Python IDE for Data Science

Data Science — it is an area that is used to study and understand data, and to draw different conclusions through different scientific processes. Python is a popular language that is quite useful for data science due to its statistical analysis ability and its readability. Python also has various packages for machine learning, natural language processing, data visualization, data analysis, and more, which make it suitable for data science. Some of the Python IDEs used for Data Science are below:

  1. Jupyter Notebook —
    Jupyter Notepad — it is an open source IDE that is used to create Jupyter documents that you can create and share with common code. It is also a web-based interactive computing environment. Jupyter notebook can support various languages ​​popular in data science like Python, Julia, Scala, R, etc.
  2. Spyder —
    Spyder & # 8212 ; is an open source IDE originally created and developed by Pierre Reibaud in 2009. It can be integrated with many different Python packages such as NumPy, SymPy, SciPy, pandas, IPython, etc. The Spyder editor also supports code introspection, code completion, syntax highlighting, horizontal and vertical splitting, etc.
  3. Sublime text —
    Sublime text — it is a native code editor that supports the Python API. Some of Sublime text's features are project-specific tweaks, fast navigation, cross-platform plugin support, etc. While Sublime text is pretty fast and has a good support team, it is not available for free. 
  4. Visual Studio Code —
    Visual Studio Code — is a code editor developed by Microsoft. It was developed using Electron, but does not use Atom. Some of the features of Visual Studio Code are built-in Git control, smart code completion, debugging support, syntax highlighting, code refactoring, and more. It's also pretty fast and lightweight. 
  5. Pycharm —
    Pycharm — it is an IDE developed by JetBrains and built specifically for Python. It has various features like code analysis, built-in unit tester, built-in Python debugger, web framework support, etc. Pycharm is especially useful in machine learning as it supports libraries like Pandas, Matplotlib, Scikit-Learn, NumPy etc.
  6. Rodeo —
    Rodeo — is an open source IDE developed by Yhat for Data Science in Python. So, Rodeo includes Python tutorials as well as cheat sheets that you can use for reference if needed. Some of Rodeo's features include syntax highlighting, autocomplete, easy interaction with data frames and graphs, native IPython support, etc.
  7. Thonny —
    Thonny — is a development environment developed in Python for the University of Tartu. It is made for beginners who are learning to program in Python or those who are teaching it. Some of the features of Thonny — it is step-by-step execution of statements without breakpoints, simple pip GUI, line numbers, variables during debugging, etc.
  8. Atom —
    Atom — is an open source text and code editor developed using Electron. It has many features like slick interface, file system browser, various extensions, etc. Atom also has an extension that Python can support while it is running. 
  9. Jani —
    Geany — is a free text editor that supports Python and also contains IDE features. It was originally written by Enrico Treger in C and C++. Some of Geany's features are character lists, autocomplete, syntax highlighting, code navigation, multi-document support, etc.




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