In NumPy, you can use thewhere()function to apply multiple conditions and return values based on those conditions. You can specify multiple conditions using logical operators like&(and),|(or), and~(not). Thenumpy.where()is a versatile function that can be used to create new arrays or upd...
The foundation of thewheremethod’s functionality lies in creating Boolean masks based on specified conditions. These masks are essentially arrays or series ofTrueandFalsevalues, representing whether each element satisfies the given condition. Given a DataFrame: import pandas as pd data = { 'Name':...
Example -2: Use of multiple conditions with logical AND The following example shows how the () function can be used with the multiple conditions defined by logical and applied in two one-dimensional arrays. Here, two one-dimensional NumPy arrays have been created by using the rand() function...
An instance of this is when numpy.where() is used with arguments such as condition, a, and b. In such a case, the returned elements are selected from arrays a and b. The selection is based on the values in the boolean array that is generated by evaluating the condition. In case the...