{"id":982,"date":"2023-07-28T02:29:34","date_gmt":"2023-07-28T02:29:34","guid":{"rendered":"https:\/\/statorials.org\/ja\/pandas-groupby%e3%81%af%e8%a4%87%e6%95%b0%e3%81%ae%e5%88%97%e3%82%92%e9%9b%86%e8%a8%88%e3%81%97%e3%81%be%e3%81%99\/"},"modified":"2023-07-28T02:29:34","modified_gmt":"2023-07-28T02:29:34","slug":"pandas-groupby%e3%81%af%e8%a4%87%e6%95%b0%e3%81%ae%e5%88%97%e3%82%92%e9%9b%86%e8%a8%88%e3%81%97%e3%81%be%e3%81%99","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/pandas-groupby%e3%81%af%e8%a4%87%e6%95%b0%e3%81%ae%e5%88%97%e3%82%92%e9%9b%86%e8%a8%88%e3%81%97%e3%81%be%e3%81%99\/","title":{"rendered":"\u30d1\u30f3\u30c0: \u8907\u6570\u306e\u5217\u3092\u30b0\u30eb\u30fc\u30d7\u5316\u3057\u3066\u96c6\u8a08\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u591a\u304f\u306e\u5834\u5408\u3001pandas DataFrame \u306e\u8907\u6570\u306e\u5217\u3092\u30b0\u30eb\u30fc\u30d7\u5316\u3057\u3066\u96c6\u7d04\u3059\u308b\u3053\u3068\u304c\u5fc5\u8981\u306a\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5e78\u3044\u306a\u3053\u3068\u306b\u3001\u3053\u308c\u306f pandas \u306e<a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.DataFrame.groupby.html\" target=\"_blank\" rel=\"noopener noreferrer\">.groupby()<\/a>\u95a2\u6570\u3068<a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.DataFrame.agg.html\" target=\"_blank\" rel=\"noopener noreferrer\">.agg()<\/a>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u7c21\u5358\u306b\u5b9f\u884c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001\u3053\u308c\u3089\u306e\u6a5f\u80fd\u306e\u5b9f\u969b\u306e\u4f7f\u7528\u4f8b\u3092\u3044\u304f\u3064\u304b\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u4f8b 1: 2 \u3064\u306e\u5217\u3067\u30b0\u30eb\u30fc\u30d7\u5316\u3057\u3001\u5e73\u5747\u3092\u6c42\u3081\u308b<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\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: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame<\/span>\ndf = pd.DataFrame({'team': ['A', 'B', 'B', 'B', 'B', 'M', 'M', 'M'],\n                   'position': ['G', 'G', 'F', 'G', 'F', 'F', 'C', 'C'],\n                   'assists': [5, 7, 7, 8, 5, 7, 6, 9],\n                   'rebounds': [11, 8, 10, 6, 6, 9, 6, 10]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #993300;\">print<\/span> (df)\n\n  team position assists rebounds\n0 AG 5 11\n1 BG 7 8\n2 BF 7 10\n3 BG 8 6\n4 BF 5 6\n5 MF 7 9\n6 MC 6 6\n7 MC 9 10\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u300c\u30c1\u30fc\u30e0\u300d\u5217\u3068\u300c\u30dd\u30b8\u30b7\u30e7\u30f3\u300d\u5217\u3067\u30b0\u30eb\u30fc\u30d7\u5316\u3057\u3001\u5e73\u5747\u30d1\u30b9\u3092\u898b\u3064\u3051\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">groupby<\/span> (['team', 'position']). <span style=\"color: #3366ff;\">agg<\/span> ({'assists': ['mean']}). <span style=\"color: #3366ff;\">reset_index<\/span> ()\n\n\n        team position assists\n                          mean\n0 A G 5.0\n1 B F 6.0\n2 B G 7.5\n3 M C 7.5\n4M F 7.0\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u51fa\u529b\u304b\u3089\u306f\u6b21\u306e\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u30c1\u30fc\u30e0 A \u306e\u30dd\u30b8\u30b7\u30e7\u30f3 G \u306e\u9078\u624b\u306e\u5e73\u5747\u30a2\u30b7\u30b9\u30c8\u306f<strong>5.0<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u30c1\u30fc\u30e0 B \u306e\u30dd\u30b8\u30b7\u30e7\u30f3 F \u306e\u9078\u624b\u306e\u5e73\u5747\u30a2\u30b7\u30b9\u30c8\u306f<strong>6.0<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u30c1\u30fc\u30e0 B \u306e\u30dd\u30b8\u30b7\u30e7\u30f3 G \u306e\u9078\u624b\u306e\u5e73\u5747\u30a2\u30b7\u30b9\u30c8\u6570\u306f<strong>7.5<\/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\u7d50\u679c\u306e DataFrame \u306e\u5217\u306e\u540d\u524d\u3092\u5909\u66f4\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#group by team and position and find mean assists<\/span>\nnew = df. <span style=\"color: #3366ff;\">groupby<\/span> (['team', 'position']). <span style=\"color: #3366ff;\">agg<\/span> ({'assists': ['mean']}). <span style=\"color: #3366ff;\">reset_index<\/span> ()\n\n<span style=\"color: #008080;\">#rename columns<\/span>\nnew.columns = ['team', 