With the invitation of Steve Jones for April month of T-SQL Tuesday, I am going to share some of my thoughts on using Jupyter notebooks.
Jupyter Notebook is an open-source web application that can serve us to create, share code and documents with others. It provides that beautiful way to document your code, text, images and query results. Jupyter notebooks in Azure data studio can run PySpark, Python 3, Spark R and Scala, as well as PowerShell. Run and visualize the data as you see the results without having to leave the environment. This is an excellent tool for documenting things. You do not have to write your long emails attaching bunch of screenshots any more. Once you start using the Jupyter notebooks, it will save you so much time and give you peace of mind. This tool can not only be used for documentation purposes but also can be used for your presentations for your demo purposes. Not only for the SQL code, this is a very nice tool for doing machine learning models, visualizing data and much more. Your code can be written in different cells which can be executed individually. This can help us to run specific part of the code in the project. This tool supports Python, R as well.
There are some magic commands that you can use to make your work easier. %clear, %autosave, %debug and %mkdir are some of the commands and these magic commands can be used in two ways. Linewise and cellwise. Linewise is when you wish to run a single command and cell-wise is when you wish to run an entire block of code.
There are also interactive dashboards in Jupyter notebooks.
When you wish to share these jupyter files and as they are in json format. You can save the notebook using different file options like a CSV, Excel, JSON or XML file . You can also convert your notebook into different formats by using the nbconvert option. For analytical queries, you can also build a chart for the data.
You can use the Jupyter notebooks for giving presentations to your customers and clients about your projects.
Jupyter notebooks is an amazing tool as you can document everything what you do. Once we start using Jupyter notebooks, you would definitely do not want to turn back to the previously used tools anymore. I recommend this tool to anyone who would like to explore and take advantage of many features the Jupyter notebooks has to offer.