{"id":2356,"date":"2023-07-22T15:17:04","date_gmt":"2023-07-22T15:17:04","guid":{"rendered":"https:\/\/statorials.org\/ar\/%d8%a7%d9%84%d8%a8%d8%a7%d9%86%d8%af%d8%a7-loc-%d8%b4%d8%b1%d9%88%d8%b7-%d9%85%d8%aa%d8%b9%d8%af%d8%af%d8%a9\/"},"modified":"2023-07-22T15:17:04","modified_gmt":"2023-07-22T15:17:04","slug":"%d8%a7%d9%84%d8%a8%d8%a7%d9%86%d8%af%d8%a7-loc-%d8%b4%d8%b1%d9%88%d8%b7-%d9%85%d8%aa%d8%b9%d8%af%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-loc-%d8%b4%d8%b1%d9%88%d8%b7-%d9%85%d8%aa%d8%b9%d8%af%d8%af%d8%a9\/","title":{"rendered":"\u0643\u064a\u0641\u064a\u0629 \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0635\u0641\u0648\u0641 \u0628\u0646\u0627\u0621\u064b \u0639\u0644\u0649 \u0634\u0631\u0648\u0637 \u0645\u062a\u0639\u062f\u062f\u0629 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 pandas loc"},"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 \u0635\u0641\u0648\u0641 \u0645\u0646 Pandas DataFrame \u0628\u0646\u0627\u0621\u064b \u0639\u0644\u0649 \u0639\u062f\u0629 \u0634\u0631\u0648\u0637:<\/span><\/p>\n

\u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u0623\u0648\u0644\u0649: \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0635\u0641\u0648\u0641 \u0627\u0644\u062a\u064a \u062a\u0633\u062a\u0648\u0641\u064a \u0634\u0631\u0648\u0637\u064b\u0627 \u0645\u062a\u0639\u062f\u062f\u0629<\/strong><\/span><\/p>\n

 df. loc<\/span> [((df[' col1<\/span> '] == ' A<\/span> ') &<\/span> (df['<\/span> col2' ]<\/span><\/span> == ' G<\/span> '))]\n<\/strong><\/pre>\n
 \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u062b\u0627\u0646\u064a\u0629: \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0635\u0641\u0648\u0641 \u0627\u0644\u062a\u064a \u062a\u0641\u064a \u0628\u0623\u062d\u062f \u0627\u0644\u0634\u0631\u0648\u0637 \u0627\u0644\u0645\u062a\u0639\u062f\u062f\u0629<\/strong><\/span><\/p>\n
 df. loc<\/span> [((df[' col1<\/span> '] > 10) |<\/span> (df['<\/span> col2' ]<\/span><\/span> < 8))]<\/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> ({' team<\/span> ': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],\n                   ' position<\/span> ': ['G', 'G', 'F', 'F', 'G', 'G', 'F', 'F'],\n                   ' assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' rebounds<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})\n\n#view DataFrame\n<\/span>df\n\n\tteam position assists rebounds\n0 A G 5 11\n1 A G 7 8\n2 A F 7 10\n3 A F 9 6\n4 B G 12 6\n5 B G 9 5\n6 B F 9 9\n7 B F 4 12\n<\/strong><\/pre>\n
 \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u0623\u0648\u0644\u0649: \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0635\u0641\u0648\u0641 \u0627\u0644\u062a\u064a \u062a\u0633\u062a\u0648\u0641\u064a \u0634\u0631\u0648\u0637\u064b\u0627 \u0645\u062a\u0639\u062f\u062f\u0629<\/strong><\/span><\/h3>\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 \u0627\u0644\u0635\u0641\u0648\u0641 \u0641\u0642\u0637 \u0645\u0646 DataFrame \u062d\u064a\u062b \u064a\u0633\u0627\u0648\u064a \u0627\u0644\u0641\u0631\u064a\u0642 “A” \u0648\u0627\u0644\u0645\u0648\u0636\u0639 \u064a\u0633\u0627\u0648\u064a “G”:<\/span><\/p>\n
 #select rows where team is equal to 'A' and position is equal to 'G'\ndf. loc<\/span> [((df[' team<\/span> '] == ' A<\/span> ') & (df[' position<\/span> '] == ' G<\/span> '))]\n\n\tteam position assists rebounds\n0 A G 5 11\n1 A G 7 8<\/span>\n<\/span><\/strong><\/pre>\n
 \u0644\u0645 \u064a\u0643\u0646 \u0647\u0646\u0627\u0643 \u0633\u0648\u0649 \u0635\u0641\u064a\u0646 \u0641\u064a DataFrame \u064a\u0633\u062a\u0648\u0641\u064a \u0643\u0644\u0627 \u0647\u0630\u064a\u0646 \u0627\u0644\u0634\u0631\u0637\u064a\u0646.<\/span><\/p>\n
 \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u062b\u0627\u0646\u064a\u0629: \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0635\u0641\u0648\u0641 \u0627\u0644\u062a\u064a \u062a\u0641\u064a \u0628\u0623\u062d\u062f \u0627\u0644\u0634\u0631\u0648\u0637 \u0627\u0644\u0645\u062a\u0639\u062f\u062f\u0629<\/strong><\/span><\/h3>\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 \u0627\u0644\u0635\u0641\u0648\u0641 \u0641\u0642\u0637 \u0641\u064a DataFrame \u062d\u064a\u062b \u062a\u0643\u0648\u0646 \u0627\u0644\u0645\u0633\u0627\u0639\u062f\u0629 \u0623\u0643\u0628\u0631 \u0645\u0646 10 \u0623\u0648<\/em> \u062a\u0643\u0648\u0646 \u0627\u0644\u0627\u0631\u062a\u062f\u0627\u062f\u0627\u062a \u0623\u0642\u0644 \u0645\u0646 8:<\/span><\/p>\n
