A fresher’s perspective: Jupyter Notebook or Desktop IDE?

If you are confused on whether to launch a notebook or a desktop IDE for your Python project, here are some differences I discovered as a data science fresher.

For collaborative projects and simple data analysis projects, I prefer to use notebooks. With its markdown, I can write a detailed explanation of my code and with its LaTeX feature, I can write complex mathematical equations. I can also run each block of code separately for better interactivity, meaning, I can write my code and test it there and then. Because notebooks are web-based IDEs, I can access them almost anywhere and I can easily share my work with other people.

On the other hand, I prefer to use desktop IDEs like Spyder for projects involving large code bases. With Spyder, I can easily browse through your working directories and open up several python files. I can also easily view the variables you used and, their types, sizes and values with just a click of your mouse in the variable explorer. Its code editor also has interesting features like syntax highlighting and code completion. I also found it easier to debug in Spyder than in notebooks because of its real time code analysis. Note that I used Spyder for my past 2 projects here in Medium [See: How I developed my own trivia game in Python & How I Programmed Rock, Paper, Scissors in Python]. The reasons why I used Spyder is primarily because its style interface is similar to MATLAB [Yes, I am more of a MATLAB girl] and its IPython Console allows me to easily test the function that contains the flow of my code.

All in all, this is a matter of one’s own preferences but I still highly recommend both Jupyter Notebook and Spyder for data science freshers like me. Both Python IDEs are intuitive, very comfortable to use and great starting places for aspiring data scientists!