G2

Furkan A.

Data scientist

Computer Software

Small-Business (50 or fewer emp.)

4/13/2026

"Everything I Need for Data Science in One Place"

5/5

What do you like best about The Jupyter Notebook?

The thing I like most about Jupyter Notebook is that it is very beginner-friendly and has a simple, easy-to-understand interface. As someone who is learning data science, I found it easy to get started without needing a lot of technical knowledge. The layout is clean and organized, which makes it comfortable to work with even for beginners. One of the biggest advantages is that I can perform multiple tasks in one place. I can write and run Python code, clean and analyze data, create visualizations, and document my work all within the same notebook. This eliminates the need to switch between different applications and tools, making my workflow much smoother and more efficient. I also like that I can see the output of my code immediately, which helps me learn faster and understand concepts more clearly. Whether I am experimenting with new ideas, practicing coding skills, working on assignments, or building data science projects, Jupyter Notebook makes the process easier and more organized. As a data science student, it has become one of my most useful tools because it helps me focus on learning, exploring data, and improving my skills rather than spending time managing multiple software programs. Overall, Jupyter Notebook provides a simple and effective environment for learning, experimenting, and developing data science projects. Review collected by and hosted on G2.com.

What do you dislike about The Jupyter Notebook?

One thing I dislike about Jupyter Notebook is that it can become slow when working with very large datasets or running heavy computations. As the amount of data increases, the notebook may start lagging, take longer to execute code, or become less responsive. This can sometimes interrupt the workflow and make it harder to work efficiently on complex projects. There have been situations where I had to wait longer for code to run or restart the notebook to improve performance. While this is not a major issue for smaller projects and learning tasks, it can be noticeable when handling larger datasets or resource-intensive operations. Apart from this limitation, Jupyter Notebook works very well for most of my data analysis, visualization, and learning activities. Its ease of use, flexibility, and beginner-friendly interface make it a valuable tool for students and professionals alike. Review collected by and hosted on G2.com.

What problems is The Jupyter Notebook solving and how is that benefiting you?

One of the biggest benefits of Jupyter Notebook is that it allows me to perform many different tasks in a single environment. I can clean and prepare data, perform data analysis, create visualizations, and even build and train machine learning models without needing to switch between multiple applications or tools. Having everything in one place makes the entire process much more convenient and efficient. This saves me a lot of time because I do not have to move data between different software programs or manage multiple workspaces. It also helps keep my projects organized since the code, outputs, charts, and notes are all stored together in one notebook. This makes it easier to track my work, review previous steps, and share projects with others. Another benefit is that Jupyter Notebook encourages experimentation and learning. I can run code in small sections, see the results immediately, and make changes whenever needed. This interactive approach helps me understand concepts more clearly and learn from my mistakes. As a data science student, Jupyter Notebook is especially valuable because it provides a practical environment for practicing skills, exploring datasets, and building projects. It helps me test ideas quickly, improve my understanding of data science concepts, and complete assignments and personal projects more efficiently. Overall, it makes learning and working on data science tasks much easier and more enjoyable. Review collected by and hosted on G2.com.