numpy.where() in PythonThe NumPy module provides a function numpy.where() for selecting elements based on a condition. It returns elements chosen from a or b depending on the condition. For example, if all arguments -> condition, a & b are passed in numpy.where() then it will return elements selected from a & b depending on values in bool array yielded by the condition. If only the condition is provided, this function is a shorthand to the function np.asarray (condition).nonzero(). Although nonzero should be preferred directly, as it behaves correctly for subclasses. Syntax:Parameters:These are the following parameters in numpy.where() function: condition: array_like, bool If this parameter set to True, yield x otherwise yield y. x, y: array_like: This parameter defines the values from which to choose. The x, y, and condition need to be broadcastable to some shape. Returns:This function returns the array with elements from x where the condition is True and elements from y elsewhere. Example 1: np.where()In the above code
In the output, the values ranging from 0 to 5 remain the same as per the condition, and the other values have been multiplied with 5. Output: array([ 0, 1, 2, 3, 4, 5, 30, 35, 40, 45, 50, 55]) Example 2: For multidimensional arrayOutput: array([[1, 8], [3, 4]]) Example 3: Broadcasting x, y, and conditionOutput: array([[10, 11, 12, 13], [ 1, 11, 12, 13], [ 2, 2, 12, 13]]) In the above code
In the output, the x value has been compared to y value if it satisfied the condition, then it will be printed x value otherwise, it will print y value, which has passed as an argument in the where() function. Example 4: Broadcasting specific valueOutput: array([[ 0, 1, 2], [ 0, 2, -2], [ 0, -2, -2]]) Next Topicnumpy.argsort() |