{"id":2969,"date":"2023-07-19T20:17:56","date_gmt":"2023-07-19T20:17:56","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%ae%e5%88%97%e3%82%92%e4%ba%a4%e6%8f%9b%e3%81%99%e3%82%8b\/"},"modified":"2023-07-19T20:17:56","modified_gmt":"2023-07-19T20:17:56","slug":"%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%ae%e5%88%97%e3%82%92%e4%ba%a4%e6%8f%9b%e3%81%99%e3%82%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%ae%e5%88%97%e3%82%92%e4%ba%a4%e6%8f%9b%e3%81%99%e3%82%8b\/","title":{"rendered":"Pandas \u3067 2 \u3064\u306e\u5217\u3092\u5165\u308c\u66ff\u3048\u308b\u65b9\u6cd5 (\u4f8b\u3042\u308a)"},"content":{"rendered":"

<\/p>\n

\n

\u6b21\u306e\u30ab\u30b9\u30bf\u30e0\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u5185\u306e 2 \u3064\u306e\u5217\u306e\u4f4d\u7f6e\u3092\u4ea4\u63db\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n

 def<\/span> swap_columns<\/span> (df, col1, col2):\n    col_list = list<\/span> ( df.columns<\/span> )\n    x, y = col_list. index<\/span> (col1), col_list. index<\/span> (col2)\n    col_list[y], col_list[x] = col_list[x], col_list[y]\n    df = df[col_list]\n    return<\/span> df\n<\/strong><\/pre>\n
\u3053\u306e\u95a2\u6570\u306f\u3001DataFrame \u5185\u306e\u5217col1<\/strong>\u3068col2<\/strong>\u306e\u4f4d\u7f6e\u3092\u4ea4\u63db\u3057\u307e\u3059\u3002<\/span><\/p>\n
\u6b21\u306e\u4f8b\u306f\u3001\u3053\u306e\u95a2\u6570\u3092\u5b9f\u969b\u306b\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n
\u4f8b: Pandas \u306e 2 \u3064\u306e\u5217\u3092\u4ea4\u63db\u3059\u308b<\/strong><\/span><\/h3>\n
\u6b21\u306e\u30d1\u30f3\u30c0 \u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u304c\u3042\u308b\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],\n                   ' points<\/span> ': [18, 22, 19, 14, 14, 11, 20, 28],\n                   ' assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' rebounds<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})\n\n#view DataFrame\n<\/span>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<\/span><\/span><\/strong><\/pre>\n
 swap_columns()<\/strong>\u95a2\u6570\u3092\u5b9a\u7fa9\u3057\u3066\u3001\u300c\u30dd\u30a4\u30f3\u30c8\u300d\u5217\u3068\u300c\u30d0\u30a6\u30f3\u30b9\u300d\u5217\u306e\u4f4d\u7f6e\u3092\u4ea4\u63db\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
 #define function to swap columns<\/span>\ndef<\/span> swap_columns<\/span> (df, col1, col2):\n    col_list = list<\/span> ( df.columns<\/span> )\n    x, y = col_list. index<\/span> (col1), col_list. index<\/span> (col2)\n    col_list[y], col_list[x] = col_list[x], col_list[y]\n    df = df[col_list]\n    return<\/span> df\n\n#swap points and rebounds columns\n<\/span>df = swap_columns<\/span> (df, ' points<\/span> ', ' rebounds<\/span> '):\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n  team rebounds assists points\n0 A 11 5 18\n1 B 8 7 22\n2 C 10 7 19\n3 D 6 9 14\n4 E 6 12 14\n5 F 5 9 11\n6 G 9 9 20\n7:12 a.m. 4:28\n<\/strong><\/pre>\n
 \u300c\u30dd\u30a4\u30f3\u30c8\u300d\u5217\u3068\u300c\u30ea\u30d0\u30a6\u30f3\u30c9\u300d\u5217\u304c\u4ea4\u63db\u3055\u308c\u3001\u4ed6\u306e\u3059\u3079\u3066\u306e\u5217\u306f\u540c\u3058\u4f4d\u7f6e\u306b\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/span><\/p>\n
\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h3>\n
\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
 \u30d1\u30f3\u30c0: \u5217\u5185\u306e\u7279\u5b9a\u306e\u5024\u306e\u51fa\u73fe\u3092\u6570\u3048\u308b\u65b9\u6cd5<\/a>
Pandas: \u5217\u304c\u5024\u3068\u4e00\u81f4\u3059\u308b\u884c\u306e\u30a4\u30f3\u30c7\u30c3\u30af\u30b9\u3092\u53d6\u5f97\u3057\u307e\u3059<\/a>
\u30d1\u30f3\u30c0: DataFrame \u306e\u6b20\u640d\u5024\u3092\u6570\u3048\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u6b21\u306e\u30ab\u30b9\u30bf\u30e0\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u5185\u306e 2 \u3064\u306e\u5217\u306e\u4f4d\u7f6e\u3092\u4ea4\u63db\u3067\u304d\u307e\u3059\u3002 def swap_columns (df, col1, col2): col_list = list ( df.col […]<\/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-2969","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"\nPandas \u3067 2 \u3064\u306e\u5217\u3092\u5165\u308c\u66ff\u3048\u308b\u65b9\u6cd5 (\u4f8b\u4ed8\u304d) \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001pandas DataFrame \u306e 2 \u3064\u306e\u5217\u3092\u4ea4\u63db\u3059\u308b\u65b9\u6cd5\u3092\u4f8b\u3092\u793a\u3057\u3066\u8aac\u660e\u3057\u307e\u3059\u3002\" \/>\n<meta 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content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-19T20:17:56+00:00\" \/>\n<meta name=\"author\" content=\"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u57f7\u7b46\u8005\" \/>\n\t<meta name=\"twitter:data1\" content=\"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u63a8\u5b9a\u8aad\u307f\u53d6\u308a\u6642\u9593\" \/>\n\t<meta name=\"twitter:data2\" content=\"1\u5206\" \/>\n<script type=\"application\/ld+json\" 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