{"id":7778,"date":"2025-10-22T07:02:44","date_gmt":"2025-10-22T07:02:44","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/10\/22\/hidden-gems-in-numpy-7-functions-every-data-scientist-should-know\/"},"modified":"2025-10-22T07:02:44","modified_gmt":"2025-10-22T07:02:44","slug":"hidden-gems-in-numpy-7-functions-every-data-scientist-should-know","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/10\/22\/hidden-gems-in-numpy-7-functions-every-data-scientist-should-know\/","title":{"rendered":"Hidden Gems in NumPy: 7 Functions Every Data Scientist Should Know"},"content":{"rendered":"<p>    Hidden Gems in NumPy: 7 Functions Every Data Scientist Should Know<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>\n<p>I\u2019ve been learning data analytics for a year now. So far, I can consider myself confident in SQL and Power BI. The transition to Python has been quite exciting. I\u2019ve been exposed to some neat and smarter approaches to data analysis. After brushing up on my skills on the Python fundamentals, the ideal next step [\u2026]<\/p>\n<p>The post <a href=\"https:\/\/towardsdatascience.com\/hidden-gems-in-numpy-7-functions-every-data-scientist-should-know\/\">Hidden Gems in NumPy: 7 Functions Every Data Scientist Should Know<\/a> appeared first on <a href=\"https:\/\/towardsdatascience.com\/\">Towards Data Science<\/a>.<\/p>\n<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    Ibrahim Salami<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/towardsdatascience.com\/hidden-gems-in-numpy-7-functions-every-data-scientist-should-know\/\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Hidden Gems in NumPy: 7 Functions Every Data Scientist Should Know I\u2019ve been learning data analytics for a year now. So far, I can consider myself confident in SQL and Power BI. The transition to Python has been quite exciting. I\u2019ve been exposed to some neat and smarter approaches to data analysis. After brushing up [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,243,83,82,913,160,238],"tags":[84,4066,2424],"class_list":["post-7778","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-data-analytics","category-data-science","category-data-visualization","category-numpy","category-programming","category-statistics","tag-data","tag-gems","tag-hidden"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/7778"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=7778"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/7778\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=7778"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=7778"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=7778"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}