According<\/em> to various job advertisements for different data science positions, both Python<\/strong> and R belong to the most commonly mentioned and preferred skills. But a lot of studies have revealed that Python programming<\/strong> language is being used more by data scientists. But what exactly makes this language a preferred one for data scientists? In this post, we\u2019ve tried to find out the answer.<\/p>\n

What makes Python ideal for data science?<\/em><\/strong><\/h3>\n

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Here\u2019re the key reasons why Python<\/strong> is being considered among the fastest-growing languages across the world.<\/p>\n

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• A complete package: Apart from being a general-purpose language, Python<\/strong> is tailor-made for every data analysis task. Data scientists need to use lots of algorithms for which the language is tailor-made as well.<\/li>\n
• Easy implementation: For any data scientist it\u2019s crucial to understand the language before going into intricate details of artificial intelligence or machine learning. Since Python<\/strong> is popular as a beginner\u2019s language and doesn\u2019t come with a steep learning curve, they don\u2019t need to think about spending time on learning how to code using this language. Python programming<\/strong> language is popular for making programs work well with the minimal lines of codes possible. This simplicity is one of the biggest factors that have helped Python<\/strong> achieve this place.<\/li>\n
• Libraries and scalability: All the libraries preferred by data scientists are available in Python<\/strong>. It also comes with a significant number of exclusive libraries. In addition, Python<\/strong> has become the best scalable language as one can develop concrete applications with ease. This feature is ideal for data scientists working to develop certain data analysis applications and models.<\/li>\n
• Massive community: Python<\/strong> is accompanied by a robust community. This community is highly cooperative and there\u2019re people who\u2019re making the job of data scientists easy by helping them in different ways. If you\u2019re a data scientist and experiencing some issues related to Python<\/strong>, most likely you\u2019ll get the answer by presenting your query to a Python<\/strong><\/li>\n<\/ul>\n

  Apart from all these, the ability to perform machine learning tasks is probably the biggest factor that has given Python programming<\/strong> language a solid edge over its competitors. It\u2019s equipped with almost all the packages a data scientist may ever need. From scientific computing and statistical modeling to linear algebra and symbolic algebra, and many more \u2013 one can find the required packages readily available.<\/p>\n

  Keeping<\/em> the above advantages of Python<\/strong> in mind, it can be said that it has become imperative for aspiring data scientists to obtain a Python certification<\/strong>. As a Python certification<\/strong> holder, you\u2019ll be able to add tremendous value to your resume and to make the path of becoming a data scientist somewhat easier than those who don\u2019t. In addition, if you\u2019re looking to switch your career and step into the field of data science, it\u2019ll be easier to demonstrate that you\u2019ve got the requisite knowledge to manage various data-related projects when you\u2019ve got a Python certification<\/strong>. And finally, as a certified Python professional, you\u2019ll be able to get better jobs coupled with bigger salaries.<\/p>\n