import numpy as np from Orange.data import Domain # Creating a NumPy array with three columns data = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]]) # Defining the domain for the dataset domain = Domain.from_numpy(X=data)
import numpy as np from Orange.data import Domain # Creating a NumPy array with two columns data = np.array([["a", 1.0], ["b", 2.0], ["c", 3.0]]) # Defining the domain for the dataset domain = Domain.from_numpy(X=data, metas=["meta"])In this example, we are creating a NumPy array with two columns and three rows. The first column contains categorical variables ("a", "b", and "c"), while the second column contains continuous variables. We use the `metas` argument to specify that the third column should be treated as metadata. Overall, the `from_numpy` function is a useful tool for creating domain objects from NumPy arrays. It is part of the `Orange` package, which is used for data mining and machine learning.