In numpy, if a dimension is given as ____ in a reshaping operation, the other dimensions are automatically calculated.OneZeroNegative oneInfinite

The correct option in the context of NumPy reshaping operations is Negative one. When using -1 as one of the dimensions in the reshape method, NumPy automatically calculates the appropriate size for that dimension based on the total number of elements and the other specified dimensions.

Explanation

1. Understanding the Reshape Operation: In NumPy, the reshape function is used to change the shape of an array without changing the data.
2. Using -1 in Reshaping: By specifying -1 as a dimension, you instruct NumPy to infer the size of that dimension so that the total number of elements remains the same. This is useful when you know the total number of elements and want to adjust other dimensions without calculating the necessary size manually.
3. Example Usage: If you have an array with 12 elements and you want to shape it into a matrix with 3 rows, you can use the reshape function like this: array.reshape(3, -1), and NumPy will automatically calculate that there should be 4 columns.

In summary, using -1 in reshaping simplifies working with arrays, as NumPy handles the dimension sizing automatically based on the data's total size.