Overview
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Learn how to analyze SQL Server data with Python. Discover how to perform statistical analyses, generate graphics, and process tabular data—directly in SQL Server.
Syllabus
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Introduction
- Analyze SQL Server data with Python
- What you should know
- Using the exercise files
- What is machine learning services?
- Install ML services for Python
- Enable script execution in SQL Server
- Use variables in Python
- Create a Python while loop
- Import a dataset from SQL Server
- Manipulate a data frame
- Output a result set to SQL Server
- Python syntax pitfalls
- Challenge: Import a data frame
- Solution: Import a data frame
- The Anaconda open-source packages
- Functions in the revoscalepy package
- Model, train, and score with microsoftml
- Produce graphics with MatPlotLib
- Get descriptive statistics with pandas
- Challenge: Sample a data frame
- Solution: Sample a data frame
- Return values with indexes and series
- Convert a series to a data frame
- Add multiple series to a data frame
- Include the index in a data frame
- Slice a data frame to series
- Challenge: Import and process data
- Solution: Import and process data
- Create a Python stored procedure
- Parameterize the procedure
- Challenge: Write a stored procedure
- Solution: Write a stored procedure
- Install MLS on a standalone server
- Add development tools to the client
- Work with Jupyter Notebooks
- Next steps
