u30a2\u30af\u30bb\u30b9\u3059\u308b\u5834\u5408\u3067\u3082\u3001\u884c\u3068\u5217\u306e\u30b0\u30eb\u30fc\u30d7\u306b\u30a2\u30af\u30bb\u30b9\u3059\u308b\u5834\u5408\u3067\u3082\u3001 <strong>.loc<\/strong>\u95a2\u6570\u306f\u4e21\u65b9\u3092\u5b9f\u884c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u4f8b 2: Pandas \u3067\u306e at \u306e\u4f7f\u7528\u65b9\u6cd5<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001 <strong>.at<\/strong>\u3092\u4f7f\u7528\u3057\u3066\u3001\u30dd\u30a4\u30f3\u30c8\u5217\u306e\u30a4\u30f3\u30c7\u30c3\u30af\u30b9\u4f4d\u7f6e 0 \u306b\u3042\u308b DataFrame \u5185\u306e\u5024\u306b\u30a2\u30af\u30bb\u30b9\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;\">#select value located at index position 0 of the points column\n<span style=\"color: #000000;\">df. <span style=\"color: #3366ff;\">at<\/span> [0, ' <span style=\"color: #ff0000;\">points<\/span> ']\n\n18<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u3053\u308c\u306b\u3088\u308a\u3001\u5024<strong>18<\/strong>\u304c\u8fd4\u3055\u308c\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u305f\u3060\u3057\u3001 <b>at<\/b>\u3092\u4f7f\u7528\u3057\u3066\u30a4\u30f3\u30c7\u30c3\u30af\u30b9\u5024 0 \u304b\u3089 4 \u307e\u3067\u306e\u884c\u3001\u304a\u3088\u3073\u30dd\u30a4\u30f3\u30c8\u5217\u3068\u30a2\u30b7\u30b9\u30c8\u5217\u306b\u30a2\u30af\u30bb\u30b9\u3057\u3088\u3046\u3068\u3059\u308b\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#try to select rows between index values 0 and 4 and columns 'points' and 'assists'\n<span style=\"color: #000000;\">df. <span style=\"color: #3366ff;\">at<\/span> [0:4, [' <span style=\"color: #ff0000;\">points<\/span> ', ' <span style=\"color: #ff0000;\">assists<\/span> ']]<\/span>\n\n<span style=\"color: #000000;\"><span style=\"color: #ff0000;\">TypeError<\/span> : unhashable type: 'list'\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>at<\/strong>\u95a2\u6570\u306f\u5165\u529b\u5f15\u6570\u3068\u3057\u3066\u8907\u6570\u306e\u884c\u307e\u305f\u306f\u8907\u6570\u306e\u5217\u3092\u53d7\u3051\u53d6\u308b\u3053\u3068\u304c\u3067\u304d\u306a\u3044\u305f\u3081\u3001\u30a8\u30e9\u30fc\u304c\u767a\u751f\u3057\u307e\u3059\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong><span style=\"color: #000000;\">\u7d50\u8ad6<\/span><\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">pandas DataFrame \u5185\u306e\u5358\u4e00\u306e\u5024\u306b\u30a2\u30af\u30bb\u30b9\u3059\u308b\u5834\u5408\u3001 <strong>loc<\/strong>\u95a2\u6570\u3068<strong>at<\/strong>\u95a2\u6570\u306f\u6b63\u5e38\u306b\u6a5f\u80fd\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u305f\u3060\u3057\u3001\u884c\u3068\u5217\u306e\u30b0\u30eb\u30fc\u30d7\u306b\u30a2\u30af\u30bb\u30b9\u3059\u308b\u5834\u5408\u306f\u3001 <strong>loc<\/strong>\u95a2\u6570\u306e\u307f\u304c\u30a2\u30af\u30bb\u30b9\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u95a2\u9023:<\/strong> <a href=\"https:\/\/statorials.org\/ja\/\u30cf\u309a\u30f3\u30bf\u3099-loc-\u5bfe-iloc\/\" target=\"_blank\" rel=\"noopener\">Pandas loc \u3068 iloc: \u9055\u3044\u306f\u4f55\u3067\u3059\u304b?<\/a><\/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\u30d1\u30f3\u30c0\u3067\u4ed6\u306e\u4e00\u822c\u7684\u306a\u64cd\u4f5c\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u3092\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ja\/\u30cf\u309a\u30f3\u30bf\u3099\u306f\u8907\u6570\u306e\u6761\u4ef6\u3092\u898b\u3064\u3051\u307e\u3059\/\" target=\"_blank\" rel=\"noopener\">Pandas Loc \u3092\u4f7f\u7528\u3057\u3066\u8907\u6570\u306e\u6761\u4ef6\u306b\u57fa\u3065\u3044\u3066\u884c\u3092\u9078\u629e\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u30cf\u309a\u30f3\u30bf\u3099\u306f\u5217\u306e\u5024\u306b\u57fa\u3064\u3099\u3044\u3066\u884c\u3092\u9078\u629e\u3057\u307e\u3059\/\">Pandas\u3067\u5217\u306e\u5024\u306b\u57fa\u3065\u3044\u3066\u884c\u3092\u9078\u629e\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u30cf\u309a\u30f3\u30bf\u3099\u306f\u30a4\u30f3\u30c6\u3099\u30c3\u30af\u30b9\u306b\u3088\u3063\u3066\u884c\u3092\u9078\u629e\u3057\u307e\u3059\/\" target=\"_blank\" rel=\"noopener\">Pandas \u3067\u30a4\u30f3\u30c7\u30c3\u30af\u30b9\u306b\u3088\u3063\u3066\u884c\u3092\u9078\u629e\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>pandas DataFrame \u306e\u884c\u3068\u5217\u3092\u9078\u629e\u3059\u308b\u5834\u5408\u3001 .loc\u3068.at\u306e 2 \u3064\u306e\u95a2\u6570\u304c\u3088\u304f\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002 2 \u3064\u306e\u95a2\u6570\u306e\u5fae\u5999\u306a\u9055\u3044\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002 .loc \u306f\u5165\u529b\u5f15\u6570\u3068\u3057\u3066\u8907\u6570\u306e\u884c\u3068\u5217\u3092\u53d6\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059 . 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