{"id":3434,"date":"2023-07-17T12:20:03","date_gmt":"2023-07-17T12:20:03","guid":{"rendered":"https:\/\/statorials.org\/ar\/%d8%a7%d9%84%d8%a8%d8%a7%d9%86%d8%af%d8%a7-%d9%8a%d8%ae%d8%aa%d8%a7%d8%b1-%d8%a7%d9%84%d8%a7%d9%94%d8%b9%d9%85%d8%af%d8%a9-%d8%a8%d8%a7%d9%84%d8%a7%d8%b3%d9%85\/"},"modified":"2023-07-17T12:20:03","modified_gmt":"2023-07-17T12:20:03","slug":"%d8%a7%d9%84%d8%a8%d8%a7%d9%86%d8%af%d8%a7-%d9%8a%d8%ae%d8%aa%d8%a7%d8%b1-%d8%a7%d9%84%d8%a7%d9%94%d8%b9%d9%85%d8%af%d8%a9-%d8%a8%d8%a7%d9%84%d8%a7%d8%b3%d9%85","status":"publish","type":"post","link":"https:\/\/statorials.org\/ar\/%d8%a7%d9%84%d8%a8%d8%a7%d9%86%d8%af%d8%a7-%d9%8a%d8%ae%d8%aa%d8%a7%d8%b1-%d8%a7%d9%84%d8%a7%d9%94%d8%b9%d9%85%d8%af%d8%a9-%d8%a8%d8%a7%d9%84%d8%a7%d8%b3%d9%85\/","title":{"rendered":"\u0643\u064a\u0641\u064a\u0629 \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0628\u0627\u0644\u0627\u0633\u0645 \u0641\u064a pandas (3 \u0623\u0645\u062b\u0644\u0629)"},"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\u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u062d\u0633\u0628 \u0627\u0644\u0627\u0633\u0645 \u0641\u064a pandas DataFrame:<\/span><\/p>\n

\u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u0623\u0648\u0644\u0649: \u062a\u062d\u062f\u064a\u062f \u0639\u0645\u0648\u062f \u0628\u0627\u0644\u0627\u0633\u0645<\/strong><\/span><\/p>\n

 df. loc<\/span> [:, ' column1<\/span> ']\n<\/strong><\/pre>\n
 \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u062b\u0627\u0646\u064a\u0629: \u062a\u062d\u062f\u064a\u062f \u0623\u0639\u0645\u062f\u0629 \u0645\u062a\u0639\u062f\u062f\u0629 \u0628\u0627\u0644\u0627\u0633\u0645<\/strong><\/span><\/p>\n
 df. loc<\/span> [:,[' column1<\/span> ',' column3<\/span> ',' column4<\/span> ']]<\/strong><\/pre>\n
 \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u062b\u0627\u0644\u062b\u0629: \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0641\u064a \u0627\u0644\u0646\u0637\u0627\u0642 \u062d\u0633\u0628 \u0627\u0644\u0627\u0633\u0645<\/strong><\/span><\/p>\n
 df. loc<\/span> [:, ' column2<\/span> ':' column4<\/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 \u0645\u0646 \u0647\u0630\u0647 \u0627\u0644\u0637\u0631\u0642 \u0639\u0645\u0644\u064a\u064b\u0627 \u0645\u0639 \u0648\u062d\u062f\u0627\u062a \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\n<\/span>df = pd. DataFrame<\/span> ({' mavs<\/span> ': [10, 12, 14, 15, 19, 22, 27],\n                   ' cavs<\/span> ': [18, 22, 19, 14, 14, 11, 20],\n                   ' hornets<\/span> ': [5, 7, 7, 9, 12, 9, 14],\n                   ' spurs<\/span> ': [10, 12, 14, 13, 13, 19, 22],\n                   ' net<\/span> ': [10, 14, 25, 22, 25, 17, 12]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n   mavs cavs hornets spurs nets\n0 10 18 5 10 10\n1 12 22 7 12 14\n2 14 19 7 14 25\n3 15 14 9 13 22\n4 19 14 12 13 25\n5 22 11 9 19 17\n6 27 20 14 22 12\n<\/strong><\/span><\/pre>\n
 \u0645\u062b\u0627\u0644 1: \u062d\u062f\u062f \u0639\u0645\u0648\u062f\u064b\u0627 \u0628\u0627\u0644\u0627\u0633\u0645<\/strong><\/span><\/h2>\n
