What Challenges Might One Face When Using Pandas in Catalysis?
While Pandas is a versatile tool, there are some challenges one might face:
Scalability: Handling extremely large datasets can be memory-intensive, potentially leading to performance issues. Complexity: The flexibility of Pandas can sometimes result in complex code that is difficult to maintain. Learning Curve: Researchers may require time to become proficient in using Pandas effectively.
Addressing these challenges often involves optimizing code, using complementary tools like Dask for larger datasets, and continuous learning.
