{"id":3536,"date":"2023-07-16T23:01:05","date_gmt":"2023-07-16T23:01:05","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e8%b3%9e\/"},"modified":"2023-07-16T23:01:05","modified_gmt":"2023-07-16T23:01:05","slug":"%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e8%b3%9e","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e8%b3%9e\/","title":{"rendered":"Pandas \u3067 assign() \u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5 (\u4f8b\u4ed8\u304d)"},"content":{"rendered":"

<\/p>\n

\n

assign()<\/strong>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u306b\u65b0\u3057\u3044\u5217\u3092\u8ffd\u52a0\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n

\u3053\u306e\u30e1\u30bd\u30c3\u30c9\u3067\u306f\u3001\u6b21\u306e\u57fa\u672c\u69cb\u6587\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/span><\/p>\n

 df. assign<\/span> (new_column = values)\n<\/strong><\/pre>\n
\u3053\u306e\u30e1\u30bd\u30c3\u30c9\u306f\u30b3\u30f3\u30bd\u30fc\u30eb\u306b\u65b0\u3057\u3044 DataFrame \u3092\u8868\u793a\u3059\u308b\u3060\u3051\u3067\u3001\u5b9f\u969b\u306b\u306f\u5143\u306e DataFrame \u3092\u5909\u66f4\u3057\u306a\u3044\u3053\u3068\u306b\u6ce8\u610f\u3059\u308b\u3053\u3068\u304c\u91cd\u8981\u3067\u3059\u3002<\/span><\/p>\n
\u5143\u306e DataFrame \u3092\u5909\u66f4\u3059\u308b\u306b\u306f\u3001 assign()<\/strong>\u30e1\u30bd\u30c3\u30c9\u306e\u7d50\u679c\u3092\u65b0\u3057\u3044\u5909\u6570\u306b\u4fdd\u5b58\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n
\u6b21\u306e\u4f8b\u306f\u3001\u6b21\u306e pandas DataFrame \u3067\u3055\u307e\u3056\u307e\u306a\u65b9\u6cd5\u3067assign()<\/strong>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#define DataFrame\ndf = pd. DataFrame<\/span> ({' points<\/span> ': [25, 12, 15, 14, 19, 23, 25, 29],\n                   ' assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' rebounds<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})<\/span>\n\n#view DataFrame<\/span>\nprint<\/span> (df)\n\n   points assists rebounds\n0 25 5 11\n1 12 7 8\n2 15 7 10\n3 14 9 6\n4 19 12 6\n5 23 9 5\n6 25 9 9\n7 29 4 12<\/strong><\/pre>\n
\u4f8b 1: \u65b0\u3057\u3044\u5909\u6570\u3092 DataFrame \u306b\u5272\u308a\u5f53\u3066\u308b<\/strong><\/span><\/h2>\n
\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001 assign()<\/strong>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u3001 points<\/strong>\u5217\u306e\u5024\u3092 2 \u500d\u3057\u305f\u5024\u306b\u7b49\u3057\u3044point2 \u3068\u3044\u3046<\/strong>\u65b0\u3057\u3044\u5909\u6570\u3092 DataFrame \u306b\u8ffd\u52a0\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n
 #add new variable called points2\ndf. assign<\/span> (points2 = df.points<\/span> * 2<\/span> )<\/span>\n\n    points<\/span> assists rebounds<\/span> points2\n0 25<\/span> 5<\/span> 11 50\n1 12<\/span> 7<\/span> 8 24\n2 15<\/span> 7<\/span> 10 30\n3 14<\/span> 9<\/span> 6 28\n4 19<\/span> 12<\/span> 6<\/span> 38\n5 23<\/span> 9<\/span> 5 46\n6 25<\/span> 9<\/span> 9 50\n7 29<\/span> 4<\/span> 12 58\n<\/span><\/span><\/strong><\/pre>\n
\u3053\u306eassign()<\/strong>\u30e1\u30bd\u30c3\u30c9\u306f\u5143\u306e DataFrame \u3092\u5909\u66f4\u3057\u306a\u3044\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/span><\/p>\n
\u5143\u306e DataFrame \u3092\u5370\u5237\u3059\u308b\u3068\u3001\u5909\u66f4\u3055\u308c\u3066\u3044\u306a\u3044\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n
 #print original DataFrame<\/span>\nprint<\/span> (df)\n\n   points assists rebounds\n0 25 5 11\n1 12 7 8\n2 15 7 10\n3 14 9 6\n4 19 12 6\n5 23 9 5\n6 25 9 9\n7 29 4 12\n<\/strong><\/pre>\n
 assign()<\/strong>\u30e1\u30bd\u30c3\u30c9\u306e\u7d50\u679c\u3092\u4fdd\u5b58\u3059\u308b\u306b\u306f\u3001\u7d50\u679c\u3092\u65b0\u3057\u3044 DataFrame \u306b\u4fdd\u5b58\u3057\u307e\u3059\u3002<\/span><\/p>\n
