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Tables and Arrays

When working with structured data, use tables with named keys for better performance, readability, and maintainability Arrays are good for lists of simple values, but tables are better for complex structured data

These are just examples to demonstrate faster data retrieval using tables versus arrays
Arrays have their own purpose and aren’t inherently bad; they just have different use cases

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Choosing Between Tables and Arrays

Tables are faster than arrays for data lookups because they use a hash map internally, providing constant time lookups, making them much more efficient, especially for larger datasets
Arrays are slower in lookups due to linear time complexity , as they require looping through each element until the value is found

for i loops are generally faster than ipairs or pairs only arrays work with ipairs or for i loops

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Efficient Data Structuring

When working with structured data, use named keys in tables to improve readability, clarity, and performance
Named keys allow for easier understanding of what each field represents, and they also enable faster lookups

Arrays with indexed values are harder to read and maintain, and lookups are slower, especially as the size of the data grows.

Work space