 #select rows where assists is greater than 10 or rebounds is less than 8\ndf. loc<\/span> [((df[' assists<\/span> '] > 10) |<\/span> (df[' rebounds<\/span> '] < 8))]\n\n\tteam position assists rebounds\n3 A F 9 6\n4 B G 12 6\n5 B G 9 5<\/span>\n<\/span><\/strong><\/pre>\n
 \u0644\u0645 \u064a\u0643\u0646 \u0647\u0646\u0627\u0643 \u0633\u0648\u0649 \u062b\u0644\u0627\u062b\u0629 \u0635\u0641\u0648\u0641 \u0641\u064a DataFrame \u062a\u0633\u062a\u0648\u0641\u064a \u0647\u0630\u064a\u0646 \u0627\u0644\u0634\u0631\u0637\u064a\u0646.<\/span><\/p>\n
 \u0645\u0644\u0627\u062d\u0638\u0629:<\/strong> \u0641\u064a \u0647\u0630\u064a\u0646 \u0627\u0644\u0645\u062b\u0627\u0644\u064a\u0646\u060c \u0642\u0645\u0646\u0627 \u0628\u062a\u0635\u0641\u064a\u0629 \u0627\u0644\u0635\u0641\u0648\u0641 \u0628\u0646\u0627\u0621\u064b \u0639\u0644\u0649 \u0634\u0631\u0637\u064a\u0646\u060c \u0648\u0644\u0643\u0646 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 & \u0648 |<\/strong> \u0633\u0645\u0627\u062a<\/strong> . \u0627\u0644\u0645\u0634\u063a\u0644\u064a\u0646\u060c \u064a\u0645\u0643\u0646\u0646\u0627 \u0627\u0644\u062a\u0635\u0641\u064a\u0629 \u062d\u0633\u0628 \u0623\u064a \u0639\u062f\u062f \u0646\u0631\u064a\u062f\u0647 \u0645\u0646 \u0627\u0644\u0634\u0631\u0648\u0637.<\/span><\/p>\n
 \u0645\u0635\u0627\u062f\u0631 \u0625\u0636\u0627\u0641\u064a\u0629<\/strong><\/span><\/h3>\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
 \u0643\u064a\u0641\u064a\u0629 \u0625\u0646\u0634\u0627\u0621 \u0639\u0645\u0648\u062f \u062c\u062f\u064a\u062f \u0628\u0646\u0627\u0621\u064b \u0639\u0644\u0649 \u0634\u0631\u0637 \u0641\u064a Pandas<\/a>
 \u0643\u064a\u0641\u064a\u0629 \u062d\u0630\u0641 \u0627\u0644\u0635\u0641\u0648\u0641 \u0627\u0644\u062a\u064a \u062a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 \u0642\u064a\u0645\u0629 \u0645\u062d\u062f\u062f\u0629 \u0641\u064a Pandas<\/a>
 \u0643\u064a\u0641\u064a\u0629 \u0625\u0632\u0627\u0644\u0629 \u0627\u0644\u0635\u0641\u0648\u0641 \u0627\u0644\u0645\u0643\u0631\u0631\u0629 \u0641\u064a \u0627\u0644\u0628\u0627\u0646\u062f\u0627<\/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 \u0635\u0641\u0648\u0641 \u0645\u0646 Pandas DataFrame \u0628\u0646\u0627\u0621\u064b \u0639\u0644\u0649 \u0639\u062f\u0629 \u0634\u0631\u0648\u0637: \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u0623\u0648\u0644\u0649: \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0635\u0641\u0648\u0641 \u0627\u0644\u062a\u064a \u062a\u0633\u062a\u0648\u0641\u064a \u0634\u0631\u0648\u0637\u064b\u0627 \u0645\u062a\u0639\u062f\u062f\u0629 df. loc [((df[‘ col1 ‘] == ‘ A ‘) & (df[‘ col2’ ] == ‘ G ‘))] \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u062b\u0627\u0646\u064a\u0629: \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0635\u0641\u0648\u0641 \u0627\u0644\u062a\u064a \u062a\u0641\u064a \u0628\u0623\u062d\u062f \u0627\u0644\u0634\u0631\u0648\u0637 \u0627\u0644\u0645\u062a\u0639\u062f\u062f\u0629 df. loc [((df[‘ col1 ‘] > 10) | […]<\/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\u0635\u0641\u0648\u0641 \u0628\u0646\u0627\u0621\u064b \u0639\u0644\u0649 \u0634\u0631\u0648\u0637 \u0645\u062a\u0639\u062f\u062f\u0629 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 Pandas loc - - 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 \u062a\u062d\u062f\u064a\u062f \u0635\u0641\u0648\u0641 \u0645\u0646 Pandas DataFrame \u0628\u0646\u0627\u0621\u064b \u0639\u0644\u0649 \u0634\u0631\u0648\u0637 \u0645\u062a\u0639\u062f\u062f\u0629 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 loc().\" \/>\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-loc-\u0634\u0631\u0648\u0637-\u0645\u062a\u0639\u062f\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 \u062a\u062d\u062f\u064a\u062f \u0627\u0644\u0635\u0641\u0648\u0641 \u0628\u0646\u0627\u0621\u064b \u0639\u0644\u0649 \u0634\u0631\u0648\u0637 \u0645\u062a\u0639\u062f\u062f\u0629 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 Pandas loc - 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