avatarManpreet Singh

Summary

The website article discusses a curated list of essential PyCharm extensions specifically tailored for data scientists to enhance their coding efficiency and productivity.

Abstract

The article "Awesome PyCharm Extensions For Data Scientists" introduces several PyCharm plugins designed to streamline the workflow of data science professionals. It begins by acknowledging the burgeoning field of Data Science and directs readers to a resource for foundational knowledge. The author then proceeds to highlight five key PyCharm extensions: Big Data Tools for interacting with various big data platforms, SonarLint for code quality checks, .CSV for easy editing of CSV/TSV/PSV files, Kite for AI-powered code autocompletion, and Highlight Bracket Pair for efficiently locating matching brackets in code. Each extension is accompanied by a description and a link to its respective marketplace for further exploration. The article concludes with an invitation for reader engagement and shares additional learning resources for programming and data science.

Opinions

  • The author expresses enthusiasm for Data Science as a career path, considering it one of their favorites.
  • Big Data Tools is praised for its ability to work with multiple big data tools, suggesting it is a valuable asset for data scientists.
  • SonarLint is recommended for its ability to detect and notify users of code issues, implying its importance in maintaining code quality.
  • The .CSV extension is highlighted as a personal favorite of the author, despite manual data editing being generally undesirable in data science, indicating its practicality in certain scenarios.
  • Kite is presented as a necessary tool for its AI-driven code completion capabilities, suggesting it can significantly boost coding speed.
  • Highlight Bracket Pair is deemed a must-have for any programming project, emphasizing its utility in navigating code syntax.
  • The author is open to feedback and connection with the audience, inviting readers to reach out on Twitter and providing a link to recommended programming resources.

Awesome PyCharm Extensions For Data Scientists

Welcome back! Data Science is an awesome career path with exploding growth, if you’re new to Data Science, check out the link below to learn more about it:

So, let’s talk about some awesome PyCharm extensions you can use as a data scientist!

Big Data Tools

First up we have Big Data Tools, this is an awesome plugin that allows you to interact with many different big data tools, including:

Check out the link below to learn more about it:

Sonar Lint

Next up we have Sonar Lint, an awesome extension for any data scientist for PyCharm. This specific extension essentially detects and notifies you of problems with your code, this includes mistakes in spelling and even flaws in syntax! If you want to check this extension out, here is the link:

.CSV

This is by far one of my favorite extensions for PyCharm, especially for any data related project. .CSV allows us to edit CSV/TSV and even PSV files very easily, this may seem like the exact opposite of what a data scientist should do (manual editing of data), but it doesn’t hurt to have this extension laying around. If you want to check this extension out, here is the link:

Kite

Next up we have Kite, this is another awesome extension that you need to install into PyCharm. This specific extension is a AI-powered coding assistant, this essentially autocompletes portions of your code! If you want to check this extension out, here is the link below:

Highlight Bracket Pair

Next up we have Highlight Bracket Pair, this is a must have for any programming project. This specific extension allows us to easily find pairs of brackets from your code, rather than having to manually look through and find your ending or beginning bracket. If you want to check this extension here, here is the link below:

There you have it! Those are some of the best PyCharm extensions you can use as a data scientist, do you plan on using these extensions? I would love to hear your thoughts about this!

As Always

if you have any suggestions, thoughts, or just want to connect, feel free to contact/follow me on Twitter! Also, below is a link to some of my favorite resources for learning programming, Python, R, Data Science, etc

Thanks so much for reading!

Coding
Programming
Data Science
Machine Learning
Python
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