The DuckDB database provides a seamless way to handle large datasets in Python with Online Analytical Processing (OLAP) optimization. You can create databases, verify data imports, and perform efficient data queries using both SQL and DuckDB’s Python API.
By the end of this video course, you’ll understand that:
- You can create a DuckDB database by reading data from files like Parquet, CSV, or JSON and saving it to a table.
- You query a DuckDB database using standard SQL syntax within Python by executing queries through a DuckDB connection object.
- You can also use DuckDB’s Python API, which uses method chaining for an object-oriented approach to database queries.
- Concurrent access in DuckDB allows multiple reads but restricts concurrent writes to ensure data integrity.
- DuckDB integrates with pandas and Polars by converting query results into DataFrames using the
.df()or.pl()methods.
What’s Included:
- 10 Lessons
- Video Subtitles and Full Transcripts
- 2 Downloadable Resources
- Accompanying Text-Based Tutorial
- Interactive Quiz to Check Your Progress
- Q&A With Python Experts: Ask a Question
- Certificate of Completion
Downloadable Resources:
Related Learning Paths:
