{"id":3854,"date":"2023-07-15T03:28:54","date_gmt":"2023-07-15T03:28:54","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%af%e5%ab%8c%e3%81%84%e3%81%97%e3%82%99%e3%82%83%e3%81%aa%e3%81%84\/"},"modified":"2023-07-15T03:28:54","modified_gmt":"2023-07-15T03:28:54","slug":"%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%af%e5%ab%8c%e3%81%84%e3%81%97%e3%82%99%e3%82%83%e3%81%aa%e3%81%84","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%af%e5%ab%8c%e3%81%84%e3%81%97%e3%82%99%e3%82%83%e3%81%aa%e3%81%84\/","title":{"rendered":"\u300cnull\u3067\u306f\u306a\u3044\u300d\u306e\u4f7f\u3044\u65b9\u306f\uff1f\u30d1\u30f3\u30c0\u3067 (\u4f8b\u4ed8\u304d)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">pandas <strong>notnull()<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001pandas DataFrame \u306e\u8981\u7d20\u304c null \u304b\u3069\u3046\u304b\u3092\u30c6\u30b9\u30c8\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u8981\u7d20\u304c NaN \u307e\u305f\u306f None \u306b\u7b49\u3057\u3044\u5834\u5408\u3001\u95a2\u6570\u306f<strong>False<\/strong>\u3092\u8fd4\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u305d\u308c\u4ee5\u5916\u306e\u5834\u5408\u3001\u95a2\u6570\u306f<strong>True<\/strong>\u3092\u8fd4\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u95a2\u6570\u3092\u5b9f\u969b\u306b\u4f7f\u7528\u3059\u308b\u4e00\u822c\u7684\u306a\u65b9\u6cd5\u3092\u3044\u304f\u3064\u304b\u793a\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u65b9\u6cd5 1: \u3069\u306e\u5217\u306b\u3082 null \u5024\u3092\u542b\u307e\u306a\u3044\u884c\u3092\u30d5\u30a3\u30eb\u30bf\u30fc\u3059\u308b<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df[df. <span style=\"color: #3366ff;\">notnull<\/span> (). <span style=\"color: #3366ff;\">all<\/span> ( <span style=\"color: #008000;\">1<\/span> )]\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\"><strong>\u65b9\u6cd5 2: \u7279\u5b9a\u306e\u5217\u306b null \u5024\u3092\u542b\u307e\u306a\u3044\u884c\u3092\u30d5\u30a3\u30eb\u30bf\u30fc\u3059\u308b<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df[df[[' <span style=\"color: #ff0000;\">this_column<\/span> ']]. <span style=\"color: #3366ff;\">notnull<\/span> (). <span style=\"color: #3366ff;\">all<\/span> ( <span style=\"color: #008000;\">1<\/span> )]<\/strong><\/pre>\n<p><span style=\"color: #000000;\"><strong>\u65b9\u6cd5 3: \u5404\u5217\u306e\u30bc\u30ed\u4ee5\u5916\u306e\u5024\u306e\u6570\u3092\u6570\u3048\u308b<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">notnull<\/span> (). <span style=\"color: #3366ff;\">sum<\/span> ()<\/strong><\/pre>\n<p><span style=\"color: #000000;\"><strong>\u65b9\u6cd5 4: DataFrame \u5168\u4f53\u5185\u306e\u30bc\u30ed\u4ee5\u5916\u306e\u5024\u306e\u6570\u3092\u6570\u3048\u308b<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">notnull<\/span> (). <span style=\"color: #3366ff;\">sum<\/span> (). <span style=\"color: #3366ff;\">sum<\/span> ()<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u4f8b\u306f\u3001\u6b21\u306e pandas DataFrame \u3067\u5404\u30e1\u30bd\u30c3\u30c9\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<span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\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, np.nan],\n                   ' <span style=\"color: #ff0000;\">assists<\/span> ': [5, np.nan, 7, 9, 12, 9, 9, np.nan],\n                   ' <span style=\"color: #ff0000;\">rebounds<\/span> ': [11, 8, 10, 6, 6, 5, np.nan, 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 18.0 5.0 11.0\n1 B 22.0 NaN 8.0\n2 C 19.0 7.0 10.0\n3D 14.0 9.0 6.0\n4 E 14.0 12.0 6.0\n5 F 11.0 9.0 5.0\n6G 20.0 9.0 NaN\n7 H NaN NaN 12.0\n<\/strong><\/pre>\n<h2><span style=\"color: #000000;\"><strong>\u4f8b 1: \u3069\u306e\u5217\u306b\u3082 null \u5024\u3092\u542b\u307e\u306a\u3044\u884c\u3092\u30d5\u30a3\u30eb\u30bf\u30fc\u3059\u308b<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001DataFrame \u3092\u30d5\u30a3\u30eb\u30bf\u30fc\u3057\u3066\u3001\u3069\u306e\u5217\u306b\u3082 null \u5024\u3092\u542b\u307e\u306a\u3044\u884c\u306e\u307f\u3092\u8868\u793a\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;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#filter for rows with no null values in any column\n<\/span>df[df. <span style=\"color: #3366ff;\">notnull<\/span> (). <span style=\"color: #3366ff;\">all<\/span> ( <span style=\"color: #008000;\">1<\/span> )]\n\n\n        team points assists rebounds\n0 A 18.0 5.0 11.0\n2 C 19.0 7.0 10.0\n3D 14.0 9.0 6.0\n4 E 14.0 12.0 6.0\n5 F 11.0 9.0 5.0<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u3053\u306e\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u3055\u308c\u305f DataFrame \u306e\u5404\u884c\u306e\u3069\u306e\u5217\u306b\u3082 null \u5024\u304c\u306a\u3044\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u4f8b 2: \u7279\u5b9a\u306e\u5217\u306b null \u5024\u3092\u542b\u307e\u306a\u3044\u884c\u3092\u30d5\u30a3\u30eb\u30bf\u30fc\u3059\u308b<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001<strong>\u30d8\u30eb\u30d1\u30fc<\/strong>\u5217\u306b null \u5024\u3092\u542b\u307e\u306a\u3044\u884c\u306e\u307f\u3092\u8868\u793a\u3059\u308b\u3088\u3046\u306b DataFrame \u3092\u30d5\u30a3\u30eb\u30bf\u30fc\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;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#filter for rows with no null values in the 'assists' column\n<\/span>df[df[[' <span style=\"color: #ff0000;\">assists<\/span> ']]. <span style=\"color: #3366ff;\">notnull<\/span> (). <span style=\"color: #3366ff;\">all<\/span> ( <span style=\"color: #008000;\">1<\/span> )]\n\n\tteam points assists rebounds\n0 A 18.0 5.0 11.0\n2 C 19.0 7.0 10.0\n3D 14.0 9.0 6.0\n4 E 14.0 12.0 6.0\n5 F 11.0 9.0 5.0\n6G 20.0 9.0 NaN<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u3053\u306e\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u3055\u308c\u305f DataFrame \u306e\u5404\u884c\u306e<strong>Helper<\/strong>\u5217\u306b null \u5024\u304c\u306a\u3044\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u4f8b 3: \u5404\u5217\u306e\u30bc\u30ed\u4ee5\u5916\u306e\u5024\u306e\u6570\u3092\u6570\u3048\u308b<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001DataFrame \u306e\u5404\u5217\u306e\u30bc\u30ed\u4ee5\u5916\u306e\u5024\u306e\u6570\u3092\u30ab\u30a6\u30f3\u30c8\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;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#count number of non-null values in each column<\/span>\ndf. <span style=\"color: #3366ff;\">notnull<\/span> (). <span style=\"color: #3366ff;\">sum<\/span> ()\n\nteam 8\npoints 7\nassists 6\nrebounds 7\ndtype: int64\n<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\"><span style=\"color: #000000;\">\u7d50\u679c\u304b\u3089\u6b21\u306e\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\"><strong>\u30c1\u30fc\u30e0<\/strong>\u5217\u306b\u306f 