PandaPy: A Wrapper Around Structured Arrays to Mimic ‘Structs’ in the C Language
2 Pages Posted: 8 Jun 2020
Date Written: May 13, 2020
Abstract
Similar to the original Pandas project, PandaPy is developed to improve the usability of python for finance. Structured data types are designed to be able to mimic ‘structs’ in the C language, and they share a similar memory layout. The biggest benefit of this approach is that NumPy directly maps onto a C structure definition, so the buffer containing the array content can be accessed directly within an appropriately written C program. This makes PandaPy a strong contender for high frequency trading on small-to-medium datasets. PandaPy currently houses more than 30 functions.
Keywords: Python, Pandas, Data Structure, Software, Finance, Economics, Latency, Memory, Structured, High Frequency Trading
JEL Classification: C65, C69, C87, C88
Suggested Citation: Suggested Citation