– It includes Python itself and a collection of pre-installed data science packages. – Streamlines the setup process for data-driven projects. – It includes popular tools like Jupyter Notebook, NumPy, Pandas, and more. – for easier managing different project dependencies.
- Python: General-purpose language, suitable for various tasks beyond data science. - Anaconda: Tailored for data science and scientific computing, offering a curated set of relevant tools.
– Python: It is easy to learn for beginners due to its clear and concise syntax. - Anaconda: Setting up an Anaconda environment is simpler, especially for Data Science projects, but requires some understanding of package management (conda) compared to using pip in vanilla Python.