Top 9 VS Code Extensions for Data Scientists

Visual Studio Code (VS Code) is a popular code editor for data scientists and developers alike. It is known for its ease of use, comprehensive feature set, and active developer community. In this article, we will explore some of the key features of VS Code that make it a great choice for data science workflows.

One of the standout features of VS Code is its support for multiple languages and platforms. It is built on top of the Electron framework, which allows it to run on Windows, Mac, and Linux operating systems. It also supports a wide range of programming languages, including Python, R, and Julia. This makes it a versatile choice for data scientists who may work with a variety of languages and tools.

In this article I will be discussing about the most important VScode extensions that have helped me throughout the process of learning data sciences. Extensions are packages of code that add new features or modify existing ones in the editor. There are hundreds of extensions available for VS Code, covering a wide range of purposes and languages and sometimes students get confused while choosing. So here I am to help you out with my experience on using Extension in VS Code.

Installing Extensions in VScode

To install an extension in Visual Studio Code (VS Code), follow these steps:

1. Open VS Code and click the “Extensions” icon on the left sidebar, or press “Ctrl + Shift + X” to open the Extensions panel.
2. In the Extensions panel, search for the extension you want to install. You can use the search bar to find specific extensions, or browse through the available categories to find something that interests you.
3. When you find the extension you want to install, click the “Install” button next to it.
4. VS Code will download and install the extension, and it will be automatically activated and available for use.

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You can also install extensions from the command line by using the “code” command. For example, to install the “Python” extension, you can run the following command:

code --install-extension ms-python.python

1. Kite Autocomplete

Kite is an AI-powered autocomplete plugin for Visual Studio Code (VS Code) that helps programmers write code faster by providing context-aware suggestions as they type. Kite integrates with VS Code to provide real-time autocomplete suggestions as users type. It uses machine learning techniques to analyze the user’s code and provide relevant suggestions based on their code context and the patterns in their codebase.

Kite is designed to be lightweight and easy to use. It runs in the background and provides suggestions as users type, without requiring any explicit action from the user. It also includes features such as documentation lookup and examples from open source code repositories, which can help users learn about new libraries and functions.

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2. Intellicode

IntelliCode is an extension for Visual Studio Code (VS Code) that provides intelligent code completion suggestions based on machine learning techniques. It uses machine learning models to analyze patterns in popular open source repositories on GitHub and provide context-aware code suggestions as users type.

IntelliCode helps developers write code faster by providing relevant suggestions based on the user’s code context and the patterns in their codebase. It also includes documentation lookup and examples from open source code repositories, which can help users learn about new libraries and functions.

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3. Python Environment Pack

The Python Extension Pack is a collection of extensions for Visual Studio Code (VS Code) that are useful for Python development. It includes extensions for language support, debugging, testing, code formatting, and more. Some of the extensions included in the Python Extension Pack are:

1. Python: This extension provides language support for Python, including features such as IntelliSense (code completion), linting, and debugging.
2. Debugpy: This extension allows users to debug Python code using the Debugpy library.
3. PyTest: This extension allows users to run PyTest tests and view test results in VS Code.
4. Black: This extension is a code formatter that uses the Black library to automatically format Python code according to a set of predefined rules.
5. YAML: This extension provides language support for YAML, a popular data serialization language often used in Python projects.

4. Python Indent

There are several extensions available for Visual Studio Code (VS Code) that can help with Python indentation. Some popular options include:

1. Python Indent: This extension automatically adjusts the indentation of Python code as it is written or pasted into VS Code. It can help users avoid common indentation errors and ensure that their code adheres to the PEP 8 style guide.
2. Better Python Indent: This extension improves upon the default Python indentation behavior in VS Code. It includes features such as support for multi-line statements and automatic detent after certain statements.

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It helps in understanding lengthy codes.

5. Arepl

Arepl (A Read-Eval-Print Loop) is an extension for Visual Studio Code (VS Code) that allows users to evaluate code snippets and see the results in real-time as they type. It is similar to a Python REPL (Read-Eval-Print Loop), but it supports a wide range of programming languages.

With Arepl, users can type in code snippets and see the results immediately, without having to run the code in a separate terminal or debugger. This can be helpful for quickly testing code ideas or trying out new libraries and functions. Arepl also includes features such as automatic indentation and syntax highlighting for multiple languages.

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6. Github Pull and Push

There are several extensions available for Visual Studio Code (VS Code) that can help with pulling and pushing code to and from GitHub. Some popular options include:

1. GitHub Pull Requests and Issues: This extension allows users to view, create, and manage pull requests and issues directly from VS Code. It includes features such as code review, project tracking, and collaboration tools.
2. GitLens: This extension provides advanced Git functionality for VS Code, including features such as blame annotations, code lens, and visual diffs. It also includes tools for working with pull requests and collaborating with others on GitHub.
3. GitHub Extension for Visual Studio: This extension allows users to connect to their GitHub accounts and work with Git repositories directly from VS Code. It includes features such as pull request and issue tracking, as well as tools for code review and collaboration

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This makes life much easier while using github along with VScode. You just have to connect your github account with VScode and download this extension.

7. Jupyter Notebook, Jupyter Notebook Renderer

The Jupyter Notebook is a popular web-based interactive computing platform for data science and machine learning. It allows users to mix code, text, and visualizations in a single document, known as a “notebook.”

There are several extensions available for Visual Studio Code (VS Code) that allow users to work with Jupyter notebooks. Some popular options include:

1. Jupyter Extension for Visual Studio Code: This extension allows users to open, edit, and run Jupyter notebooks directly in VS Code. It includes features such as syntax highlighting, code completion, and IntelliSense.
2. Jupyter Notebook Renderer: This extension allows users to view Jupyter notebooks as static HTML files in VS Code. It can be helpful for previewing notebooks before committing them to a repository or sharing them with others.

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8. Markdown All in One

Markdown All in One is an extension for Visual Studio Code (VS Code) that provides a set of tools for working with Markdown files. Markdown is a lightweight markup language that is often used for formatting text in README files, documentation, and other types of written content.

The Markdown All in One extension includes a number of features that can make working with Markdown files easier, including:

1. Syntax highlighting: This feature provides syntax highlighting for Markdown files, making it easier to read and write Markdown code.
2. Table formatting: This feature allows users to easily create and edit tables in Markdown files using a simple table editor.
3. Task lists: This feature allows users to create task lists in Markdown files using checkboxes, making it easy to track progress and organize tasks.
4. Snippets: This feature provides a set of snippets that can be inserted into Markdown files to help users write common elements such as headings, lists, and links.

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A very handy tool for creating notebooks for publishing or for Data Science Project.

9. Codesnap

Code Snap is an extension for Visual Studio Code (VS Code) that allows users to take snapshots of their code and compare them to previous versions. It is useful for tracking changes to code over time and identifying differences between versions.

With Code Snap, users can take snapshots of their code at any time and save them to a local repository. They can then view and compare the snapshots to see what has changed between versions. Code Snap includes features such as syntax highlighting and line-by-line comparison, which can make it easier to identify differences between versions.

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Codesnap can be very helpful if you are presenting your work for a course project or to your technical manager. Normaly its not advised to put code on your presentations but sometimes you are interested to show how you solved a particular problem. So Codesnap is the answer.

I hope these Extensions will make your lives easier and your data learning journey interesting. If you know some good extensions please mention in the comments.

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