Creating a good work area is the most important factor to increase productivity. In this article, we will set up a working environment with the most suitable and mostly free apps for ourselves.
What Is Working Environment?
Working environments are virtual workspace where we create algorithms where we develop programs and manage datasets.
Creating a good workspace makes the tasks you perform easier and saves time. In this article, we’ll look at exactly how we can create a good work environment.
Some programs are paid, so if the recommended application is paid, we will note it, and you can find the price in the information box below.
Select Code Editor For Data Science
Code editors are diverse, there are currently 100s of code editors on the market. The code editors on this list were chosen not because they are popular, but because they are comfortable and convenient to use.
I have been using visual studio code for about 3 years, now I will share my experiences with you. Visual studio code may look like an ordinary text editor when it first comes, but since it is open-source, you can easily install plugins and create an IDE for yourself.
Its best features are open source so it can be developed endlessly, there are many plugins available for languages such as python, R. There are many plugins available for viewing datasets.
Vim is more difficult and more complex than other code editors. I wouldn’t recommend using it if you are a new user. However, once you get used to it, is very useful for editing code.
You can set up vim through My Master Designer and customize your Vim with plugins. Click here to access the article.
It is more compatible with Github than other code editors. You can work with Visual Studio Code and VIM plug-ins on Github, but Atom is very useful to work with GitHub.
The plugin pool is large, you can use it to write code with Python. However, there is an important minus that vim and visual studio code plugins are more advanced than Atom plugins.
DataGrip is an application that should be on the list, even if it is not a code editor. It helps programmers working with SQL a lot. If you are working with big data, it will be very useful to use DataGrip.
If you are a data scientist, you don’t just write code, we need office programs to present your project, to present data.
It will always be beneficial for you to have Word, Excel, Access, Powerpoint in your toolbox. These programs also have a free app, but we recommend Windows Office.
Anaconda offers very useful tools for a stand-alone data scientist, the foremost being Jupyter Notebook.
Providing free and high-quality tools, Anaconda provides great advantages to your computer. It is also very useful for managing your projects and building libraries.
Don’t you be tempted to publish your projects as open-source? Github still works, Github it’s the easiest way to check your codes.
You should use Github to fix the fatal mistakes you make, and if you are developing code with a group, it is great for controlling each other’s changes.