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With so many software types to choose from, it can be challenging to know which one to choose. If you’re looking for a data science tool, PyCharm is a good choice. Thanks to its student license, you can even access the software for free if you’re still studying.
PyCharm is good for data science. The software works well with multiple scripts and comes with the Python console. Student licenses are available, and PyCharm has many great features, including a debugger and excellent project maintenance tools.
If you’re looking for more information on PyCharm, and whether it’s a useful tool for data science or not, you’ve come to the right place. The following article contains advice on Professional PyCharm, what features you get with PyCharm, and much more.
What Is PyCharm?
PyCharm is an Integrated Development Environment (IDE). IDEs are coding tools that allow you to test and to debug your code, as well as writing it. However, some of the features of IDEs like PyCharm appear in iNotebooks, like Jupyter Notebook.
The most significant benefit of using an IDE instead of writing code in Word or Notepad is the capacity to run your code from within the same program. Nevertheless, some word processors now offer plug-ins that will test and debug code.
Experienced coders and data scientists who already work with Python or Anaconda will find PyCharm easy to use. PyCharm uses libraries such as NumPy and Matplotlib, so if you use those frequently, you’ll find that PyCharm has everything you need.
Is PyCharm Good?
PyCharm is one of the best IDEs available, and it’s made by JetBrains, the team behind IntelliJ IDEA.
PyCharm can handle multiple scripts, has excellent debugging capabilities, and works well for users who already work with Python, Anaconda, and more.
PyCharm is an excellent choice for data science, but you may have to pay for the Professional Edition to access the data science tools.
What Features Does It Have?
The Jetbrains software, PyCharm, is packed full of useful features to make your work easier. PyCharm features include:
- Supports Javascript, CSS, SQL, and more
- Code editor
- Error highlighting
- Debugger
- Git, SVN, Mercurial integration
- Customization of interfaces and keybinding
- PyCharm plug-ins library
Is PyCharm Suitable for Beginners?
There is a learning curve to using PyCharm, but this is true of most software for new users. On the one hand, PyCharm is great for those already experienced working with Python, which may alienate newcomers to the Python programs. However, everyone has to start somewhere, and with its functionality geared towards easily maintainable code, PyCharm could be an excellent place to start.
If you’re unsure whether PyCharm is right for you or not, download the Community Edition for free. It won’t have all the features, but it’ll give you a chance to test it out and determine how steep the learning curve would be for you.
A useful guide can go a long way to getting you up to speed with new software. We recommend Learn Python Quickly: A Complete Beginner’s Guide to Learning Python, Even If You’re New to Programming (available on Amazon). It comes in print, digital, or audiobook and covers everything you need to know to get started programming with Python.
There’s an excellent video on setting up PyCharm by Tech With Tim here:
PyCharm is mostly an excellent choice for data science, but like all good things, it has some downsides.
Pros of PyCharm
- Integration with Git, Mercurial, Python, Anaconda
- Supports several other scripts
- Excellent debugger
- Vast plug-ins library
- Community Edition available for free
- Student license available
- Project maintenance tools
Cons of PyCharm
- Scientific tools not included in Community edition
- May be challenging to learn to use
- Requires a large amount of memory
If you’ve never used Python for data science projects before, Python Data Science Handbook: Essential Tools for Working with Data on Amazon will guide you through the process. It’s available in print or digital and covers iPython, Jupyter, NumPy, Pandas, Matplotlib, and Scikit-Learn.
PyCharm has some excellent data science features, such as visualization of data plots, scientific libraries, and Conda integration. However, you will need the Professional Edition to access PyCharm’s data science tools. You will also get Jupyter Notebook with your software, allowing you to integrate this with PyCharm.
PyCharm Community Edition
The Community Edition is free, and you can get the Professional Edition free on a student license. That being said, you can also use the Community Edition for work just fine, in case you do not find value in investing in the Professional Edition.
