Once you are done with the analysis and decision process and want to build a data science application, you may prefer to jump to Spyder. You may prefer Jupyter Notebook for data analysis, data visualization during the process of decisions and presentations. Spyder is not interactive as Jupyter but more efficient for building a whole data science application.
Pycharm vs jupyterlab code#
Again you can code Python here but there are some differences with Jupyter Notebook.
Notice that JupyterLab and Notebook are launching differently.Īlso notice P圜harm and Spyder because they are our next topics.ĭo not forget that this is not the whole list. You see some programs under this distribution. Screenshot of programs under Anaconda Navigator by Ayşe Kübra Kuyucu Below is a screenshot from my Anaconda Navigator. You can manage the programs and all other features of Anaconda. You can open Jupyter Notebooks on multiple web tabs but if you are used to using IDEs, it might seem more user-friendly to use JupyterLab. It lets you collect multiple Jupyter Notebooks under one tab. It is very interactive and lets you run partial codes. You can also call it a web application under Anaconda.
It is a web-based program under Anaconda distribution and it lets you code Python. So if you want to continue on data science, learn more about Anaconda but if you want to build an app (that does not include data science) with Python, do not think about Anaconda much. These programs in Anaconda are specialized in data science (eg you can not develop a website). Jupyter Notebook and Spyder are two of these programs. It may contain more than one program in it.Ĭheck this link for a longer answer for what Python Distribution is.Īnaconda contains multiple programs that let you use Python. A Python distribution is a program that allows you to use Python. It is a Python (and also R) distribution. It is the packages and libraries that allow Python to do many different things.Īll the popular terms you see in the title are either a framework or a library or something about managing and using Python packages.īefore going further, here is a very quick, nice video that answers what Python is and the reasons why you should use Python. The key point about Python for our article is about packages. You can use it for many purposes as you use other programming languages. What is the relationship between P圜harm and Anaconda? What is the difference between JupyterLab and Jupyter Notebook? What is the difference between package, library, and framework? I will also be answering the following questions. If my short answers did not satisfy you and you want to learn more, I wrote more details in the article.
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