However, Zeppelin has a few pitfalls such as no extension support to bring in a new functionality, unlike Jupyter which provides more than 80 extensions brought out by the Jupyter development community. It also allows the user to combine multiple paragraphs of code written in Python in one single line, which is helpful when there are a lot of iterations in the code. Apache has a host of advantages over Jupyter such as multi-user support and richer inbuilt data visualisation tools. Apache ZeppelinĪpache’s standalone data analysis product, Zeppelin is making news and is competing with the likes of Jupyter. One interesting feature of P圜harm is the presence of a sharp debugger with a graphical interface along with offering customisations. Apart from computation, it also supports Web Development languages such as HTML/CSS, Javascript, Angular.js among many other languages. Jupyter users will definitely agree with the packages Pycharm integrates with libraries such as Numpy and Matplotlib for numerical computing and data visualisation in Python. P圜harm not only supports Python programming language, but also handles code written in SQL and similar database languages along the line.
P圜harmĪrdent users of Jupyter might try this similar notebook interface which offers better features. In this article, we explore the top five alternative notebooks for Jupyter that offers better features and flexibility along with having a different take when it comes to coding and its implementation. Though it is one of the most commonly used notebook in the data science fraternity, Jupyter has a few setbacks such as fragmented output code, version overlapping and so on. Jupyter is the offshoot project of IPython Notebook. Primarily used for data visualisation, Jupyter is flexible and supports most of the popular programming languages such as R, JavaScript, HTML/CSS, Node.js among others. Jupyter Notebook, popularly known as Jupyter among data science aficionados, is an open-source interactive coding application which allows the user/programmer a plethora of options such as testing code, equations, data visualisations, text and many more, using the Python programming language.
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