{"id":3774,"date":"2023-07-15T15:12:09","date_gmt":"2023-07-15T15:12:09","guid":{"rendered":"https:\/\/statorials.org\/ar\/%d8%a7%d9%84%d8%a8%d8%a7%d9%86%d8%af%d8%a7-%d8%aa%d8%ad%d8%b5%d9%84-%d8%b9%d9%84%d9%89-%d8%a7%d9%94%d8%b3%d9%85%d8%a7%d8%a1-%d8%a7%d9%84%d8%a7%d9%94%d8%b9%d9%85%d8%af%d8%a9\/"},"modified":"2023-07-15T15:12:09","modified_gmt":"2023-07-15T15:12:09","slug":"%d8%a7%d9%84%d8%a8%d8%a7%d9%86%d8%af%d8%a7-%d8%aa%d8%ad%d8%b5%d9%84-%d8%b9%d9%84%d9%89-%d8%a7%d9%94%d8%b3%d9%85%d8%a7%d8%a1-%d8%a7%d9%84%d8%a7%d9%94%d8%b9%d9%85%d8%af%d8%a9","status":"publish","type":"post","link":"https:\/\/statorials.org\/ar\/%d8%a7%d9%84%d8%a8%d8%a7%d9%86%d8%af%d8%a7-%d8%aa%d8%ad%d8%b5%d9%84-%d8%b9%d9%84%d9%89-%d8%a7%d9%94%d8%b3%d9%85%d8%a7%d8%a1-%d8%a7%d9%84%d8%a7%d9%94%d8%b9%d9%85%d8%af%d8%a9\/","title":{"rendered":"\u0643\u064a\u0641\u064a\u0629 \u0627\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0641\u064a pandas (3 \u0637\u0631\u0642)"},"content":{"rendered":"

<\/p>\n

\n

\u064a\u0645\u0643\u0646\u0643 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0637\u0631\u0642 \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0644\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0641\u064a pandas DataFrame:<\/span><\/p>\n

\u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u0623\u0648\u0644\u0649: \u0627\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0643\u0627\u0641\u0629 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629<\/strong><\/span><\/p>\n

