5 Best Python IDEs for Data Science Buffs

5 Best Python IDEs for Data Science Buffs

IDE, short form for Integrated Development Environment, is a coding tool a programmer needs for daily-use. It works as an entire set for Source Code Editor on top of debugging featured building tool.

 

Over the last couple of years, the popularity of Python has reached new heights – all thanks to Python’s adaptability and a robust community of developers. Since it is one of most widely used languages in data science, below we have listed 5 famous Python IDEs data science buffs must be familiar with.

Jupyter

All documents having equations, live codes, descriptive texts and visualizations can be created and shared on Jupyter Notebook, which is a web-based and an open-source application. Apart from Python, this notebook supports 40 more programming languages! If you’re a newbie in the data science field, Jupyter is the perfect environment to start off. This IDE enables programmers to include image HTML components in videos. It also supports data cleaning, data transformation, statistical modeling, numerical simulation, etc. There are hardly any cons of this IDE except for a complicated installation process and difficulty in carrying out lengthy, asynchronous tasks.

PyCharm

With features such as advanced debugger, code inspection, web programming and high-quality completion, PyCharm is a full-blown Python IDE. Apart from Python, PyCharm supports SQL codes and similar database languages. It has shortcuts to simplify refactoring process and allows easy code completion too. However, this IDE is memory intensive.

Rodeo

Designed especially for projects related to machine learning and data science, Rodeo is a popular open-source Python IDE. This lightweight, customizable and intuitive IDE supports Ipython and features like auto-complete and syntax highlighting. In addition to these, the integrated tutorial facility comes very handy for new Python learners. However, this IDE has some memory issues and its development is also quite slow.

Spyder

A strong scientific environment developed in Python, Spyder is designed particularly for data science. This IDE offers multiple functions, like debugging, advanced editing, analysis, comprehensive development tool, interactive execution, data exploration, etc. It also includes automatic code completion and code analysis tool among many other useful tools, and works well in a multi-language editor. However, this IDE isn’t useful in projects outside data science field and consumes a lot of memory.

Visual Studio Code

This is a text editor developed by Microsoft, but it is also used as an IDE. Popular features of this IDE are syntax highlighting, autocomplete function and IntelliSense that allows code completion based on functions, imported modules and variable types. Its Source Code Editor is very speedy and lightweight, but common features found in a full IDE suite are missing.

Concluding:

Hope these Python IDEs comes handy for your data science projects. If you’re looking for Python training classes in Kolkata, Techtree Technologies is the institute to get in touch with. This upcoming Python Programming Training in Kolkata is good for both beginners and advanced learners, ensuring you emerge with the right skills needed to compete in today’s job market.

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