{"id":892,"date":"2023-07-28T09:46:04","date_gmt":"2023-07-28T09:46:04","guid":{"rendered":"https:\/\/statorials.org\/pl\/upusc-pandy\/"},"modified":"2023-07-28T09:46:04","modified_gmt":"2023-07-28T09:46:04","slug":"upusc-pandy","status":"publish","type":"post","link":"https:\/\/statorials.org\/pl\/upusc-pandy\/","title":{"rendered":"Jak usun\u0105\u0107 wiersze z warto\u015bciami nan w pandach"},"content":{"rendered":"

<\/p>\n

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Cz\u0119sto mo\u017cesz chcie\u0107 usun\u0105\u0107 wiersze zawieraj\u0105ce warto\u015bci NaN w ramce DataFrame pandy. Na szcz\u0119\u015bcie mo\u017cna to \u0142atwo zrobi\u0107 za pomoc\u0105 funkcji pandy dropna()<\/a> .<\/span><\/p>\n

W tym samouczku przedstawiono kilka przyk\u0142ad\u00f3w u\u017cycia tej funkcji w nast\u0119puj\u0105cej ramce DataFrame pand:<\/span><\/p>\n

 import<\/span> numpy as<\/span> np\nimport<\/span> scipy.stats as<\/span> stats\n\n#create DataFrame with some NaN values<\/span>\ndf = pd.DataFrame({'rating': [np.nan, 85, np.nan, 88, 94, 90, 76, 75, 87, 86],\n                   'points': [np.nan, 25, 14, 16, 27, 20, 12, 15, 14, 19],\n                   'assists': [5, 7, 7, np.nan, 5, 7, 6, 9, 9, 5],\n                   'rebounds': [11, 8, 10, 6, 6, 9, 6, 10, 10, 7]})\n\n#view DataFrame\n<\/span>df\n\n\n        rating points assists rebounds\n0 NaN NaN 5.0 11\n1 85.0 25.0 7.0 8\n2 NaN 14.0 7.0 10\n3 88.0 16.0 NaN 6\n4 94.0 27.0 5.0 6\n5 90.0 20.0 7.0 9\n6 76.0 12.0 6.0 6\n7 75.0 15.0 9.0 10\n8 87.0 14.0 9.0 10\n9 86.0 19.0 5.0 7\n<\/strong><\/pre>\n
 Przyk\u0142ad 1: Usu\u0144 wiersze z warto\u015bciami NaN<\/strong><\/span><\/h3>\n
 Mo\u017cemy u\u017cy\u0107 nast\u0119puj\u0105cej sk\u0142adni, aby usun\u0105\u0107 wszystkie wiersze zawieraj\u0105ce warto\u015bci<\/em> NaN:<\/span><\/p>\n
 df. dropna<\/span> ()\n\n\trating points assists rebounds\n1 85.0 25.0 7.0 8\n4 94.0 27.0 5.0 6\n5 90.0 20.0 7.0 9\n6 76.0 12.0 6.0 6\n7 75.0 15.0 9.0 10\n8 87.0 14.0 9.0 10\n9 86.0 19.0 5.0 7\n<\/strong><\/pre>\n
 Przyk\u0142ad 2: Usu\u0144 wiersze ze wszystkimi warto\u015bciami NaN<\/strong><\/span><\/h3>\n
 Mo\u017cemy zastosowa\u0107 nast\u0119puj\u0105c\u0105 sk\u0142adni\u0119, aby usun\u0105\u0107 wszystkie wiersze zawieraj\u0105ce wszystkie<\/em> warto\u015bci NaN w ka\u017cdej kolumnie:<\/span><\/p>\n
 df. dropna<\/span> (how=' all<\/span> ') \n\n        rating points assists rebounds\n0 NaN NaN 5.0 11\n1 85.0 25.0 7.0 8\n2 NaN 14.0 7.0 10\n3 88.0 16.0 NaN 6\n4 94.0 27.0 5.0 6\n5 90.0 20.0 7.0 9\n6 76.0 12.0 6.0 6\n7 75.0 15.0 9.0 10\n8 87.0 14.0 9.0 10\n9 86.0 19.0 5.0 7\n<\/strong><\/pre>\n
 W tej konkretnej ramce DataFrame nie by\u0142o wierszy ze wszystkimi warto\u015bciami NaN, wi\u0119c \u017caden z wierszy nie zosta\u0142 usuni\u0119ty.<\/span><\/p>\n
 Przyk\u0142ad 3: Usu\u0144 wiersze poni\u017cej okre\u015blonego progu<\/strong><\/span><\/h3>\n
