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Code Along ↗Analyzing Olympics Data with SQL and Python
Learn how to load data from different sources and perform exploratory analyses.
Justin Saddlemyer
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Learn to use a combination of SQL & Python to import, process, and analyze data

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Analyzing Olympics Data in SQL & Databricks
In this session, Holly, a Staff Developer Advocate at Databricks, teaches you how to get started using the Databricks platform while working through an analysis of Olympics sporting data.

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Superbowl Analysis in Python
Learn to do exploratory data analysis in Python on historic Super Bowl data.



Learn how to leverage the power of DataLab by combining Python and SQL to load data from different sources, combine them, and perform exploratory analyses.
This training will use an Olympics dataset and then enrich it with country details from a SQL database. Learners will then explore the data, uncovering interesting insights and creating interactive visualizations.
This training is geared towards learners with some background in SQL and some introductory knowledge of Python. It is recommended that they take Joining Data in SQL and Data Manipulation with pandas prior to attending the session.
Key takeaways
Combine different data sources using SQL & Python using DataLab
Perform basic exploratory analysis using pandas
Learn how to use Plotly to easily create interactive visualizations
Materials
Access to the solution notebook