{"id":14655,"date":"2022-10-08T16:14:32","date_gmt":"2022-10-08T10:44:32","guid":{"rendered":"https:\/\/jassweb.com\/solved\/solved-python-arrays-in-numpy\/"},"modified":"2022-10-08T16:14:32","modified_gmt":"2022-10-08T10:44:32","slug":"solved-python-arrays-in-numpy","status":"publish","type":"post","link":"https:\/\/jassweb.com\/solved\/solved-python-arrays-in-numpy\/","title":{"rendered":"[Solved] Python arrays in numpy"},"content":{"rendered":"<p> [ad_1]<br \/>\n<\/p>\n<div id=\"answer-49739254\" class=\"answer js-answer accepted-answer js-accepted-answer\" data-answerid=\"49739254\" data-parentid=\"49734812\" data-score=\"1\" data-position-on-page=\"1\" data-highest-scored=\"1\" data-question-has-accepted-highest-score=\"1\" itemprop=\"acceptedAnswer\" itemscope itemtype=\"https:\/\/schema.org\/Answer\">\n<div class=\"post-layout\">\n<div class=\"votecell post-layout--left\"><\/div>\n<div class=\"answercell post-layout--right\">\n<div class=\"s-prose js-post-body\" itemprop=\"text\">\n<p>Perhaps the closest thing in Python to this Javascript array behavior is a dictionary.  It&#8217;s a hashed mapping.<\/p>\n<p><code>defaultdict<\/code> is a dictionary that implements a default value.<\/p>\n<pre><code>In [1]: from collections import defaultdict\nIn [2]: arr = defaultdict(bool)\n<\/code><\/pre>\n<p>Insert a couple of <code>True<\/code> elements:<\/p>\n<pre><code>In [3]: arr[10] = True\nIn [4]: arr\nOut[4]: defaultdict(bool, {10: True})\nIn [5]: arr[20] = True\nIn [6]: arr\nOut[6]: defaultdict(bool, {10: True, 20: True})\n<\/code><\/pre>\n<p>Fetching some other element returns the <code>default<\/code> (<code>False<\/code> in this case), and adds it to the dictionary:<\/p>\n<pre><code>In [7]: arr[3]\nOut[7]: False\nIn [8]: arr\nOut[8]: defaultdict(bool, {3: False, 10: True, 20: True})\n<\/code><\/pre>\n<p><code>defaultdict(list)<\/code> is a handy way of collecting values in lists within the dictionary.  <code>defaultdict(int)<\/code> implements a counter.<\/p>\n<p><code>numpy<\/code> arrays have a fixed size, and specified <code>dtype<\/code>:<\/p>\n<pre><code>In [21]: x = np.zeros(8, bool)\nIn [22]: x[5]=True\nIn [23]: x\nOut[23]: array([False, False, False, False, False,  True, False, False])\n<\/code><\/pre>\n<p>You can make a new array by concatenating with something else (forget the <code>np.append<\/code> function).<\/p>\n<p>Python lists can be initialed to a empty size, <code>alist= []<\/code>, and can grow with <code>append<\/code> or <code>extend<\/code>.  But you can&#8217;t grow the list by indexing.<\/p>\n<\/p><\/div>\n<div class=\"mt24\"><\/div>\n<\/div>\n<p>            <span class=\"d-none\" itemprop=\"commentCount\">0<\/span> <\/p><\/div>\n<\/div>\n<p>[ad_2]<\/p>\n<p>solved Python arrays in numpy <\/p>\n","protected":false},"excerpt":{"rendered":"<p>[ad_1] Perhaps the closest thing in Python to this Javascript array behavior is a dictionary. It&#8217;s a hashed mapping. defaultdict is a dictionary that implements a default value. In [1]: from collections import defaultdict In [2]: arr = defaultdict(bool) Insert a couple of True elements: In [3]: arr[10] = True In [4]: arr Out[4]: defaultdict(bool, &#8230; <a title=\"[Solved] Python arrays in numpy\" class=\"read-more\" href=\"https:\/\/jassweb.com\/solved\/solved-python-arrays-in-numpy\/\" aria-label=\"More on [Solved] Python arrays in numpy\">Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[320],"tags":[361,821,581,349,482],"class_list":["post-14655","post","type-post","status-publish","format-standard","hentry","category-solved","tag-arrays","tag-indexing","tag-numpy","tag-python","tag-python-3-x"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>[Solved] Python arrays in numpy - JassWeb<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/jassweb.com\/solved\/solved-python-arrays-in-numpy\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"[Solved] Python arrays in numpy - JassWeb\" \/>\n<meta property=\"og:description\" content=\"[ad_1] Perhaps the closest thing in Python to this Javascript array behavior is a dictionary. 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