Review of the Jupyter Notebook
May 24, 2021
Review of the Jupyter Notebook
Score 8 out of 10
Vetted Review
Verified User
Overall Satisfaction with Jupyter Notebook
As an organization, we are using Python for solving manual task creation by automatically doing this task. So for this we use the RPA technology, but for that we have to scrape the data from the PDF. So we use the Python library from which we read the data which in the form of image then create the CSV table by using the library.
- Easy to use and handle as it takes less hardware requirements.
- Helps [in] creating the data visualization.
- Provide support for difficult language.
- Needs more code styling.
- The markdown is limited.
- For the new user, there [should be] some intro videos or tutorial for that.
- Easy to use and open source platform.
- Data visualization and format.
- Easy navigation platform for the new user.
- The markdown is best in the best in that.
- As a company [if you] are using Python language, then it is best for you.
- You can also make data visualization.
- It is also cost effective.
PyCharm is also a suitable software for this similar functionality. But I consider Jupyter Notebook as the best [of] all time. It is more effective and provide[s] the best functionality for data visualization and it will provide the modelling and code editing. There is multi language support for the different languages also.
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?
Yes
Did implementation of Jupyter Notebook go as expected?
Yes
Would you buy Jupyter Notebook again?
Yes