8 \u3064\u306e\u975e\u30bc\u30ed\u5024\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\"><b>\u30dd\u30a4\u30f3\u30c8<\/b>\u5217\u306b\u306f 7 \u3064\u306e\u975e\u30bc\u30ed\u5024\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\"><b>Assists<\/b>\u5217\u306b\u306f 6 \u3064\u306e\u30bc\u30ed\u4ee5\u5916\u306e\u5024\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\"><b>\u30d0\u30a6\u30f3\u30b9<\/b>\u5217\u306b\u306f 7 \u3064\u306e\u975e\u30bc\u30ed\u5024\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<h2><span style=\"color: #000000;\"><strong>\u4f8b 4: DataFrame \u5168\u4f53\u5185\u306e\u30bc\u30ed\u4ee5\u5916\u306e\u5024\u306e\u6570\u3092\u6570\u3048\u308b<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001DataFrame \u5168\u4f53\u5185\u306e\u30bc\u30ed\u4ee5\u5916\u306e\u5024\u306e\u6570\u3092\u30ab\u30a6\u30f3\u30c8\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;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#count number of non-null values in entire DataFrame\n<\/span>df. <span style=\"color: #3366ff;\">notnull<\/span> (). <span style=\"color: #3366ff;\">sum<\/span> (). <span style=\"color: #3366ff;\">sum<\/span> ()\n\n28\n<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u51fa\u529b\u304b\u3089\u3001DataFrame \u5168\u4f53\u306b<strong>28 \u500b<\/strong>\u306e\u975e\u30bc\u30ed\u5024\u304c\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/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\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u64cd\u4f5c\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n<p> Pandas DataFrame \u3092\u5217\u5024\u3067\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u3059\u308b\u65b9\u6cd5<br \/><a href=\"https:\/\/statorials.org\/ja\/\u30cf\u309a\u30f3\u30bf\u3099\u306b\u306f\u542b\u307e\u308c\u3066\u3044\u307e\u305b\u3093\/\" target=\"_blank\" rel=\"noopener\">Pandas\u3067\u300c\u3092\u542b\u307e\u306a\u3044\u300d\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\u8907\u6570\u306e\u6761\u4ef6\u3092\u30d5\u30a3\u30eb\u30bf\u30fc\u3057\u307e\u3059\/\" target=\"_blank\" rel=\"noopener\">\u8907\u6570\u306e\u6761\u4ef6\u3067 Pandas DataFrame \u3092\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>pandas notnull()\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001pandas DataFrame \u306e\u8981\u7d20\u304c null \u304b\u3069\u3046\u304b\u3092\u30c6\u30b9\u30c8\u3067\u304d\u307e\u3059\u3002 \u8981\u7d20\u304c NaN \u307e\u305f\u306f None \u306b\u7b49\u3057\u3044\u5834\u5408\u3001\u95a2\u6570\u306fFalse\u3092\u8fd4\u3057\u307e\u3059\u3002 \u305d\u308c\u4ee5\u5916\u306e [&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-3854","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Pandas \u3067\u300cIs Not Null\u300d\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5 (\u4f8b\u4ed8\u304d) \u2013 \u8a18\u4e8b<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001pandas \u3067 notnull() \u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u5024\u304c null \u304b\u3069\u3046\u304b\u3092\u30c6\u30b9\u30c8\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\u306f\u5acc\u3044\u3057\u3099\u3083\u306a\u3044\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas \u3067\u300cIs Not Null\u300d\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5 (\u4f8b\u4ed8\u304d) \u2013 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