<\/span><\/h2>\n\n\n\nBelow is the comparison graph of NumPy vs Pandas. However, the NumPy is in blue, and the Pandas is in red.<\/p>\n\n\n\nAs you can see, the search term for “NumPy” is unsteady and below pandas. On the other hand, Pandas have been gaining interest from people for the past 5 years. If we talk about which is better in terms of Google search, then the clear winner of this round is Pandas, but if we talk about features, then the clear answer is NumPy without any doubt.<\/p>\n\n\n\n
<\/span>Conclusion<\/span><\/h2>\n\n\n\nThis is the end of the blog, NumPy vs pandas. So, in conclusion, we can say that Pandas has been built on top of NumPy. On the other hand, both Python libraries have significant differences. Pandas and NumPy simplify matrix multiplication and are heavily used in data science and machine learning.<\/p>\n\n\n\n
Hence, we recommend this library to all today’s new programmers who want to learn these libraries to become machine learning, data science, researchers, or machine learning practitioners. As a result, this will not only open gates for them to grab a job at some of the biggest IT companies in the world but also help them in their day-to-day calculations to become good Data Science and Machine Learning experts.<\/p>\n\n\n\n
<\/span>FAQs <\/span><\/h2>\n\n\n\n
\n
\n
<\/span>Q1. Is NumPy faster than Pandas?<\/strong><\/span><\/h3>\n\n\n
If we talk about which one is faster, then indexing in NumPy arrays is very fast. On the other hand, indexing in the Pandas series is very slow. As a result, NumPy is way faster than Pandas.\u00a0<\/p>\n\n<\/div>\n<\/div>\n
\n
<\/span>Q2. Is Pandas same as NumPy?<\/strong><\/span><\/h3>\n\n\n
Like NumPy, Pandas is one of the world’s most widely used Python libraries in data science. On the other hand, it provides data analysis tools and high-performance, easy-to-use structures, unlike the NumPy library, which provides objects for multi-dimensional arrays. However, Pandas provides an in-memory 2D table object called a Dataframe.<\/p>\n\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n
<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/p>\n","protected":false},"excerpt":{"rendered":"
One of the world\u2019s most popular general-purpose programming languages is Python. If you are in the IT sector, then you must be familiar with Python. On the other hand, there are multiple reasons why it has become so popular in many fields, like software engineering, data science, machine learning, and many more. However, the main […]<\/p>\n","protected":false},"author":1,"featured_media":12176,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[77,138],"tags":[1630,1631,1626,1628,1624,1625,1627,1629],"class_list":["post-12173","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-science","category-programming","tag-is-numpy-faster-than-pandas","tag-is-pandas-same-as-numpy","tag-key-features-of-numpy-library","tag-key-features-of-pandas-library","tag-numpy-vs-pandas","tag-what-is-numpy","tag-what-is-pandas","tag-which-is-better-numpy-vs-pandas"],"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/posts\/12173","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/comments?post=12173"}],"version-history":[{"count":0,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/posts\/12173\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/media\/12176"}],"wp:attachment":[{"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/media?parent=12173"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/categories?post=12173"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/tags?post=12173"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}