{"id":3536,"date":"2023-07-16T23:21:00","date_gmt":"2023-07-16T23:21:00","guid":{"rendered":"https:\/\/statorials.org\/ar\/%d8%a7%d9%84%d8%a8%d8%a7%d9%86%d8%af%d8%a7-%d8%a7%d9%95%d8%b9%d8%a7%d8%af%d8%a9-%d8%aa%d8%b9%d9%8a%d9%8a%d9%86-%d8%a7%d9%84%d9%81%d9%87%d8%b1%d8%b3-%d8%a8%d8%b9%d8%af-dropna\/"},"modified":"2023-07-16T23:21:00","modified_gmt":"2023-07-16T23:21:00","slug":"%d8%a7%d9%84%d8%a8%d8%a7%d9%86%d8%af%d8%a7-%d8%a7%d9%95%d8%b9%d8%a7%d8%af%d8%a9-%d8%aa%d8%b9%d9%8a%d9%8a%d9%86-%d8%a7%d9%84%d9%81%d9%87%d8%b1%d8%b3-%d8%a8%d8%b9%d8%af-dropna","status":"publish","type":"post","link":"https:\/\/statorials.org\/ar\/%d8%a7%d9%84%d8%a8%d8%a7%d9%86%d8%af%d8%a7-%d8%a7%d9%95%d8%b9%d8%a7%d8%af%d8%a9-%d8%aa%d8%b9%d9%8a%d9%8a%d9%86-%d8%a7%d9%84%d9%81%d9%87%d8%b1%d8%b3-%d8%a8%d8%b9%d8%af-dropna\/","title":{"rendered":"\u0627\u0644\u0628\u0627\u0646\u062f\u0627: \u0643\u064a\u0641\u064a\u0629 \u0625\u0639\u0627\u062f\u0629 \u0636\u0628\u0637 \u0627\u0644\u0641\u0647\u0631\u0633 \u0628\u0639\u062f \u0627\u0633\u062a\u062e\u062f\u0627\u0645 dropna()"},"content":{"rendered":"

<\/p>\n

\n

\u064a\u0645\u0643\u0646\u0643 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0628\u0646\u0627\u0621 \u0627\u0644\u062c\u0645\u0644\u0629 \u0627\u0644\u0623\u0633\u0627\u0633\u064a \u0627\u0644\u062a\u0627\u0644\u064a \u0644\u0625\u0639\u0627\u062f\u0629 \u062a\u0639\u064a\u064a\u0646 \u0641\u0647\u0631\u0633 \u0627\u0644\u0628\u0627\u0646\u062f\u0627 DataFrame \u0628\u0639\u062f \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 dropna()<\/strong> \u0644\u0625\u0633\u0642\u0627\u0637 \u0627\u0644\u0635\u0641\u0648\u0641 \u0630\u0627\u062a \u0627\u0644\u0642\u064a\u0645 \u0627\u0644\u0645\u0641\u0642\u0648\u062f\u0629:<\/span><\/p>\n

 df = df. dropna<\/span> (). reset_index<\/span> (drop= True<\/span> )\n<\/strong><\/pre>\n
 \u064a\u0648\u0636\u062d \u0627\u0644\u0645\u062b\u0627\u0644 \u0627\u0644\u062a\u0627\u0644\u064a \u0643\u064a\u0641\u064a\u0629 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0628\u0646\u0627\u0621 \u0627\u0644\u062c\u0645\u0644\u0629 \u0647\u0630\u0627 \u0639\u0645\u0644\u064a\u064b\u0627.<\/span><\/p>\n
 \u0645\u062b\u0627\u0644: \u0625\u0639\u0627\u062f\u0629 \u062a\u0639\u064a\u064a\u0646 \u0627\u0644\u0641\u0647\u0631\u0633 \u0641\u064a Pandas \u0628\u0639\u062f \u0627\u0633\u062a\u062e\u062f\u0627\u0645 dropna()<\/strong><\/span><\/h2>\n
 \u0644\u0646\u0641\u062a\u0631\u0636 \u0623\u0646 \u0644\u062f\u064a\u0646\u0627 DataFrame \u0627\u0644\u0628\u0627\u0646\u062f\u0627 \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0627\u0644\u062a\u064a \u062a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 \u0645\u0639\u0644\u0648\u0645\u0627\u062a \u062d\u0648\u0644 \u0645\u062e\u062a\u0644\u0641 \u0644\u0627\u0639\u0628\u064a \u0643\u0631\u0629 \u0627\u0644\u0633\u0644\u0629:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\nimport<\/span> numpy as<\/span> np\n\n#create dataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],\n                   ' points<\/span> ': [18, np.nan, 19, 14, 14, 11, 20, 28],\n                   ' assists<\/span> ': [5, 7, 7, 9, 12, np.nan, 9, 4],\n                   ' rebounds<\/span> ': [11, 8, 10, 6, 6, 5, np.nan, 12]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n  team points assists rebounds\n0 A 18.0 5.0 11.0\n1 B NaN 7.0 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 NaN 5.0\n6G 20.0 9.0 NaN\n7 H 28.0 4.0 12.0\n<\/strong><\/pre>\n
