We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Matt Harrison - An Introduction to Pandas 2, Polars, and DuckDB | PyData Global 2023
Explore the world of data processing with Pandas, Polars, and DuckDB, learn how to optimize code, improve performance, and reduce computational overhead with Pullers and PyArrow.
- The importance of having a query engine to optimize code and reduce execution time.
- Pullers, a query engine with a data frame API, can be used to improve performance and reduce computational overhead.
- A main difference between Pullers and Pandas is the ability to chain queries and optimize performance.
- DuckDB, a query engine, can also be used to query against data stored in Pandas or Polaris.
- The importance of leveraging PyArrow for faster data processing.
- The potential drawbacks of using Pandas, including its high memory usage and slow performance.
- The importance of considering the size of data and the type of operations being performed when choosing a data processing library.
- The ability to use Pullers to port Pandas code to a faster and more efficient version.
- The importance of understanding the data and the context in which it is being used when choosing a data processing library.
- The potential benefits of using Pollers, including improved performance and reduced computational overhead.