 Mo\u017cemy u\u017cy\u0107 nast\u0119puj\u0105cej sk\u0142adni, aby usun\u0105\u0107 wszystkie wiersze, kt\u00f3re nie zawieraj\u0105 co najmniej<\/em> okre\u015blonej liczby warto\u015bci innych ni\u017c NaN:<\/span><\/p>\n
 df. dropna<\/span> (thresh= 3<\/span> ) \n\n\trating points assists rebounds\n1 85.0 25.0 7.0 8\n2 NaN 14.0 7.0 10\n3 88.0 16.0 NaN 6\n4 94.0 27.0 5.0 6\n5 90.0 20.0 7.0 9\n6 76.0 12.0 6.0 6\n7 75.0 15.0 9.0 10\n8 87.0 14.0 9.0 10\n9 86.0 19.0 5.0 7\n<\/strong><\/pre>\n
 Pierwszy wiersz oryginalnej ramki DataFrame nie zawiera\u0142 co najmniej 3 warto\u015bci innych ni\u017c NaN, wi\u0119c by\u0142 to jedyny wiersz, kt\u00f3ry zosta\u0142 usuni\u0119ty.<\/span><\/p>\n
 Przyk\u0142ad 4: Usu\u0144 wiersz z warto\u015bciami Nan w okre\u015blonej kolumnie<\/strong><\/span><\/h3>\n
 Mo\u017cemy u\u017cy\u0107 nast\u0119puj\u0105cej sk\u0142adni, aby usun\u0105\u0107 wszystkie wiersze zawieraj\u0105ce warto\u015b\u0107 NaN w okre\u015blonej kolumnie:<\/span><\/p>\n
 df. dropna<\/span> (subset=[' assists<\/span> '])\n\n\trating points assists rebounds\n0 NaN NaN 5.0 11\n1 85.0 25.0 7.0 8\n2 NaN 14.0 7.0 10\n4 94.0 27.0 5.0 6\n5 90.0 20.0 7.0 9\n6 76.0 12.0 6.0 6\n7 75.0 15.0 9.0 10\n8 87.0 14.0 9.0 10\n9 86.0 19.0 5.0 7<\/strong><\/pre>\n
 Przyk\u0142ad 5: Zresetuj indeks po usuni\u0119ciu wierszy z NaN<\/strong><\/span><\/h3>\n
 Mo\u017cemy u\u017cy\u0107 nast\u0119puj\u0105cej sk\u0142adni, aby zresetowa\u0107 indeks DataFrame po usuni\u0119ciu wierszy z warto\u015bciami NaN:<\/span><\/p>\n
 #drop all rows that have any NaN values<\/span>\ndf = df. dropna<\/span> ()\n\n#reset index of DataFrame<\/span>\ndf = df. reset_index<\/span> (drop=True)\n\n#view DataFrame<\/span>\ndf\n\n        rating points assists rebounds\n0 85.0 25.0 7.0 8\n1 94.0 27.0 5.0 6\n2 90.0 20.0 7.0 9\n3 76.0 12.0 6.0 6\n4 75.0 15.0 9.0 10\n5 87.0 14.0 9.0 10\n6 86.0 19.0 5.0 77<\/strong><\/pre>\n
 Pe\u0142n\u0105 dokumentacj\u0119 funkcji dropna() znajdziesz tutaj<\/a> .<\/em><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"
Cz\u0119sto mo\u017cesz chcie\u0107 usun\u0105\u0107 wiersze zawieraj\u0105ce warto\u015bci NaN w ramce DataFrame pandy. Na szcz\u0119\u015bcie mo\u017cna to \u0142atwo zrobi\u0107 za pomoc\u0105 funkcji pandy dropna() . W tym samouczku przedstawiono kilka przyk\u0142ad\u00f3w u\u017cycia tej funkcji w nast\u0119puj\u0105cej ramce DataFrame pand: import numpy as np import scipy.stats as stats #create DataFrame with some NaN values df = pd.DataFrame({’rating’: […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"class_list":["post-892","post","type-post","status-publish","format-standard","hentry","category-przewodnik"],"yoast_head":"\nJak usun\u0105\u0107 wiersze z warto\u015bciami NaN w Pandach<\/title>\n<meta name=\"description\" content=\"Proste wyja\u015bnienie, jak usun\u0105\u0107 wiersze z warto\u015bciami NaN w pandzie DataFrame.