Data Scientist’s Starter Pack

Data Scientist’s Starter Pack

Must-have tools to master with working on data science projects. In this article, I will mainly focus on some of the most important tools to have and work with, tools which allow better and cleaner codingand faster way of collaboration.

When working on a data science project, many skills might be required from theoretical to technical ones. In this article, I will mainly focus on some of the most important tools to have and work with, tools which allow better and cleaner codingand faster way of collaboration.

Table of content

The summary is as follows:

  1. Visual Studio Code
  2. Bash commands
  3. Virtual environment
  4. Git & Github

1. Visual Studio Code

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The daily tasks of a data scientist are mainly about coding. For this reason, it is important to have a nice editor capable of encapsuling many other tools. VS code does that! It is a tool developed by Microsoft and considered to be one of the most used editors. It allows the run, edit and debug of the your code plus many other useful extensions such as:

  • Python: “A Visual Studio Code extension with rich support for the Python language, including features such as IntelliSense, linting, debugging, code navigation, code formatting, Jupyter notebook support, refactoring, variable explorer, test explorer, snippets, and more!”

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https://code.visualstudio.com

  • Gitlens : “GitLens supercharges the Git capabilities built into Visual Studio Code. It helps you to visualize code authorship at a glance via Git blame annotations and code lens, seamlessly navigate and explore Git repositories, gain valuable insights via powerful comparison commands, and so much more.”

virtual-environment vscode github terminal-commands data-science

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