![]() Most data scientists who use Anaconda also work with Jupyter notebooks. Furthermore, Anaconda comes with a desktop GUI called Anaconda Navigator (see below), making it easy to launch applications and manage packages and environments without using command-line commands. Many essential libraries related to data science are already preinstalled, including NumPy, Pandas, matplotlib, etc. Glueviz: An open-source Python library for exploring data relationships.Orange: A python environment for data mining and visualization.Visual Studio (VS) Code: An IDE for professional purposes by Microsoft.RStudio: An environment for the programming language R.Spyder: Apython environment specifically designed for scientific purposes. ![]() Qt Console: A light-weight terminal application for visualization.Pycharm: A fully integrated python programming environment for professional purposes.Jupyter Notebooks: They are open-source web applications that support creating and sharing code, equations, visualizations, and narrative text.Below is a brief description of these tools: ![]() In addition, Anaconda has an integrated package manager that provides access to several tools and frameworks used in data science and software engineering, including Spyder, RStudio, Visual Studio Code, and Jupyter Notebooks. First of all, Anaconda includes a Python distribution, so there is no need for a separate Python installation. For various reasons, Anaconda has become the most popular Python environment for machine learning.
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