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5 Popular Python Open-Source IDEs For Data Science Enthusiasts

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Integrated Development Environment (IDE) is the daily-used coding tool for a programmer which enables a complete set for Source Code Editor as well as debugging featured building tool. Over the last few years, Python has emerged as one of the most used languages by the programmers, thanks to its high versatility and developer community. In this article, we list down 5 top Python IDEs to choose from for data science enthusiasts.

(The list is in alphabetical order)

1| Jupyter

Jupyter Notebook is an open-sourced web-based application which allows you to create and share documents containing live code, equations, visualisations, and narrative text. This notebook not only supports Python but also has support for over 40 programming languages. It provides a perfect environment for the data science enthusiast who just started out in their career in this field. This IDE supports markdown and enables you to add HTML components from images to videos. The IDE also includes data cleaning and transformation, numerical simulation, statistical modelling, data visualisation, and many others.

Type: Open Sourced

Pros:

  • Produce rich and interactive output
  • Edit snippets before running them

Cons:

  • Complex for running long asynchronous tasks
  • The installation process is complex

Click here to get started with Jupyter.

2| PyCharm

This IDE is a full-fledged IDE for Python scripting language which includes features like an advanced debugger, high-quality completion, support for web programming as well as code inspection. Pycharm IDE not only supports Python but also supports code written in SQL and other similar database languages along the line. It enables easy code completion irrespective of the packages and also has some shortcuts for easy refactoring process.

Type: PyCharm has several licensing options with different features from open-sources to paid versions.

Pros:

  • It has Version Control System Integration with many external plug-in supports.
  • Codes can be easily run, edit or debug without any external requirement

Cons:

  • Memory Intensive
  • Initial set-up can be time-consuming

Click here to get started with PyCharm.

3| Rodeo

Rodeo is an open-sourced Python Integrated Development Environment which is lightweight, intuitive, customisable and built especially for data science/machine learning projects. The Rodeo text editor comes with auto-complete, syntax highlighting and Ipython support. It also includes Integrated tutorials which help its users to get started with learning Python.

Type: Open Sourced

Pros:

  • The Rodeo visual file navigator allows its users to find whatever they are looking for.
  • Helps the users to quickly get some idea about the data structures without writing any additional lines of code.

Cons:

  • Slow development of the tool.
  • Memory Issues.

Click here to get started with Rodeo.

4| Spyder

Spyder is a powerful scientific environment written in Python which is built especially for data science. It offers a unique combination of advanced editing, analysis, debugging and profiling functionality of a comprehensive development tool along with data exploration, interactive execution, deep inspection and many more. This IDE works efficiently in a multi-language editor with a function/class browser, code analysis tool, automatic code completion, etc.

Type: Open Sourced

Pros:

  • Easy to use/install and intuitive interface
  • Excellent variable explorer

Cons:

  • Memory consuming
  • Falls short in non-data science projects.

Click here to get started with Spyder.

5| Visual Studio Code

Developed by Microsoft, this text editor can also be used as an IDE. It has features like syntax highlighting, autocomplete function and als,  has an IntelliSense which enables completion of codes based on variable types, functions, and imported modules,

Type: Open Sourced

Pros:

  • Superfast and lightweight Source Code Editor
  • Visual studio supports inbuilt Integrated terminal, initially starting at the root of your opened project.

Cons:

  • Lacks most features of a full IDE suite
  • Longer launch time than most of its competitors

Click here to get started with Visual Studio Code.

Other Alternative IDE

Sublime Text

Sublime Text is one of the most popular code editors for the programmers which supports on almost all the platforms. It has a rich set of extensions which extend the syntax and editing features as well as built-in support for Python code editing. Projects in Sublime Text capture the full contents of the workspace, including modified and unsaved files.

Type: This IDE does not come for free, however, you can use the evaluation version for an unlimited period.

Pros:

  • This IDE is fast and well-supported
  • Sublime Text has a powerful, Python API that allows plugins to augment built-in functionality.

Cons:

  • There is no console version available
  • Settings are stored in fixed, platform-specific locations which makes it hard to store your settings in a central Git repository, and share it across different machines and OSes.

Click here to get started with Sublime Text.

The post 5 Popular Python Open-Source IDEs For Data Science Enthusiasts appeared first on Analytics India Magazine.


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