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Both languages are supported by open-source licenses (as opposed to commercial SAS and SPSS tools or proprietary MATLAB) and traditionally are considered the most popular. The rapid development of Data Science leads to a quick change of positions of these two programming languages. In this article, we will analyze the trends in the confrontation of Python vs R for data science, the advantages and disadvantages, and if it is possible to combine them.
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What programming language to choose? This is the eternal question for all IT specialists. Every forum is full of questions about which technology is better. But it is very hard to say for sure because the answer will vary depending on the needs, requirements, and peculiarities of a certain case. We compared Python and PHP, by such criteria: speed of development; performance; choice of web frameworks; talent pool; easiness of learning; documentation; debugging; library support; backend.
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Is it worth thinking about developing a mobile app in Python? Find out what are the peculiarities of Python mobile development and check some real-life examples. Read what you should take into account while building mobile apps in Python, what resources you need to develop a mobile app using Python, and more.
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What makes Python stand out in the development world? Fast development process, huge popularity, perfect choice for complex back-end, and more. Ideamotive provides industry and technology fitted tech talent for startups, scale-ups, and enterprises, as well as quality articles. In this one, you will learn what you need to take into account while hiring Python developers.
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Develop data-heavy apps, rank well on Google, keep the data safe, and make use of machine learning - all of this thanks to Django development, a high-level Python web framework. Ideamotive provides industry and technology fitted tech talent for startups, scale-ups, and enterprises, as well as quality articles. Read how to hire Django developers perfect for your next web project.