{"id":144692,"date":"2025-03-31T11:45:22","date_gmt":"2025-03-31T06:15:22","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=144692"},"modified":"2025-03-31T11:45:22","modified_gmt":"2025-03-31T06:15:22","slug":"numpy-filter-array","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/numpy-filter-array\/","title":{"rendered":"NumPy Filter Array"},"content":{"rendered":"<h3>Program 1<\/h3>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\">#Filter\r\nimport numpy as np\r\nmyar=[]\r\nprint(\"Enter Percentages of 10 student: \")\r\nfor i in range(1,11):\r\n    n=int(input())\r\n    myar.append(n)\r\n\r\nar=np.array(myar)    \r\nfilt_arr=[]\r\n\r\nfor x in ar:\r\n    if(x&gt;=60):\r\n        filt_arr.append(True)\r\n    else:\r\n      filt_arr.append(False)          \r\n\r\nnewar=ar[filt_arr]      \r\nprint(newar)\r\n\r\n# myar=[]\r\n# print(\"Enter 10 elements: \")\r\n# for i in range(1,11):\r\n#     n=int(input())\r\n#     myar.append(n)\r\n\r\n# ar=np.array(myar)\r\n\r\n# filt_arr=[]\r\n\r\n# for x in ar:\r\n#     if(x%2==0):\r\n#         filt_arr.append(True)\r\n#     else:\r\n#        filt_arr.append(False)\r\n\r\n# newar=ar[filt_arr]\r\n# print(ar)\r\n# print(newar)\r\n\r\n# print(ar)\r\n# print(filt_arr)            \r\n\r\n\r\n     \r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n# ar=np.array([1,4,6,8,5,10])\r\n# filt_arr=[True,False,True,True,False,False]\r\n# newar=ar[filt_arr]\r\n# print(ar)\r\n# print(filt_arr)\r\n# print(\"---------------------------------------\")\r\n# print(newar)<\/pre>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Program 1 #Filter import numpy as np myar=[] print(&#8220;Enter Percentages of 10 student: &#8220;) for i in range(1,11): n=int(input()) myar.append(n) ar=np.array(myar) filt_arr=[] for x in ar: if(x&gt;=60): filt_arr.append(True) else: filt_arr.append(False) newar=ar[filt_arr] print(newar) # myar=[]&#46;&#46;&#46;<\/p>\n","protected":false},"author":581,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[22401],"tags":[33927,33929,9170,33928,33926,31785,31784,9175],"class_list":["post-144692","post","type-post","status-publish","format-standard","hentry","category-numpy","tag-filter-array-in-numpy","tag-filter-in-numpy","tag-numpy","tag-numpy-filter","tag-numpy-filter-array","tag-numpy-practical","tag-numpy-program","tag-numpy-tutorial"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - 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DataFlair","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/data-flair.training\/blogs\/numpy-filter-array\/","og_locale":"en_US","og_type":"article","og_title":"NumPy Filter Array - DataFlair","og_description":"Program 1 #Filter import numpy as np myar=[] print(\"Enter Percentages of 10 student: \") for i in range(1,11): n=int(input()) myar.append(n) ar=np.array(myar) filt_arr=[] for x in ar: if(x&gt;=60): filt_arr.append(True) else: filt_arr.append(False) newar=ar[filt_arr] print(newar) # myar=[]&#46;&#46;&#46;","og_url":"https:\/\/data-flair.training\/blogs\/numpy-filter-array\/","og_site_name":"DataFlair","article_publisher":"https:\/\/www.facebook.com\/DataFlairWS\/","article_published_time":"2025-03-31T06:15:22+00:00","author":"DataFlair Team","twitter_card":"summary_large_image","twitter_creator":"@DataFlairWS","twitter_site":"@DataFlairWS","twitter_misc":{"Written by":"DataFlair Team","Est. reading time":"1 minute"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/data-flair.training\/blogs\/numpy-filter-array\/#article","isPartOf":{"@id":"https:\/\/data-flair.training\/blogs\/numpy-filter-array\/"},"author":{"name":"DataFlair Team","@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/person\/c187795dc82ab948373cca526df7c445"},"headline":"NumPy Filter Array","datePublished":"2025-03-31T06:15:22+00:00","mainEntityOfPage":{"@id":"https:\/\/data-flair.training\/blogs\/numpy-filter-array\/"},"wordCount":5,"commentCount":0,"publisher":{"@id":"https:\/\/data-flair.training\/blogs\/#organization"},"keywords":["filter array in numpy","filter in numpy","Numpy","numpy filter","numpy filter array","numpy practical","numpy program","NumPy Tutorial"],"articleSection":["NumPy Tutorials"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/data-flair.training\/blogs\/numpy-filter-array\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/data-flair.training\/blogs\/numpy-filter-array\/","url":"https:\/\/data-flair.training\/blogs\/numpy-filter-array\/","name":"NumPy Filter Array - 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