{"id":3766,"date":"2023-07-15T15:55:47","date_gmt":"2023-07-15T15:55:47","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%ae%e9%8e%96%e3%81%ae%e4%b8%8b%e3%81%a6%e3%82%99\/"},"modified":"2023-07-15T15:55:47","modified_gmt":"2023-07-15T15:55:47","slug":"%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%ae%e9%8e%96%e3%81%ae%e4%b8%8b%e3%81%a6%e3%82%99","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%e9%8e%96%e3%81%ae%e4%b8%8b%e3%81%a6%e3%82%99\/","title":{"rendered":"Pandas: \u5217\u5168\u4f53\u306e\u90e8\u5206\u6587\u5b57\u5217\u3092\u53d6\u5f97\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"

<\/p>\n

\n

\u6b21\u306e\u57fa\u672c\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u306e\u5217\u5168\u4f53\u306e\u90e8\u5206\u6587\u5b57\u5217\u3092\u53d6\u5f97\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n

 df[' some_substring<\/span> '] = df[' string_column<\/span> ']. str<\/span> [1:4]\n<\/strong><\/pre>\n
\u3053\u306e\u7279\u5b9a\u306e\u4f8b\u3067\u306f\u3001 string_column<\/strong>\u306e\u4f4d\u7f6e 1 \uff5e 4 \u306e\u6587\u5b57\u3092\u542b\u3080some_substring<\/strong>\u3068\u3044\u3046\u65b0\u3057\u3044\u5217\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002<\/span><\/span><\/p>\n
\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
\u4f8b: Pandas \u306e\u5217\u5168\u4f53\u306e\u90e8\u5206\u6587\u5b57\u5217\u3092\u53d6\u5f97\u3059\u308b<\/strong><\/span><\/h2>\n
\u3055\u307e\u3056\u307e\u306a\u30d0\u30b9\u30b1\u30c3\u30c8\u30dc\u30fc\u30eb \u30c1\u30fc\u30e0\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
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['Mavericks', 'Warriors', 'Rockets', 'Hornets', 'Lakers'],\n                   ' points<\/span> ': [120, 132, 108, 118, 106]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n        team points\n0 Mavericks 120\n1 Warriors 132\n2 Rockets 108\n3 Hornets 118\n4 Lakers 106<\/strong><\/span><\/pre>\n
\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001\u30c1\u30fc\u30e0<\/strong>\u5217\u306e 1 \u4f4d\u304b\u3089 4 \u4f4d\u307e\u3067\u306e\u6587\u5b57\u3092\u542b\u3080\u65b0\u3057\u3044\u5217\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
 #create column that extracts characters in positions 1 through 4 in team column\n<\/span>df[' team_substring<\/span> '] = df[' team<\/span> ']. str<\/span> [1:4]\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n        team points team_substring\n0 Mavericks 120 ave\n1 Warriors 132 arr\n2 Rockets 108 ock\n3 Hornets 118 orn\n4 Lakers 106 ake\n<\/span><\/span><\/strong><\/pre>\n
 Team_substring<\/strong>\u3068\u3044\u3046\u65b0\u3057\u3044\u5217\u306b\u306f\u3001\u30c1\u30fc\u30e0\u5217\u306e\u4f4d\u7f6e 1 \u304b\u3089 4 \u307e\u3067\u306e\u6587\u5b57\u304c\u542b\u307e\u308c\u307e\u3059\u3002<\/span><\/p>\n
\u3053\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u6570\u5024\u5217\u304b\u3089\u90e8\u5206\u6587\u5b57\u5217\u3092\u62bd\u51fa\u3057\u3088\u3046\u3068\u3059\u308b\u3068\u3001\u30a8\u30e9\u30fc\u304c\u767a\u751f\u3059\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n
 #attempt to extract characters in positions 0 through 2 in points column\n<\/span>df[' points_substring<\/span> '] = df[' points<\/span> ']. str<\/span> [:2]\n\nAttributeError: Can only use .str accessor with string values!\n<\/span><\/span><\/strong><\/pre>\n
\u4ee3\u308f\u308a\u306b\u3001\u6700\u521d\u306bastype(str)<\/strong>\u3092\u4f7f\u7528\u3057\u3066\u6570\u5024\u5217\u3092\u6587\u5b57\u5217\u306b\u5909\u63db\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n
 #extract characters in positions 0 through 2 in points column\n<\/span>df[' points_substring<\/span> '] = df[' points<\/span> ']. astype<\/span> (str). str<\/span> [:2]\n\n#view updated DataFrame<\/span>\nprint<\/span> (df)\n\n        team points points_substring\n0 Mavericks 120 12\n1 Warriors 132 13\n2 Rockets 108 10\n3 Hornets 118 11\n4 Lakers 106 10<\/span><\/span><\/strong><\/pre>\n
\u4eca\u56de\u306f\u3001\u6700\u521d\u306b\u6587\u5b57\u5217\u306b\u5909\u63db\u3057\u305f\u305f\u3081\u3001\u30c9\u30c3\u30c8<\/strong>\u5217\u306e\u4f4d\u7f6e 0 \uff5e 2 \u306e\u6587\u5b57\u3092\u6b63\u5e38\u306b\u62bd\u51fa\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\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\u30bf\u30b9\u30af\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u3092\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n
 \u30d1\u30f3\u30c0: \u6587\u5b57\u5217\u306b\u8907\u6570\u306e\u90e8\u5206\u6587\u5b57\u5217\u304c\u542b\u307e\u308c\u3066\u3044\u308b\u304b\u3069\u3046\u304b\u3092\u78ba\u8a8d\u3057\u307e\u3059<\/a>
Pandas: \u5217\u306e\u5404\u5024\u306b\u6587\u5b57\u5217\u3092\u8ffd\u52a0\u3059\u308b\u65b9\u6cd5<\/a>
\u30d1\u30f3\u30c0: \u7279\u5b9a\u306e\u6587\u5b57\u5217\u3092\u542b\u3080\u5217\u3092\u9078\u629e\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u6b21\u306e\u57fa\u672c\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u306e\u5217\u5168\u4f53\u306e\u90e8\u5206\u6587\u5b57\u5217\u3092\u53d6\u5f97\u3067\u304d\u307e\u3059\u3002 df[‘ some_substring ‘] = df[‘ string_column ‘]. str [1:4] \u3053\u306e\u7279\u5b9a […]<\/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-3766","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"\n\u30d1\u30f3\u30c0: \u5217\u5168\u4f53\u306e\u90e8\u5206\u6587\u5b57\u5217\u3092\u53d6\u5f97\u3059\u308b\u65b9\u6cd5 \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001pandas DataFrame 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\u306e\u5217\u5168\u4f53\u306e\u90e8\u5206\u6587\u5b57\u5217\u3092\u53d6\u5f97\u3059\u308b\u65b9\u6cd5\u3092\u3044\u304f\u3064\u304b\u306e\u4f8b\u3068\u3068\u3082\u306b\u8aac\u660e\u3057\u307e\u3059\u3002\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ja\/\u30cf\u309a\u30f3\u30bf\u3099\u306e\u9396\u306e\u4e0b\u3066\u3099\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-15T15:55:47+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\" 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Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/ja\/#website\"},\"datePublished\":\"2023-07-15T15:55:47+00:00\",\"dateModified\":\"2023-07-15T15:55:47+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/ja\/#\/schema\/person\/86b92d2dd87368b26360d19d9c6a5d83\"},\"description\":\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001pandas DataFrame 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