The Most Trusted Distribution for Data Science
Anaconda® is a package manager, an environment manager, a Python/R data science distribution, and a collection of over 7,500+ open-source packages. Anaconda is free and easy to install, and it offers free community support.
Want to install conda and use conda to install just the packages you need? Get Miniconda.
Anaconda Navigator or conda?
After you install Anaconda or Miniconda, if you prefer a desktop graphical user interface (GUI) then use Navigator. If you prefer to use Anaconda prompt (or terminal on Linux or macOS), then use that and conda. You can also switch between them.
You can install, remove, or update any Anaconda package with a few clicks in Navigator, or with a single conda command in Anaconda Prompt (terminal on Linux or macOS).
- To try Navigator, after installing Anaconda, click the Navigator icon on your
operating system’s program menu, or in Anaconda prompt (or terminal on Linux or
macOS), run the command
- To try conda, after installing Anaconda or Miniconda, take the 30-minute conda test drive and download a conda cheat sheet.
Packages available in Anaconda
- Over 250 packages are automatically installed with Anaconda.
- Over 7,500 additional open-source packages (including R) can be individually installed from the
Anaconda repository with the
- Thousands of other packages are available from Anaconda Cloud.
- You can download other packages using the
pip installcommand that is installed with Anaconda. Pip packages provide many of the features of conda packages and in some cases they can work together. However, the preference should be to install the conda package if it is available.
- You can also make your own custom packages using
conda buildcommand, and you can share them with others by uploading them to Anaconda Cloud, PyPI, or other repositories.
Anaconda2 includes Python 2.7 and Anaconda3 includes Python 3.7. However, it does not matter which one you download, because you can create new environments that include any version of Python packaged with conda. See Managing Python with conda.