{"id":145049,"date":"2025-05-12T12:09:40","date_gmt":"2025-05-12T06:39:40","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=145049"},"modified":"2025-05-12T12:09:40","modified_gmt":"2025-05-12T06:39:40","slug":"filter-array-in-numpy","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/filter-array-in-numpy\/","title":{"rendered":"NumPy Filter Array"},"content":{"rendered":"<h3>Program 1<\/h3>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\">#Filter in Numpy\r\nimport numpy as np\r\n\r\n# mylist=[]\r\n# print(\"Enter Precentages: \")\r\n# for i in range(10):\r\n#     x=int(input())\r\n#     mylist.append(x)\r\n\r\n# myar=np.array(mylist)\r\n# my_filtr=[]\r\n# for per in np.nditer(myar):\r\n#     if(per&gt;=60):\r\n#         my_filtr.append(True)\r\n#     else:\r\n#         my_filtr.append(False)    \r\n\r\n# newar=myar[my_filtr]        \r\n\r\n# print(newar)\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n# mylist=[]\r\n# print(\"Enter 10 Elements: \")\r\n# for i in range(10):\r\n#     x=int(input())\r\n#     mylist.append(x)\r\n\r\n# myar=np.array(mylist)\r\n\r\n# print(myar)\r\n# my_filtr=[]\r\n\r\n# for m in np.nditer(myar):\r\n#     if(m%2==0):\r\n#         my_filtr.append(True)\r\n#     else:\r\n#         my_filtr.append(False)\r\n\r\n# newar=myar[my_filtr]\r\n# print(\"Even Numbers:\")\r\n\r\n# print(newar)\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#myar=np.array([5,2,7,8,10,20,40])\r\n# filt_ar=[True,False,True,True,False,False,True]\r\n# print(myar)\r\n# print(filt_ar)\r\n# newar=myar[filt_ar]\r\n# print(newar)<\/pre>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Program 1 #Filter in Numpy import numpy as np # mylist=[] # print(&#8220;Enter Precentages: &#8220;) # for i in range(10): # x=int(input()) # mylist.append(x) # myar=np.array(mylist) # my_filtr=[] # for per in np.nditer(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":[4692,33927,9170,33926,31785,31784,34194],"class_list":["post-145049","post","type-post","status-publish","format-standard","hentry","category-numpy","tag-filter","tag-filter-array-in-numpy","tag-numpy","tag-numpy-filter-array","tag-numpy-practical","tag-numpy-program","tag-numpy-program-on-filter"],"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\/filter-array-in-numpy\/","og_locale":"en_US","og_type":"article","og_title":"NumPy Filter Array - DataFlair","og_description":"Program 1 #Filter in Numpy import numpy as np # mylist=[] # print(\"Enter Precentages: \") # for i in range(10): # x=int(input()) # mylist.append(x) # myar=np.array(mylist) # my_filtr=[] # for per in np.nditer(myar): #&#46;&#46;&#46;","og_url":"https:\/\/data-flair.training\/blogs\/filter-array-in-numpy\/","og_site_name":"DataFlair","article_publisher":"https:\/\/www.facebook.com\/DataFlairWS\/","article_published_time":"2025-05-12T06:39:40+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\/filter-array-in-numpy\/#article","isPartOf":{"@id":"https:\/\/data-flair.training\/blogs\/filter-array-in-numpy\/"},"author":{"name":"DataFlair Team","@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/person\/c187795dc82ab948373cca526df7c445"},"headline":"NumPy Filter Array","datePublished":"2025-05-12T06:39:40+00:00","mainEntityOfPage":{"@id":"https:\/\/data-flair.training\/blogs\/filter-array-in-numpy\/"},"wordCount":5,"commentCount":0,"publisher":{"@id":"https:\/\/data-flair.training\/blogs\/#organization"},"keywords":["filter","filter array in numpy","Numpy","numpy filter array","numpy practical","numpy program","numpy program on filter"],"articleSection":["NumPy Tutorials"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/data-flair.training\/blogs\/filter-array-in-numpy\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/data-flair.training\/blogs\/filter-array-in-numpy\/","url":"https:\/\/data-flair.training\/blogs\/filter-array-in-numpy\/","name":"NumPy Filter Array - 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