Data Exploration with Python and SQL Server using Jupyter Notebooks
When it comes to data-driven research, presenting the results is a complicated task.
It is convenient to have an initial dataset handy, if anyone asks to re-run the computations or wants to interact with the data.
Reproducibility across a number of fields is a tough task and there aren’t too many tools that can help. It’s easy to show numbers in Excel or in Power Point, but in many use cases, the context and the pathway to the results is lost.
It is convenient to have an initial dataset handy, if anyone asks to re-run the computations or wants to interact with the data.
Reproducibility across a number of fields is a tough task and there aren’t too many tools that can help. It’s easy to show numbers in Excel or in Power Point, but in many use cases, the context and the pathway to the results is lost.
What is the Jupyter Notebooks?
Jupyter Notebooks is a great tool that is becoming more and more popular these days. Jupyter Notebook combines live code execution with textual comments, equations and graphical visualizations. It helps you to follow and understand how the researcher got to his conclusions. The audience can play with the data set either during the presentation or later on. Some people say that Project Jupyter is a revolution in the data exploration world just like the discovery of Jupiter's moons was a revolution in astronomy.
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Read my full article here about %sql magic Julyter command which can be used for interactive data analysis using our favorite language: SQL: https://www.mssqltips.com/sqlservertip/6120/data-exploration-with-python-and-sql-server-using-jupyter-notebooks/
Yours
Maria
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