 list<\/span> (df)<\/span><\/span><\/strong><\/pre>\n
 \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u062b\u0627\u0646\u064a\u0629: \u0627\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0623\u0628\u062c\u062f\u064a\u064b\u0627<\/strong><\/span><\/p>\n
 sorted<\/span> (df)\n<\/span><\/span><\/strong><\/pre>\n
 \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u062b\u0627\u0644\u062b\u0629: \u0627\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0628\u0646\u0648\u0639 \u0628\u064a\u0627\u0646\u0627\u062a \u0645\u062d\u062f\u062f<\/strong><\/span><\/p>\n
 list<\/span> ( df.select_dtypes<\/span> (include=[' int64<\/span> ', ' bool<\/span> ']))<\/strong><\/pre>\n
 \u062a\u0648\u0636\u062d \u0627\u0644\u0623\u0645\u062b\u0644\u0629 \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0643\u064a\u0641\u064a\u0629 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0643\u0644 \u0637\u0631\u064a\u0642\u0629 \u0645\u0639 \u0627\u0644\u0628\u0627\u0646\u062f\u0627 DataFrame \u0627\u0644\u062a\u0627\u0644\u064a\u0629:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F'],\n                   ' points<\/span> ': [18, 22, 19, 14, 14, 11],\n                   ' assists<\/span> ': [5, 7, 7, 9, 12, 9],\n                   ' playoffs<\/span> ': [True, False, False, True, True, True]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n  team points assists playoffs\n0 A 18 5 True\n1 B 22 7 False\n2 C 19 7 False\n3 D 14 9 True\n4 E 14 12 True\n5 F 11 9 True\n<\/b><\/pre>\n
 \u0645\u062b\u0627\u0644 1: \u0627\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0643\u0627\u0641\u0629 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629<\/strong><\/span><\/h2>\n
 \u0623\u0633\u0647\u0644 \u0637\u0631\u064a\u0642\u0629 \u0644\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u062c\u0645\u064a\u0639 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0641\u064a pandas DataFrame \u0647\u064a \u0627\u0633\u062a\u062e\u062f\u0627\u0645 list()<\/strong> \u0643\u0645\u0627 \u064a\u0644\u064a:<\/span><\/span><\/p>\n
 #get all column names<\/span>\nlist<\/span> (df)\n\n['team', 'points', 'assists', 'playoffs']\n<\/span><\/span><\/strong><\/pre>\n
 \u0648\u0627\u0644\u0646\u062a\u064a\u062c\u0629 \u0647\u064a \u0642\u0627\u0626\u0645\u0629 \u062a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0627\u0644\u0623\u0631\u0628\u0639\u0629 \u0644\u0640 pandas DataFrame.<\/span><\/span><\/p>\n
 \u0645\u062b\u0627\u0644 2: \u0627\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0623\u0628\u062c\u062f\u064a\u064b\u0627<\/strong><\/span><\/h2>\n
 \u0644\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0641\u064a Pandas DataFrame \u0628\u0627\u0644\u062a\u0631\u062a\u064a\u0628 \u0627\u0644\u0623\u0628\u062c\u062f\u064a\u060c \u064a\u0645\u0643\u0646\u0643 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 sorted()<\/strong> \u0643\u0645\u0627 \u064a\u0644\u064a:<\/span><\/p>\n
 #get column names in alphabetical order<\/span>\nsorted<\/span> (df)\n\n['assists', 'playoffs', 'points', 'team']\n<\/span><\/span><\/strong><\/pre>\n
 \u0648\u0627\u0644\u0646\u062a\u064a\u062c\u0629 \u0647\u064a \u0642\u0627\u0626\u0645\u0629 \u062a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0627\u0644\u0623\u0631\u0628\u0639\u0629 \u0644\u0640 pandas DataFrame \u0627\u0644\u0645\u062f\u0631\u062c\u0629 \u0628\u0627\u0644\u062a\u0631\u062a\u064a\u0628 \u0627\u0644\u0623\u0628\u062c\u062f\u064a.<\/span><\/p>\n
 \u064a\u0645\u0643\u0646\u0643 \u0623\u064a\u0636\u064b\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0648\u0633\u064a\u0637\u0629 verse=True<\/strong> \u0644\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0628\u062a\u0631\u062a\u064a\u0628 \u0623\u0628\u062c\u062f\u064a \u0639\u0643\u0633\u064a:<\/span><\/p>\n
 #get column names in reverse alphabetical order<\/span>\nsorted<\/span> (df, reverse= True<\/span> )\n\n['team', 'points', 'playoffs', 'assists']<\/span><\/span><\/strong>\n<\/pre>\n
 \u0645\u062b\u0627\u0644 3: \u0627\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0628\u0646\u0648\u0639 \u0628\u064a\u0627\u0646\u0627\u062a \u0645\u062d\u062f\u062f<\/strong><\/span><\/h2>\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\u062a\u0627\u0644\u064a \u0644\u0639\u0631\u0636 \u0646\u0648\u0639 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0644\u0643\u0644 \u0639\u0645\u0648\u062f \u0641\u064a DataFrame:<\/span><\/span><\/p>\n
 #view data type of each column<\/span>\ndf. dtypes<\/span>\n\nteam object\nint64 dots\nassists int64\nplayoffs bool\ndtype:object\n<\/span><\/span><\/strong><\/pre>\n