\" \/>\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\/pl\/upusc-pandy\/\" \/>\n<meta property=\"og:locale\" content=\"pl_PL\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Jak usun\u0105\u0107 wiersze z warto\u015bciami NaN w Pandach\" \/>\n<meta property=\"og:description\" content=\"Proste wyja\u015bnienie, jak usun\u0105\u0107 wiersze z warto\u015bciami NaN w pandzie DataFrame.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/pl\/upusc-pandy\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-28T09:46:04+00:00\" \/>\n<meta name=\"author\" content=\"Benjamin Anderson\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Napisane przez\" \/>\n\t<meta name=\"twitter:data1\" content=\"Benjamin Anderson\" \/>\n\t<meta name=\"twitter:label2\" content=\"Szacowany czas czytania\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minuty\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/pl\/upusc-pandy\/\",\"url\":\"https:\/\/statorials.org\/pl\/upusc-pandy\/\",\"name\":\"Jak usun\u0105\u0107 wiersze z warto\u015bciami NaN w Pandach\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/pl\/#website\"},\"datePublished\":\"2023-07-28T09:46:04+00:00\",\"dateModified\":\"2023-07-28T09:46:04+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/pl\/#\/schema\/person\/6484727a4612df3e69f016c3129c6965\"},\"description\":\"Proste wyja\u015bnienie, jak usun\u0105\u0107 wiersze z warto\u015bciami NaN w pandzie DataFrame.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/pl\/upusc-pandy\/#breadcrumb\"},\"inLanguage\":\"pl-PL\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/pl\/upusc-pandy\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/pl\/upusc-pandy\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Dom\",\"item\":\"https:\/\/statorials.org\/pl\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Jak usun\u0105\u0107 wiersze z warto\u015bciami nan w pandach\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/pl\/#website\",\"url\":\"https:\/\/statorials.org\/pl\/\",\"name\":\"Statorials\",\"description\":\"Tw\u00f3j przewodnik po kompetencjach statystycznych!\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/pl\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"pl-PL\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/statorials.org\/pl\/#\/schema\/person\/6484727a4612df3e69f016c3129c6965\",\"name\":\"Benjamin Anderson\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"pl-PL\",\"@id\":\"https:\/\/statorials.org\/pl\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/statorials.org\/pl\/wp-content\/uploads\/2023\/11\/Benjamin-Anderson-96x96.jpg\",\"contentUrl\":\"https:\/\/statorials.org\/pl\/wp-content\/uploads\/2023\/11\/Benjamin-Anderson-96x96.jpg\",\"caption\":\"Benjamin Anderson\"},\"description\":\"Cze\u015b\u0107, jestem Benjamin i jestem emerytowanym profesorem statystyki, kt\u00f3ry zosta\u0142 oddanym nauczycielem Statorials. 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