{"id":3274,"date":"2023-07-18T08:25:19","date_gmt":"2023-07-18T08:25:19","guid":{"rendered":"https:\/\/statorials.org\/ar\/np-%d8%a7%d9%94%d9%88-%d8%a7%d9%84%d8%a8%d8%a7%d9%86%d8%af%d8%a7\/"},"modified":"2023-07-18T08:25:19","modified_gmt":"2023-07-18T08:25:19","slug":"np-%d8%a7%d9%94%d9%88-%d8%a7%d9%84%d8%a8%d8%a7%d9%86%d8%af%d8%a7","status":"publish","type":"post","link":"https:\/\/statorials.org\/ar\/np-%d8%a7%d9%94%d9%88-%d8%a7%d9%84%d8%a8%d8%a7%d9%86%d8%af%d8%a7\/","title":{"rendered":"\u0627\u0644\u0628\u0627\u0646\u062f\u0627: \u0643\u064a\u0641\u064a\u0629 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u0627 \u064a\u0639\u0627\u062f\u0644 np.where()"},"content":{"rendered":"<p><\/p>\n<hr>\n<p style=\";text-align:right;direction:rtl\"><span style=\"color: #000000;\">\u064a\u0645\u0643\u0646\u0643 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0648\u0638\u064a\u0641\u0629 NumPy <a href=\"https:\/\/numpy.org\/doc\/stable\/reference\/generated\/numpy.where.html\" target=\"_blank\" rel=\"noopener\">Where()<\/a> \u0644\u062a\u062d\u062f\u064a\u062b \u0642\u064a\u0645 \u0645\u0635\u0641\u0648\u0641\u0629 NumPy \u0628\u0633\u0631\u0639\u0629 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u0646\u0637\u0642 if-else.<\/span><\/p>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0639\u0644\u0649 \u0633\u0628\u064a\u0644 \u0627\u0644\u0645\u062b\u0627\u0644\u060c \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\u062b \u0627\u0644\u0642\u064a\u0645 \u0641\u064a \u0645\u0635\u0641\u0648\u0641\u0629 NumPy \u0627\u0644\u062a\u064a \u062a\u0633\u062a\u0648\u0641\u064a \u0634\u0631\u0637\u064b\u0627 \u0645\u0639\u064a\u0646\u064b\u0627:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n\n<span style=\"color: #008080;\">#create NumPy array of values\n<\/span>x = np. <span style=\"color: #3366ff;\">array<\/span> ([1, 3, 3, 6, 7, 9])\n\n<span style=\"color: #008080;\">#update valuesin array based on condition\n<\/span>x = np. <span style=\"color: #3366ff;\">where<\/span> ((x &lt; 5) | (x &gt; 8), x\/2, x)\n\n<span style=\"color: #008080;\">#view updated array\n<\/span>x\n\narray([0.5, 1.5, 1.5, 6. , 7. , 4.5])\n<\/strong><\/pre>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0625\u0630\u0627<\/strong> \u0643\u0627\u0646\u062a \u0642\u064a\u0645\u0629 \u0645\u0639\u064a\u0646\u0629 \u0641\u064a \u0627\u0644\u062c\u062f\u0648\u0644 \u0623\u0642\u0644 \u0645\u0646 5 \u0623\u0648 \u0623\u0643\u0628\u0631 \u0645\u0646 8\u060c \u0641\u0625\u0646\u0646\u0627 \u0646\u0642\u0633\u0645 \u0627\u0644\u0642\u064a\u0645\u0629 \u0639\u0644\u0649 2.<\/span><\/p>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0648\u0625\u0644\u0627<\/strong> \u0641\u0625\u0646\u0646\u0627 \u0646\u062a\u0631\u0643 \u0627\u0644\u0642\u064a\u0645\u0629 \u062f\u0648\u0646 \u062a\u063a\u064a\u064a\u0631.<\/span><\/p>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u064a\u0645\u0643\u0646\u0646\u0627 \u0625\u062c\u0631\u0627\u0621 \u0639\u0645\u0644\u064a\u0629 \u0645\u0645\u0627\u062b\u0644\u0629 \u0641\u064a pandas DataFrame \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 <a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.DataFrame.where.html\" target=\"_blank\" rel=\"noopener\">pandaswhere()<\/a> \u060c \u0644\u0643\u0646 \u0628\u0646\u0627\u0621 \u0627\u0644\u062c\u0645\u0644\u0629 \u0645\u062e\u062a\u0644\u0641 \u0642\u0644\u064a\u0644\u0627\u064b.