 \u064a\u0648\u0636\u062d \u0627\u0644\u0643\u0648\u062f \u0627\u0644\u062a\u0627\u0644\u064a \u0643\u064a\u0641\u064a\u0629 \u062a\u062d\u062f\u064a\u062f \u0639\u0645\u0648\u062f “\u0627\u0644\u0645\u062d\u0641\u0632\u0627\u062a” \u0641\u064a DataFrame:<\/span><\/p>\n
 #select column with name 'spurs'\n<\/span>df. loc<\/span> [:, ' spurs<\/span> ']\n\n0 10\n1 12\n2 14\n3 13\n4 13\n5 19\n6 22\nName: spurs, dtype: int64<\/span><\/span><\/strong><\/pre>\n
 \u064a\u062a\u0645 \u0625\u0631\u062c\u0627\u0639 \u0627\u0644\u0642\u064a\u0645 \u0627\u0644\u0645\u0648\u062c\u0648\u062f\u0629 \u0641\u064a \u0639\u0645\u0648\u062f “\u062a\u0648\u062a\u0646\u0647\u0627\u0645” \u0641\u0642\u0637.<\/span><\/p>\n
 \u0627\u0644\u0645\u062b\u0627\u0644 2: \u062a\u062d\u062f\u064a\u062f \u0623\u0639\u0645\u062f\u0629 \u0645\u062a\u0639\u062f\u062f\u0629 \u0628\u0627\u0644\u0627\u0633\u0645<\/strong><\/span><\/h2>\n
 \u064a\u0648\u0636\u062d \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u0629 \u0627\u0644\u0628\u0631\u0645\u062c\u064a\u0629 \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0643\u064a\u0641\u064a\u0629 \u062a\u062d\u062f\u064a\u062f \u0623\u0639\u0645\u062f\u0629 \u0627\u0644\u0643\u0647\u0648\u0641 \u0648\u0627\u0644\u0645\u0647\u0645\u0627\u0632\u0627\u062a \u0648\u0627\u0644\u0634\u0628\u0643\u0627\u062a \u0641\u064a DataFrame:<\/span><\/p>\n
 #select columns with names cavs, spurs, and nets\n<\/span>df. loc<\/span> [:, [' cavs<\/span> ', ' spurs<\/span> ', ' nets<\/span> ']]\n\n        cavs spurs nets\n0 18 10 10\n1 22 12 14\n2 19 14 25\n3 14 13 22\n4 14 13 25\n5 11 19 17\n6 20 22 12<\/span><\/span><\/strong><\/pre>\n
 \u064a\u062a\u0645 \u0625\u0631\u062c\u0627\u0639 \u0642\u064a\u0645 \u0627\u0644\u0643\u0647\u0648\u0641 \u0648\u0627\u0644\u0645\u0647\u0645\u0627\u0632\u0627\u062a \u0648\u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0627\u0644\u0634\u0628\u0643\u064a\u0629 \u0641\u0642\u0637.<\/span><\/p>\n
 \u0645\u062b\u0627\u0644 3: \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0641\u064a \u0646\u0637\u0627\u0642 \u062d\u0633\u0628 \u0627\u0644\u0627\u0633\u0645<\/strong><\/span><\/h2>\n
 \u064a\u0648\u0636\u062d \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u0629 \u0627\u0644\u0628\u0631\u0645\u062c\u064a\u0629 \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0643\u064a\u0641\u064a\u0629 \u062a\u062d\u062f\u064a\u062f \u0643\u0627\u0641\u0629 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0628\u064a\u0646 \u0627\u0644\u0623\u0633\u0645\u0627\u0621 “hornets” \u0648”net” \u0641\u064a DataFrame:<\/span><\/p>\n
 #select all columns between hornets and nets\n<\/span>df. loc<\/span> [:, ' hornets<\/span> ': ' nets<\/span> ']\n\n        hornets spurs nets\n0 5 10 10\n1 7 12 14\n2 7 14 25\n3 9 13 22\n4 12 13 25\n5 9 19 17\n6 14 22 12<\/span><\/span><\/strong><\/pre>\n
 \u064a\u062a\u0645 \u0625\u0631\u062c\u0627\u0639 \u0643\u0627\u0641\u0629 \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0627\u0644\u0645\u0648\u062c\u0648\u062f\u0629 \u0628\u064a\u0646 \u0627\u0644\u0627\u0633\u0645\u064a\u0646 “hornets” \u0648”net”.<\/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