What You Get With Community PyCharm
There is a significant difference in how much you get with Community PyCharm, compared to the Professional Edition. Some of the main features of Community PyCharm include:
Pycharm Professional License Student Edition
- Debugger
- Code inspections
- Core Python support
- Python console
- Git, Github
- Mercurial
However, this is a small list, and the Community Edition features many functions and libraries. You can check out the full list here.
PyCharm Professional Edition
If you want full functionality or need a feature that’s not included in the Community Edition, the Professional Edition is well worth the cost.
Data scientists will find PyCharm worth paying for to get access to its scientific tools. None of these are available in the free version.
What You Get With Professional PyCharm
Professional PyCharm includes everything available in the Community Edition as well as the following:
- Code coverage
- Cython
- Duplicate code detection
- Python profiler
- UML diagrams
- Platform tools like profiler integration
- Perforce
- Many web development tools, such as JavaScript Debugger
- Python web frameworks
- Remote development and containers
- SQL
- Scientific tools like SciView
You can view the full list of Professional PyCharm features here.
How Do You Get a Student License for Professional PyCharm?
Pycharm Professional For Students
You can apply for a student, or educational license (teachers may also apply), here. Student licenses apply to middle and high school students, as well as undergraduate and graduate students. You may also be eligible for a free license if you are a vocational student. You must be enrolled in a full-time course that lasts for a year or longer.
Licenses last one year and must be renewed via a link in your account.
Do I Need to Install Python to Run PyCharm?
PyCharm works through Python, so you will have to install the parent software first. The PyCharm program acts as a complement to Python, but it can really enhance your data science projects. The Python console is included with PyCharm Community and PyCharm Professional.
- Does PyCharm work on non-Python projects? PyCharm has a lot of plug-ins for non-Python projects, such as SQL and CSS. If you usually work with several computer languages, PyCharm works well as a single hub for you to work in.
- Can you adapt the code? The Community Edition of PyCharm is open source, and you can modify it to suit your needs. You can view the source code through Github. Open source code is publicly accessible code, which you can view, modify, and distribute however you want.
Conclusion
In this article, I examined PyCharm and listed its features. I looked at whether PyCharm is good for data science or not, what you get with Community vs. Professional PyCharm, and how to get a student license. I also listed some of the pros and cons of PyCharm and explained that you could adapt the code for the Community Edition. Geronimo stilton libri pdf download free.
Pycharm Professional License Student Download
To sum up, the free version of PyCharm is useful, but most of the data science tools you’ll need are restricted to the Professional Edition. However, if you are a student or teacher, you can access PyCharm Professional for free.
- Free educational licenses. (n.d.). JetBrains. https://www.jetbrains.com/community/education/#students
- (n.d.). GitHub. https://github.com/
- (n.d.). JetBrains. https://www.jetbrains.com/
- Polat, G. (2020, September 27). Effective deep learning development environment with PyCharm and docker. Medium. https://towardsdatascience.com/effective-deep-learning-development-environment-with-pycharm-and-docker-34018f122d92
- Professional vs. community – Compare editions | PyCharm. (2020, August 25). JetBrains. https://www.jetbrains.com/pycharm/features/editions_comparison_matrix.html
- PyCharm community edition and professional edition explained: Licenses and more – PyCharm blog | JetBrains. (n.d.). JetBrains Blog. https://blog.jetbrains.com/pycharm/2017/09/pycharm-community-edition-and-professional-edition-explained-licenses-and-more/
- PyCharm for data scientists. (n.d.). KDnuggets. https://www.kdnuggets.com/2019/05/pycharm-data-scientists.html
- Scientific & data science tools – Features | PyCharm. (n.d.). JetBrains. https://www.jetbrains.com/pycharm/features/scientific_tools.html
- Top 5 Python IDEs for data science. (n.d.). DataCamp Community. https://www.datacamp.com/community/tutorials/data-science-python-ide