Using Python for data analysis (6) NumPy basics: vector computing and pythonnumpy

Using Python for data analysis (6) NumPy basics: vector computing and pythonnumpy

Vectoring refers to replacing the loop with an array expression to manipulate each element in the group.
NumPy provides a universal function (ufunc function) that performs an element-level operation on data in the ndarray. For example, the square function computes the square of each element. The rint function rounds each element into the numpy. where function.
The numpy. where function is a vectorized version of the ternary expression x if condition else y, such as mathematical and statistical methods.
For example, the np. sum function can sum the elements in the logarithm group:
For a two-dimensional array, the sum function also sums all elements, but the two-dimensional array has two directions: horizontal axis and vertical axis. Therefore, the sum function can also sum two-dimensional arrays in the direction: