Anaconda · Data Analysis

Python for Data Science using Anaconda

I am a lazy guy, when I already have my setup environment, it is hard for me to move on. In my lovely MacBook, I had Python with python virtual environments (virtualenv), of course, one of my virtualenv has a complete data science libraries. I used this virtualenv when I want to do data analysis. I also had experiences using docker-machine to be more productive and reproducible in analyzing data but it is heavy so I keep using virtualenv.

I have heard about Anaconda or conda which is the platform that bundles all data science libraries to one plate and you just enjoy it, but I never tried yet. Still, it is hard to move on. Then, after I have a new computer in my office and it is Windows. I wanted to start working with data using Python in my computer and I tried to remember what steps I have to do? Installing Python, installing PIP, installing virtualenv, installing virtualenv wrapper, installing all data science libraries to one of my virtualenv, and start working.

As the lazy guy, I do not want to do that. I went to anaconda website and I decided to try Anaconda and tarrraa!!!!!!!!

Just go to download the installer which matches with your operating system, install it then launch the Anaconda Navigator.


It was surprising me, I even can run Rstudio using Anaconda Navigator. If you enjoy using Jupyter (IPython Notebook), you just need to press launch for the Jupyter. It is also supported by one of beautiful IDE to do data analysis in Python which is Spider. It is really cool. Previously when I used R, I always use Rstudio as my IDE to do data analysis and now if you want to move to Python, you can use a similar IDE which is Spider.

If you want to know what kind of data science libraries that you need to install manually if you don’t want to use Anaconda, please visit this link. The picture below describes the Python environment for Data Science which may useful for you:

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