![]() ![]() Switching to one of these systems later, or transferring your code to one of these systems should be easy. Not only will you get better performance with less issues, but you will be training yourself to program in an environment that is very close to what you would use on a full Linux or Apple OS. If you want to vastly improve your development experience on Windows, I suggest you forego the aforementioned options and instead consider Windows Subsystem for Linux (WSL). These are often difficult to set up, difficult to reproduce, and full of compatibility issues despite their supposed isolation from the Windows OS. ![]() So next you may consider spinning up virtual machine environments in Windows. But you may not be comfortable with this process, and oh what a pain it is to log in and out every time you switch tasks. ![]() To get past the limitations of programming in Windows, you could dual-boot Linux and Windows on the same machine and switch between the partitions as your tasks require. Why should I use Windows Subsystem for Linux? You may run into issues with speed, compatibility is woefully lacking, debugging is much harder than it should be, and almost every Stack Overflow post gives you instructions that only work in Unix/Linux. ![]() But, the more complex your work becomes, the more drawbacks you will encounter with Windows. If you are in your first year of college, this setup will work beautifully. Windows can handle data science, especially if you aren’t going much further than installing Python, Anaconda, and R with some common packages. For example, are you limited to Windows because of workplace requirements? Do you not have the budget to switch to a new Apple machine? Do you not have the time or knowledge to install a Linux OS on your PC? Are Windows and Microsoft Office suite what you are most comfortable with? Or perhaps you don’t want to have to replace all the Windows software for which you have spent a small fortune purchasing licenses. The answer for each person is based on individual preferences, experience, and external limitations.įor some people, the answer may be Windows. When a budding data scientist decides to buy a new laptop for college, they inevitably come to their friends, classmates, or Stack Overflow to ask the question, “What operating system should I use for data science?” This question is as contentious among programmers as “Should I use tabs or spaces?” If you ask me, there is not a single best answer to this question. ![]()
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