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...
Python numpy array row extraction based on another's array column, Two 2D numpy arrays are given (arr_all and arr_sub) whereas the second is a random subset of the first. I need to get the rows of the first Numpy: Select all rows and columns from an array Question: As I write ...