The read_csv method in Pandas loads all rows of the dataset into the DataFrame before filtering to remove all unwanted rows.
On the other hand, the scan_csv method in Polars delays execution and optimizes the operation until the collect method is called.
This approach accelerates code execution, particularly when handling large datasets.
Polars vs. Pandas for CSV Loading and Filtering Read More »
Polars is a lightning-fast DataFrame library that utilizes all available cores on your machine. Polars has two APIs: an eager API and a lazy API.
The eager execution is similar to Pandas, which executes code immediately.
In contrast, the lazy execution defers computations until the collect() method is called. This approach avoids unnecessary computations, making lazy execution potentially more efficient than eager execution.
Polars: Speed Up Data Processing 12x with Lazy Execution Read More »