Data Science toolkit Anaconda

Data Science toolkit Anaconda. In my previous blog, we had discussed about Data Scienceis. In this topic we will learn about Anaconda a free and open-source distribution of the Python and R programming languages for scientific computing (data science, machine learning applications, large-scale data processing, predictive analytics, etc.), that aims to simplify package management and deployment. The distribution includes data-science packages suitable for Windows, Linux, and macOS. It is developed and maintained by Anaconda, Inc., which was founded by Peter Wang and Travis Oliphant in 2012. As an Anaconda, Inc. product, it is also known as Anaconda Distribution or Anaconda Individual Edition, while other products from the company are Anaconda Team Edition and Anaconda Enterprise Edition, which are both not free.

With over 20 million users worldwide, the open-source Individual Edition (Distribution) is the easiest way to perform Python/R data science and machine learning on a single machine. Developed for solo practitioners, it is the toolkit that equips you to work with thousands of open-source packages and libraries. I recommend using Anaconda Navigator, a desktop graphical user interface (GUI) system that includes links to all the applications included with the distribution including RStudio, iPython, Jupyter Notebook, JupyterLab, Spyder, Glue, and Orange. The default environment is Python 3.6, but you can also easily install Python 3.5, Python 2.7, or R. The documentation is incredibly detailed and there is an excellent community of users for additional support. If you want to learn DataScience from  Easyshiksha.

Now You know what is Data Science toolkit Anaconda. I will breif you about Anaconda inbuild pacakages and the difference between Anaconda Navigator or conda.

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 anaconda-navigator.
• 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 conda install command.
• Thousands of other packages are available from Anaconda Cloud.
• You can download other packages using the pip install command 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 the conda build command, and you can share them with others by uploading them to Anaconda Cloud, PyPI, or other repositories.