'pos', 'mean_assists']\n\n<span style=\"color: #008080;\">#view DataFrame<\/span>\n<span style=\"color: #993300;\">print<\/span> (new)\n\n\tteam pos mean_assists\n0 A G 5.0\n1 B F 6.0\n2 B G 7.5\n3 M C 7.5\n4M F 7.0<\/strong><\/pre>\n<h3><span style=\"color: #000000;\"><strong>\u4f8b 2: 2 \u3064\u306e\u5217\u3067\u30b0\u30eb\u30fc\u30d7\u5316\u3057\u3001\u8907\u6570\u306e\u7d71\u8a08\u3092\u691c\u7d22\u3057\u307e\u3059\u3002<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u524d\u306e\u4f8b\u3068\u540c\u3058 pandas DataFrame \u3092\u4f7f\u7528\u3057\u3066\u3044\u308b\u3068\u4eee\u5b9a\u3057\u307e\u3057\u3087\u3046\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame<\/span>\ndf = pd.DataFrame({'team': ['A', 'B', 'B', 'B', 'B', 'M', 'M', 'M'],\n                   'position': ['G', 'G', 'F', 'G', 'F', 'F', 'C', 'C'],\n                   'assists': [5, 7, 7, 8, 5, 7, 6, 9],\n                   'rebounds': [11, 8, 10, 6, 6, 9, 6, 10]})<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u300c\u30c1\u30fc\u30e0\u300d\u5217\u3068\u300c\u30dd\u30b8\u30b7\u30e7\u30f3\u300d\u5217\u306b\u30b0\u30eb\u30fc\u30d7\u5316\u3055\u308c\u305f\u30ea\u30d0\u30a6\u30f3\u30c9\u6570\u306e\u4e2d\u592e\u5024\u3068\u6700\u5927\u6570\u3092\u898b\u3064\u3051\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">groupby<\/span> (['team', 'position']). <span style=\"color: #3366ff;\">agg<\/span> ({'rebounds': ['median', 'max']}). <span style=\"color: #3366ff;\">reset_index<\/span> ()\n\n\n        team position rebounds\n                         median max\n0 A G 11 11\n1 B F 8 10\n2 B G 7 8\n3 M C 8 10\n4 M F 9 9\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u51fa\u529b\u304b\u3089\u306f\u6b21\u306e\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u30c1\u30fc\u30e0 A \u306e G \u30dd\u30b8\u30b7\u30e7\u30f3\u306e\u9078\u624b\u306e\u30ea\u30d0\u30a6\u30f3\u30c9\u306e\u4e2d\u592e\u5024\u306f<strong>11<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u30c1\u30fc\u30e0 A \u306e\u30dd\u30b8\u30b7\u30e7\u30f3 G \u306e\u30d7\u30ec\u30fc\u30e4\u30fc\u306e\u6700\u5927\u30ea\u30d0\u30a6\u30f3\u30c9\u306f<strong>11<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u30c1\u30fc\u30e0 B \u306e\u30dd\u30b8\u30b7\u30e7\u30f3 F \u306e\u9078\u624b\u306e\u30ea\u30d0\u30a6\u30f3\u30c9\u306e\u4e2d\u592e\u5024\u306f<strong>8<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u30c1\u30fc\u30e0 B \u306e\u30dd\u30b8\u30b7\u30e7\u30f3 F \u306e\u30d7\u30ec\u30fc\u30e4\u30fc\u306e\u6700\u5927\u30ea\u30d0\u30a6\u30f3\u30c9\u306f<strong>10<\/strong>\u3067\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u7b49\u3005\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h3>\n<p><a href=\"https:\/\/statorials.org\/ja\/\u30cf\u309a\u30f3\u30bf\u3099\u306f\u8907\u6570\u306e\u6761\u4ef6\u3092\u30d5\u30a3\u30eb\u30bf\u30fc\u3057\u307e\u3059\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u8907\u6570\u306e\u6761\u4ef6\u3067 Pandas DataFrame \u3092\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u30cf\u309a\u30f3\u30bf\u3099\u306f\u6b20\u640d\u5024\u3092\u6570\u3048\u307e\u3059\/\" target=\"_blank\" rel=\"noopener noreferrer\">Pandas DataFrame \u306e\u6b20\u640d\u5024\u3092\u6570\u3048\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u30cf\u309a\u30f3\u30bf\u3099\u30c6\u3099\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u3092\u30b9\u30bf\u30c3\u30af\u3059\u308b\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u8907\u6570\u306e Pandas DataFrame \u3092\u30b9\u30bf\u30c3\u30af\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u591a\u304f\u306e\u5834\u5408\u3001pandas DataFrame \u306e\u8907\u6570\u306e\u5217\u3092\u30b0\u30eb\u30fc\u30d7\u5316\u3057\u3066\u96c6\u7d04\u3059\u308b\u3053\u3068\u304c\u5fc5\u8981\u306a\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002 \u5e78\u3044\u306a\u3053\u3068\u306b\u3001\u3053\u308c\u306f pandas \u306e.groupby()\u95a2\u6570\u3068.agg()\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u7c21\u5358\u306b\u5b9f\u884c\u3067\u304d\u307e\u3059\u3002 [&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-982","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - 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