 \u064a\u0645\u0643\u0646\u0643 \u0628\u0639\u062f \u0630\u0644\u0643 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 Select_dtypes()<\/strong> \u0644\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0630\u0627\u062a \u0646\u0648\u0639 \u0628\u064a\u0627\u0646\u0627\u062a \u0645\u062d\u062f\u062f \u0641\u0642\u0637.<\/span><\/p>\n
 \u0639\u0644\u0649 \u0633\u0628\u064a\u0644 \u0627\u0644\u0645\u062b\u0627\u0644\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 \u0644\u0644\u062d\u0635\u0648\u0644 \u0641\u0642\u0637 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0627\u0644\u062a\u064a \u062a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 \u0646\u0648\u0639 \u0628\u064a\u0627\u0646\u0627\u062a int64<\/strong> \u0623\u0648 bool<\/strong> :<\/span><\/p>\n
 #get all columns that have data type of int64 or bool<\/span>\nlist<\/span> ( df.select_dtypes<\/span> (include=[' int64<\/span> ', ' bool<\/span> ']))\n\n['points', 'assists', 'playoffs']<\/span>\n<\/span><\/strong><\/pre>\n
 \u0648\u0627\u0644\u0646\u062a\u064a\u062c\u0629 \u0647\u064a \u0642\u0627\u0626\u0645\u0629 \u0628\u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0627\u0644\u062a\u064a \u062a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 \u0646\u0648\u0639 \u0628\u064a\u0627\u0646\u0627\u062a int64<\/strong> \u0623\u0648 bool<\/strong> .<\/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\u0639\u0645\u0644\u064a\u0627\u062a \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
 \u0627\u0644\u0628\u0627\u0646\u062f\u0627: \u0643\u064a\u0641\u064a\u0629 \u0625\u0639\u0627\u062f\u0629 \u062a\u0633\u0645\u064a\u0629 \u0627\u0644\u0623\u0639\u0645\u062f\u0629<\/a>
 \u0627\u0644\u0628\u0627\u0646\u062f\u0627: \u0643\u064a\u0641\u064a\u0629 \u062a\u0639\u064a\u064a\u0646 \u0639\u0645\u0648\u062f \u0643\u0645\u0624\u0634\u0631<\/a>
 \u0627\u0644\u0628\u0627\u0646\u062f\u0627: \u0627\u062d\u0635\u0644 \u0639\u0644\u0649 \u0641\u0647\u0631\u0633 \u0627\u0644\u0635\u0641\u0648\u0641 \u0627\u0644\u062a\u064a \u064a\u062a\u0637\u0627\u0628\u0642 \u0639\u0645\u0648\u062f\u0647\u0627 \u0645\u0639 \u0627\u0644\u0642\u064a\u0645\u0629<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u064a\u0645\u0643\u0646\u0643 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0637\u0631\u0642 \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0644\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0641\u064a pandas DataFrame: \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u0623\u0648\u0644\u0649: \u0627\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0643\u0627\u0641\u0629 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 list (df) \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u062b\u0627\u0646\u064a\u0629: \u0627\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0623\u0628\u062c\u062f\u064a\u064b\u0627 sorted (df) \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u062b\u0627\u0644\u062b\u0629: \u0627\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0628\u0646\u0648\u0639 \u0628\u064a\u0627\u0646\u0627\u062a \u0645\u062d\u062f\u062f list ( df.select_dtypes (include=[‘ int64 ‘, ‘ bool ‘])) \u062a\u0648\u0636\u062d \u0627\u0644\u0623\u0645\u062b\u0644\u0629 \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0643\u064a\u0641\u064a\u0629 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0643\u0644 \u0637\u0631\u064a\u0642\u0629 \u0645\u0639 […]<\/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\u0643\u064a\u0641\u064a\u0629 \u0627\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0641\u064a Pandas (3 \u0637\u0631\u0642) \u2013 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 \u0627\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0645\u0646 Pandas DataFrame\u060c \u0645\u0639 \u0639\u062f\u0629 \u0623\u0645\u062b\u0644\u0629.\" \/>\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-\u062a\u062d\u0635\u0644-\u0639\u0644\u0649-\u0627\u0654\u0633\u0645\u0627\u0621-\u0627\u0644\u0627\u0654\u0639\u0645\u062f\u0629\/\" \/>\n<meta property=\"og:locale\" content=\"az_AZ\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u0643\u064a\u0641\u064a\u0629 \u0627\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0641\u064a Pandas (3 \u0637\u0631\u0642) \u2013 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 \u0627\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0623\u0633\u0645\u0627\u0621 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0645\u0646 Pandas DataFrame\u060c \u0645\u0639 \u0639\u062f\u0629 \u0623\u0645\u062b\u0644\u0629.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ar\/\u0627\u0644\u0628\u0627\u0646\u062f\u0627-\u062a\u062d\u0635\u0644-\u0639\u0644\u0649-\u0627\u0654\u0633\u0645\u0627\u0621-\u0627\u0644\u0627\u0654\u0639\u0645\u062f\u0629\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-15T15:12:09+00:00\" \/>\n<meta name=\"author\" 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