 #add new variable called points2 and save results in new DataFrame\ndf. assign<\/span> (points2 = df.points<\/span> * 2<\/span> )\n\n#view new DataFrame<\/span>\nprint<\/span> (df_new)\n\n   points assists rebounds points2\n0 25 5 11 50\n1 12 7 8 24\n2 15 7 10 30\n3 14 9 6 28\n4 19 12 6 38\n5 23 9 5 46\n6 25 9 9 50\n7 29 4 12 58\n<\/span><\/span><\/strong><\/pre>\n
 df_new<\/strong>\u3068\u3044\u3046\u65b0\u3057\u3044\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306b\u306f\u3001\u4f5c\u6210\u3057\u305fPoints2<\/strong>\u5217\u304c\u542b\u307e\u308c\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n
\u4f8b 2: \u8907\u6570\u306e\u65b0\u3057\u3044\u5909\u6570\u3092 DataFrame \u306b\u5272\u308a\u5f53\u3066\u308b<\/strong><\/span><\/h2>\n
\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001 assign()<\/strong>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066 3 \u3064\u306e\u65b0\u3057\u3044\u5909\u6570\u3092 DataFrame \u306b\u8ffd\u52a0\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n
 #add three new variables to DataFrame and store results in new DataFrame<\/span>\ndf_new = df. assign<\/span> (points2 = df. points<\/span> * 2<\/span> ,\n                   assists_rebs = df. assists<\/span> + df. rebounds<\/span> ,\n                   conference = ' Western<\/span> ')\n\n#view new DataFrame\n<\/span>print<\/span> (df_new)\n\n   points assists rebounds points2 assists_rebs conference\n0 25 5 11 50 16 Western\n1 12 7 8 24 15 Western\n2 15 7 10 30 17 Western\n3 14 9 6 28 15 Western\n4 19 12 6 38 18 Western\n5 23 9 5 46 14 Western\n6 25 9 9 50 18 Western\n7 29 4 12 58 16 Western\n<\/strong><\/pre>\n
 3 \u3064\u306e\u65b0\u3057\u3044\u5217\u304c DataFrame \u306b\u8ffd\u52a0\u3055\u308c\u305f\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n
\u6ce8<\/strong>: pandas assign()<\/strong>\u30e1\u30bd\u30c3\u30c9\u306e\u5b8c\u5168\u306a\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u306f\u3053\u3053\u3067<\/a>\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h2>\n
\u6b21\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001\u30d1\u30f3\u30c0\u3067\u4ed6\u306e\u4e00\u822c\u7684\u306a\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3092\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n
 Pandas\u3067describe()\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5<\/a>
Pandas \u3067 idxmax() \u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5<\/a>
Pandas \u3067\u9078\u629e\u3057\u305f\u5217\u306b\u95a2\u6570\u3092\u9069\u7528\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
assign()\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u306b\u65b0\u3057\u3044\u5217\u3092\u8ffd\u52a0\u3067\u304d\u307e\u3059\u3002 \u3053\u306e\u30e1\u30bd\u30c3\u30c9\u3067\u306f\u3001\u6b21\u306e\u57fa\u672c\u69cb\u6587\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002 df. assign (new_column = values) \u3053\u306e\u30e1\u30bd\u30c3 […]<\/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-3536","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"\nPandas \u3067 assign() \u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5 (\u4f8b\u4ed8\u304d) \u2013 Statology<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001\u30d1\u30f3\u30c0\u3067 assign() \u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3092\u3044\u304f\u3064\u304b\u306e\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 rel=\"canonical\" href=\"https:\/\/statorials.org\/ja\/\u30cf\u309a\u30f3\u30bf\u3099\u8cde\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas \u3067 assign() \u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5 (\u4f8b\u4ed8\u304d) \u2013 Statology\" \/>\n<meta property=\"og:description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001\u30d1\u30f3\u30c0\u3067 assign() \u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3092\u3044\u304f\u3064\u304b\u306e\u4f8b\u3068\u3068\u3082\u306b\u8aac\u660e\u3057\u307e\u3059\u3002\" 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