Anaconda
Anaconda is a Python and R data science distribution that bundles the Conda package and environment manager, a large collection of prebuilt packages, and the Anaconda Navigator desktop application.
Installation and Setup
Download the installer for Windows, macOS, or Linux from the official website and follow the guided setup. After installation, update Conda and verify the setup:
$ conda --version
$ conda update conda
You can also use the Anaconda Navigator if you don’t want to deal with the terminal:
$ anaconda-navigator
Key Features
- Manages packages and environments across Python and compiled libraries using Conda
- Installs many prebuilt binary packages for scientific computing without requiring a separate compiler toolchain
- Provides Anaconda Navigator for managing environments and packages and launching tools from a GUI
- Supports multiple package sources known as channels, including Anaconda’s default channels and community channels like conda-forge
- Captures reproducible environments via explicit specifications, such as
environment.yml
Usage
Create an isolated environment and install packages:
$ conda create -n venv python=3.14
$ conda activate venv
$ conda install numpy pandas
List packages and export the environment:
$ conda list
$ conda env export > environment.yml
Install from a specific channel:
$ conda install -c conda-forge jupyterlab
You can use pip inside a Conda environment when a package isn’t available on your chosen channels. However, you should use a single package resolver for a given environment to keep dependency metadata consistent.
Related Resources
Course
Working With Python Virtual Environments
This course demonstrates how Python's virtual environments work as a "sandbox" and you get a quick walkthrough on how to set up a new environment (or virtualenv, as they're called for short) and how to install third-party packages into it using the pip command.
By Leodanis Pozo Ramos • Updated May 31, 2026