 \u0627\u0644\u0628\u0627\u0646\u062f\u0627: \u0643\u064a\u0641\u064a\u0629 \u0646\u0642\u0644 \u0639\u0645\u0648\u062f \u0623\u0645\u0627\u0645 DataFrame<\/a>
 \u0627\u0644\u0628\u0627\u0646\u062f\u0627: \u0643\u064a\u0641\u064a\u0629 \u0627\u0644\u062a\u062d\u0642\u0642 \u0645\u0645\u0627 \u0625\u0630\u0627 \u0643\u0627\u0646 \u0627\u0644\u0639\u0645\u0648\u062f \u064a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 \u0633\u0644\u0633\u0644\u0629<\/a>
 \u0627\u0644\u0628\u0627\u0646\u062f\u0627: \u0643\u064a\u0641\u064a\u0629 \u0625\u0636\u0627\u0641\u0629 \u0639\u0645\u0648\u062f \u0641\u0627\u0631\u063a \u0625\u0644\u0649 DataFrame (3 \u0623\u0645\u062b\u0644\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\u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u062d\u0633\u0628 \u0627\u0644\u0627\u0633\u0645 \u0641\u064a pandas DataFrame: \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u0623\u0648\u0644\u0649: \u062a\u062d\u062f\u064a\u062f \u0639\u0645\u0648\u062f \u0628\u0627\u0644\u0627\u0633\u0645 df. loc [:, ‘ column1 ‘] \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u062b\u0627\u0646\u064a\u0629: \u062a\u062d\u062f\u064a\u062f \u0623\u0639\u0645\u062f\u0629 \u0645\u062a\u0639\u062f\u062f\u0629 \u0628\u0627\u0644\u0627\u0633\u0645 df. loc [:,[‘ column1 ‘,’ column3 ‘,’ column4 ‘]] \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u062b\u0627\u0644\u062b\u0629: \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0641\u064a \u0627\u0644\u0646\u0637\u0627\u0642 \u062d\u0633\u0628 \u0627\u0644\u0627\u0633\u0645 df. loc [:, ‘ column2 ‘:’ column4 ‘] \u062a\u0648\u0636\u062d \u0627\u0644\u0623\u0645\u062b\u0644\u0629 […]<\/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 \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0628\u0627\u0644\u0627\u0633\u0645 \u0641\u064a \u0627\u0644\u0628\u0627\u0646\u062f\u0627 (3 \u0623\u0645\u062b\u0644\u0629) - \u0627\u0644\u0625\u062d\u0635\u0627\u0626\u064a\u0627\u062a<\/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 \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u062d\u0633\u0628 \u0627\u0644\u0627\u0633\u0645 \u0641\u064a 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-\u064a\u062e\u062a\u0627\u0631-\u0627\u0644\u0627\u0654\u0639\u0645\u062f\u0629-\u0628\u0627\u0644\u0627\u0633\u0645\/\" \/>\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 \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u0628\u0627\u0644\u0627\u0633\u0645 \u0641\u064a \u0627\u0644\u0628\u0627\u0646\u062f\u0627 (3 \u0623\u0645\u062b\u0644\u0629) - \u0627\u0644\u0625\u062d\u0635\u0627\u0626\u064a\u0627\u062a\" \/>\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 \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0623\u0639\u0645\u062f\u0629 \u062d\u0633\u0628 \u0627\u0644\u0627\u0633\u0645 \u0641\u064a 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-\u064a\u062e\u062a\u0627\u0631-\u0627\u0644\u0627\u0654\u0639\u0645\u062f\u0629-\u0628\u0627\u0644\u0627\u0633\u0645\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-17T12:20:03+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 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