You can learn more about different Python Integrated Development Environments here. It is also possible to integrate Anaconda with other Python Integrated Development Environments including P圜harm and Atom. An Integrated Development Environment is a coding tool which allows you to write, test and debug your code as they typically offer code completion, code insight by highlighting, resource management and debugging tools among many other features. Conda even makes it easy to switch between Python 2 and 3 (you can learn more here).Īnaconda comes with Spyder, a Python Integrated Development Environment. If you need additional packages after installing Anaconda, you can use Anaconda's package manager conda or pip to install those packages.This is highly advantageous as you don't have to manage dependencies between multiple packages yourself. You can learn more about Jupyter Notebooks here. Jupyter notebooks contain both code and rich text elements, such as figures, links, and equations. The image below shows a Jupyter Notebook in action. An installation of Anaconda comes with many packages such as numpy, scikit-learn, scipy, and pandas preinstalled and it is also the recommended way to install Jupyter Notebooks.

Benefits of AnacondaĪnaconda is a package manager, an environment manager, and Python distribution that contains a collection of many open source packages. There are many different python distributions, but for data science, the Anaconda Python Distribution is the most popular. To be able to use Python on your local computer, you first need to install it. This tutorial will let you know what packages, what softwares you need to install to get started with the various technologies. It is not always easy to know what you need to install for the various projects you have in mind. After learning on an online interactive training and education platform like Datacamp, one of the next steps is taking that skill gained in Python, R, Git, or Unix Shell and using it on your local computer.

Cygwin anaconda