<\/span><\/p>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0641\u064a\u0645\u0627 \u064a\u0644\u064a \u0628\u0646\u0627\u0621 \u0627\u0644\u062c\u0645\u0644\u0629 \u0627\u0644\u0623\u0633\u0627\u0633\u064a \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 NumPywhere():<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>x = np. <span style=\"color: #3366ff;\">where<\/span> (condition, value_if_true, value_if_false)\n<\/strong><\/pre>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0648\u0625\u0644\u064a\u0643 \u0628\u0646\u0627\u0621 \u0627\u0644\u062c\u0645\u0644\u0629 \u0627\u0644\u0623\u0633\u0627\u0633\u064a \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0648\u0638\u064a\u0641\u0629 pandaswhere():<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df[' <span style=\"color: #ff0000;\">col<\/span> '] = (value_if_false). <span style=\"color: #3366ff;\">where<\/span> (condition, value_if_true)<\/strong><\/pre>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\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 \u0627\u0644\u062f\u0627\u0644\u0629 pandaswhere() \u0639\u0645\u0644\u064a\u064b\u0627.<\/span><\/p>\n<h2 style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0645\u062b\u0627\u0644: \u0645\u0627 \u064a\u0639\u0627\u062f\u0644 np.where() \u0641\u064a Pandas<\/strong><\/span><\/h2>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\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:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">A<\/span> ': [18, 22, 19, 14, 14, 11, 20, 28],\n                   ' <span style=\"color: #ff0000;\">B<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n    AB\n0 18 5\n1 22 7\n2 19 7\n3 14 9\n4 14 12\n5 11 9\n6 20 9\n7 28 4<\/strong><\/span><\/pre>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><span style=\"color: #000000;\">\u064a\u0645\u0643\u0646\u0646\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 <strong>pandaswhere()<\/strong> \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0644\u062a\u062d\u062f\u064a\u062b \u0627\u0644\u0642\u064a\u0645 \u0641\u064a \u0627\u0644\u0639\u0645\u0648\u062f A \u0628\u0646\u0627\u0621\u064b \u0639\u0644\u0649 \u0634\u0631\u0637 \u0645\u0639\u064a\u0646:<\/span><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#update values in column A based on condition\n<\/span>df[' <span style=\"color: #ff0000;\">A<\/span> '] = (df[' <span style=\"color: #ff0000;\">A<\/span> '] \/ 2). <span style=\"color: #3366ff;\">where<\/span> (df[' <span style=\"color: #ff0000;\">A<\/span> '] &lt; 20, df[' <span style=\"color: #ff0000;\">A<\/span> '] * 2)\n\n<span style=\"color: #008080;\">#view updated DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n      AB\n0 9.0 5\n1 44.0 7\n2 9.5 7\n3 7.0 9\n4 7.0 12\n5 5.5 9\n6 40.0 9\n7 56.0 4\n<\/span><\/span><\/strong><\/pre>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0625\u0630\u0627<\/strong> \u0643\u0627\u0646\u062a \u0642\u064a\u0645\u0629 \u0645\u0639\u064a\u0646\u0629 \u0641\u064a \u0627\u0644\u0639\u0645\u0648\u062f A \u0623\u0642\u0644 \u0645\u0646 20\u060c \u0641\u0625\u0646\u0646\u0627 \u0646\u0636\u0631\u0628 \u0627\u0644\u0642\u064a\u0645\u0629 \u0641\u064a 2.<\/span><\/p>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0648\u0625\u0644\u0627<\/strong> \u0641\u0625\u0646\u0646\u0627 \u0642\u0633\u0645\u0646\u0627 \u0627\u0644\u0642\u064a\u0645\u0629 \u0639\u0644\u0649 2.<\/span><\/p>\n<h2 style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0645\u0635\u0627\u062f\u0631 \u0625\u0636\u0627\u0641\u064a\u0629<\/strong><\/span><\/h2>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\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<p style=\";text-align:right;direction:rtl\"> <a href=\"https:\/\/statorials.org\/ar\/\u0627\u0644\u0628\u0627\u0646\u062f\u0627-\u062a\u062d\u0633\u0628-\u0627\u0644\u0642\u064a\u0645-\u0641\u064a-\u0627\u0644\u0639\u0645\u0648\u062f-\u0645\u0639-\u0627\u0644\u0634\u0631\u0637\/\" target=\"_blank\" rel=\"noopener\">\u0627\u0644\u0628\u0627\u0646\u062f\u0627: \u0643\u064a\u0641\u064a\u0629 \u062d\u0633\u0627\u0628 \u0627\u0644\u0642\u064a\u0645 \u0641\u064a \u0639\u0645\u0648\u062f \u0645\u0639 \u0627\u0644\u0634\u0631\u0637<\/a><br \/> <a href=\"https:\/\/statorials.org\/ar\/\u0627\u0644\u0628\u0627\u0646\u062f\u0627-\u0627\u0655\u0633\u0642\u0627\u0637-\u0627\u0644\u0635\u0641\u0648\u0641-\u0645\u0639-\u0627\u0644\u0634\u0631\u0637\/\" target=\"_blank\" rel=\"noopener\">\u0627\u0644\u0628\u0627\u0646\u062f\u0627: \u0643\u064a\u0641\u064a\u0629 \u062d\u0630\u0641 \u0627\u0644\u0635\u0641\u0648\u0641 \u0641\u064a DataFrame \u0628\u0646\u0627\u0621\u064b \u0639\u0644\u0649 \u0627\u0644\u062d\u0627\u0644\u0629<\/a><br \/> <a href=\"https:\/\/statorials.org\/ar\/\u062a\u0633\u062a\u0628\u062f\u0644-\u0627\u0644\u0628\u0627\u0646\u062f\u0627-\u0627\u0644\u0642\u064a\u0645-\u0641\u064a-\u0627\u0644\u0639\u0645\u0648\u062f-\u0628\u0646\u0627\u0621\u064b-\u0639\u0644\u0649-\u0627\u0644\u062d\u0627\u0644\u0629\/\" target=\"_blank\" rel=\"noopener\">\u0627\u0644\u0628\u0627\u0646\u062f\u0627: \u0643\u064a\u0641\u064a\u0629 \u0627\u0633\u062a\u0628\u062f\u0627\u0644 \u0627\u0644\u0642\u064a\u0645 \u0641\u064a \u0639\u0645\u0648\u062f \u0628\u0646\u0627\u0621\u064b \u0639\u0644\u0649 \u0627\u0644\u062d\u0627\u0644\u0629<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u064a\u0645\u0643\u0646\u0643 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0648\u0638\u064a\u0641\u0629 NumPy Where() \u0644\u062a\u062d\u062f\u064a\u062b \u0642\u064a\u0645 \u0645\u0635\u0641\u0648\u0641\u0629 NumPy \u0628\u0633\u0631\u0639\u0629 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u0646\u0637\u0642 if-else. \u0639\u0644\u0649 \u0633\u0628\u064a\u0644 \u0627\u0644\u0645\u062b\u0627\u0644\u060c \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\u062b \u0627\u0644\u0642\u064a\u0645 \u0641\u064a \u0645\u0635\u0641\u0648\u0641\u0629 NumPy \u0627\u0644\u062a\u064a \u062a\u0633\u062a\u0648\u0641\u064a \u0634\u0631\u0637\u064b\u0627 \u0645\u0639\u064a\u0646\u064b\u0627: import numpy as np #create NumPy array of values x = np. array ([1, 3, 3, 6, 7, 9]) #update valuesin array based on condition [&hellip;]<\/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":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u0627\u0644\u0628\u0627\u0646\u062f\u0627: \u0643\u064a\u0641\u064a\u0629 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u0627 \u064a\u0639\u0627\u062f\u0644 np.where() \u2013 \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 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u0627 \u064a\u0639\u0627\u062f\u0644 np.where() \u0641\u064a \u0627\u0644\u0628\u0627\u0646\u062f\u0627\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\/np-\u0627\u0654\u0648-\u0627\u0644\u0628\u0627\u0646\u062f\u0627\/\" \/>\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 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u0627 \u064a\u0639\u0627\u062f\u0644 np.where() \u2013 \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 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u0627 \u064a\u0639\u0627\u062f\u0644 np.where() \u0641\u064a \u0627\u0644\u0628\u0627\u0646\u062f\u0627\u060c \u0645\u0639 \u0639\u062f\u0629 \u0623\u0645\u062b\u0644\u0629.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ar\/np-\u0627\u0654\u0648-\u0627\u0644\u0628\u0627\u0646\u062f\u0627\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-18T08:25:19+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\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/ar\/np-%d8%a7%d9%94%d9%88-%d8%a7%d9%84%d8%a8%d8%a7%d9%86%d8%af%d8%a7\/\",\"url\":\"https:\/\/statorials.org\/ar\/np-%d8%a7%d9%94%d9%88-%d8%a7%d9%84%d8%a8%d8%a7%d9%86%d8%af%d8%a7\/\",\"name\":\"\u0627\u0644\u0628\u0627\u0646\u062f\u0627: \u0643\u064a\u0641\u064a\u0629 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u0627 \u064a\u0639\u0627\u062f\u0644 np.where() \u2013 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