 \u0644\u0646\u0641\u062a\u0631\u0636 \u0627\u0644\u0622\u0646 \u0623\u0646\u0646\u0627 \u0646\u0633\u062a\u062e\u062f\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 dropna()<\/strong> \u0644\u0625\u0632\u0627\u0644\u0629 \u0643\u0627\u0641\u0629 \u0627\u0644\u0635\u0641\u0648\u0641 \u0645\u0646 DataFrame \u0627\u0644\u062a\u064a \u062a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 \u0642\u064a\u0645\u0629 \u0645\u0641\u0642\u0648\u062f\u0629 \u0641\u064a \u0639\u0645\u0648\u062f:<\/span><\/span><\/p>\n
 #drop rows with nan values in any column\n<\/span>df = df. dropna<\/span> ()\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\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\n7 H 28.0 4.0 12.0<\/strong><\/pre>\n
 \u0644\u0627\u062d\u0638 \u0623\u0646 \u0627\u0644\u0641\u0647\u0631\u0633 \u0644\u0627 \u064a\u0632\u0627\u0644 \u064a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 \u0642\u064a\u0645 \u0627\u0644\u0641\u0647\u0631\u0633 \u0627\u0644\u0623\u0635\u0644\u064a\u0629 \u0644\u0643\u0644 \u0635\u0641.<\/span><\/p>\n
 \u0644\u0625\u0639\u0627\u062f\u0629 \u0636\u0628\u0637 \u0627\u0644\u0641\u0647\u0631\u0633 \u0628\u0639\u062f \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 dropna()<\/strong> \u060c \u064a\u0645\u0643\u0646\u0646\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0635\u064a\u063a\u0629 \u0627\u0644\u062a\u0627\u0644\u064a\u0629:<\/span><\/p>\n
 #drop rows with nan values in any column\n<\/span>df = df. dropna<\/span> (). reset_index<\/span> (drop= True<\/span> )\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n  team points assists rebounds\n0 A 18.0 5.0 11.0\n1 C 19.0 7.0 10.0\n2 D 14.0 9.0 6.0\n3 E 14.0 12.0 6.0\n4 H 28.0 4.0 12.0\n<\/strong><\/pre>\n
 \u0644\u0627\u062d\u0638 \u0623\u0646\u0647 \u062a\u0645 \u062d\u0630\u0641 \u0643\u0644 \u0627\u0644\u0635\u0641\u0648\u0641 \u0630\u0627\u062a \u0627\u0644\u0642\u064a\u0645 \u0627\u0644\u0645\u0641\u0642\u0648\u062f\u0629 \u0648\u0625\u0639\u0627\u062f\u0629 \u062a\u0639\u064a\u064a\u0646 \u0642\u064a\u0645 \u0627\u0644\u0641\u0647\u0631\u0633.<\/span><\/span><\/p>\n
 \u062a\u062a\u0631\u0627\u0648\u062d \u0642\u064a\u0645 \u0627\u0644\u0641\u0647\u0631\u0633 \u0627\u0644\u0622\u0646 \u0645\u0646 0 \u0625\u0644\u0649 4.<\/span><\/p>\n
 \u0645\u0635\u0627\u062f\u0631 \u0625\u0636\u0627\u0641\u064a\u0629<\/strong><\/span><\/h2>\n
 \u062a\u0634\u0631\u062d \u0627\u0644\u0628\u0631\u0627\u0645\u062c \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u064a\u0629 \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0643\u064a\u0641\u064a\u0629 \u062a\u0646\u0641\u064a\u0630 \u0627\u0644\u0645\u0647\u0627\u0645 \u0627\u0644\u0634\u0627\u0626\u0639\u0629 \u0627\u0644\u0623\u062e\u0631\u0649 \u0641\u064a \u0627\u0644\u0628\u0627\u0646\u062f\u0627:<\/span><\/p>\n
 \u0643\u064a\u0641\u064a\u0629 \u0637\u0628\u0627\u0639\u0629 Pandas DataFrame \u0628\u062f\u0648\u0646 \u0641\u0647\u0631\u0633<\/a>
 \u0643\u064a\u0641\u064a\u0629 \u0627\u0644\u062a\u0635\u0641\u064a\u0629 \u062d\u0633\u0628 \u0642\u064a\u0645\u0629 \u0627\u0644\u0641\u0647\u0631\u0633 \u0641\u064a \u0627\u0644\u0628\u0627\u0646\u062f\u0627<\/a>
 \u0643\u064a\u0641\u064a\u0629 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0639\u0645\u0648\u062f \u0627\u0644\u0623\u0648\u0644 \u0643\u0641\u0647\u0631\u0633 \u0641\u064a Pandas<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u064a\u0645\u0643\u0646\u0643 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0628\u0646\u0627\u0621 \u0627\u0644\u062c\u0645\u0644\u0629 \u0627\u0644\u0623\u0633\u0627\u0633\u064a \u0627\u0644\u062a\u0627\u0644\u064a \u0644\u0625\u0639\u0627\u062f\u0629 \u062a\u0639\u064a\u064a\u0646 \u0641\u0647\u0631\u0633 \u0627\u0644\u0628\u0627\u0646\u062f\u0627 DataFrame \u0628\u0639\u062f \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 dropna() \u0644\u0625\u0633\u0642\u0627\u0637 \u0627\u0644\u0635\u0641\u0648\u0641 \u0630\u0627\u062a \u0627\u0644\u0642\u064a\u0645 \u0627\u0644\u0645\u0641\u0642\u0648\u062f\u0629: df = df. dropna (). reset_index (drop= True ) \u064a\u0648\u0636\u062d \u0627\u0644\u0645\u062b\u0627\u0644 \u0627\u0644\u062a\u0627\u0644\u064a \u0643\u064a\u0641\u064a\u0629 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0628\u0646\u0627\u0621 \u0627\u0644\u062c\u0645\u0644\u0629 \u0647\u0630\u0627 \u0639\u0645\u0644\u064a\u064b\u0627. \u0645\u062b\u0627\u0644: \u0625\u0639\u0627\u062f\u0629 \u062a\u0639\u064a\u064a\u0646 \u0627\u0644\u0641\u0647\u0631\u0633 \u0641\u064a Pandas \u0628\u0639\u062f \u0627\u0633\u062a\u062e\u062f\u0627\u0645 dropna() \u0644\u0646\u0641\u062a\u0631\u0636 \u0623\u0646 \u0644\u062f\u064a\u0646\u0627 DataFrame \u0627\u0644\u0628\u0627\u0646\u062f\u0627 \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0627\u0644\u062a\u064a \u062a\u062d\u062a\u0648\u064a […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"yoast_head":"\n\u0627\u0644\u0628\u0627\u0646\u062f\u0627: \u0643\u064a\u0641\u064a\u0629 \u0625\u0639\u0627\u062f\u0629 \u0636\u0628\u0637 \u0627\u0644\u0641\u0647\u0631\u0633 \u0628\u0639\u062f \u0627\u0633\u062a\u062e\u062f\u0627\u0645 dropna() - Statorials<\/title>\n<meta name=\"description\" content=\"\u064a\u0634\u0631\u062d \u0647\u0630\u0627 \u0627\u0644\u0628\u0631\u0646\u0627\u0645\u062c \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u064a \u0643\u064a\u0641\u064a\u0629 \u0625\u0639\u0627\u062f\u0629 \u062a\u0639\u064a\u064a\u0646 \u0641\u0647\u0631\u0633 Pandas DataFrame \u0628\u0639\u062f \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 dropna()\u060c \u0645\u0639 \u0645\u062b\u0627\u0644.\" \/>\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\/ar\/\u0627\u0644\u0628\u0627\u0646\u062f\u0627-\u0627\u0655\u0639\u0627\u062f\u0629-\u062a\u0639\u064a\u064a\u0646-\u0627\u0644\u0641\u0647\u0631\u0633-\u0628\u0639\u062f-dropna\/\" \/>\n<meta property=\"og:locale\" content=\"az_AZ\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u0627\u0644\u0628\u0627\u0646\u062f\u0627: \u0643\u064a\u0641\u064a\u0629 \u0625\u0639\u0627\u062f\u0629 \u0636\u0628\u0637 \u0627\u0644\u0641\u0647\u0631\u0633 \u0628\u0639\u062f \u0627\u0633\u062a\u062e\u062f\u0627\u0645 dropna() - Statorials\" \/>\n<meta property=\"og:description\" content=\"\u064a\u0634\u0631\u062d \u0647\u0630\u0627 \u0627\u0644\u0628\u0631\u0646\u0627\u0645\u062c \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u064a \u0643\u064a\u0641\u064a\u0629 \u0625\u0639\u0627\u062f\u0629 \u062a\u0639\u064a\u064a\u0646 \u0641\u0647\u0631\u0633 Pandas DataFrame \u0628\u0639\u062f \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 dropna()\u060c \u0645\u0639 \u0645\u062b\u0627\u0644.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ar\/\u0627\u0644\u0628\u0627\u0646\u062f\u0627-\u0627\u0655\u0639\u0627\u062f\u0629-\u062a\u0639\u064a\u064a\u0646-\u0627\u0644\u0641\u0647\u0631\u0633-\u0628\u0639\u062f-dropna\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-16T23:21:00+00:00\" \/>\n<meta name=\"author\" content=\"\u062f\u0643\u062a\u0648\u0631 \u0628\u0646\u064a\u0627\u0645\u064a\u0646 \u0623\u0646\u062f\u0631\u0633\u0648\u0646\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"\u062f\u0643\u062a\u0648\u0631 \u0628\u0646\u064a\u0627\u0645\u064a\u0646 \u0623\u0646\u062f\u0631\u0633\u0648\u0646\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" 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