Jupyter Notebook - A solid choice for early stage data analysis!
May 13, 2021
Jupyter Notebook - A solid choice for early stage data analysis!
Score 8 out of 10
Vetted Review
Verified User
Overall Satisfaction with Jupyter Notebook
Jupyter Notebook is used widely within our data science groups as a way to experiment with ML and other models. It's great for early stage data analysis as well as for training and sharing of new Python models within the group in a clear way. The interface is easy to use and onboard onto and has been a great way for members to easily share and onboard new associates onto their existing Python analysis scripts.
- Markdown for comments/explanations.
- Interactive programming.
- Easy to use and share notebooks.
- Doesn't have some features that competitors have.
- Difficult to do direct collaboration on the same notebook.
- Doesn't provide great code style support/corrections.
- Browser editing of code.
- Easy to use and start up.
- Interactive programming.
- Allowed for rapid exploration of initial phase analysis.
- Sped up process of realizing and deploying data models.
- Great communication tool both internally and externally.
Jupyter Notebook has a nicer interface than RStudio in our opinion and since most of our group is familiar with Jupyter Notebook it has made it a default choice. Overall the interactive programming as well as the easy visualizations, model deployment, and markdown made Jupyter Notebook a good choice although some people do still use RStudio for specific projects. Jupyter Notebook is a bit nicer as a communication tool so it has become a preferred method of sharing and getting feedback on early stage data analysis and modeling.
Do you think Jupyter Notebook delivers good value for the price?
Yes
Are you happy with Jupyter Notebook's feature set?
Yes
Did Jupyter Notebook live up to sales and marketing promises?
I wasn't involved with the selection/purchase process
Did implementation of Jupyter Notebook go as expected?
Yes
Would you buy Jupyter Notebook again?
Yes