Multi-dimensional indexing (e.g. `obj[:, none]`) is no longer supported. convert to a numpy array before indexing instead.

The error message you are encountering is related to multi-dimensional indexing in Python’s numpy library. The specific issue arises when trying to use a syntax like `obj[:, none]`, which is no longer supported in recent versions of numpy. The solution to this problem is to convert the object into a numpy array before performing the indexing operation.

Let’s provide a more detailed explanation with an example. Suppose you have an object named `obj` that you intend to index using multi-dimensional indexing. Initially, you might have been using the unsupported syntax (`obj[:, none]`) that results in the error you mentioned.

    import numpy as np
    
    # Creating a sample object
    obj = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
    
    # Attempting multi-dimensional indexing
    result = obj[:, none]
  

To resolve this issue, you need to convert the object `obj` into a numpy array using the `np.array()` function. This conversion allows you to use the correct syntax for multi-dimensional indexing. Let’s modify the example code to reflect this solution:

    import numpy as np
    
    # Creating a sample object
    obj = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
    
    # Converting the object to a numpy array
    obj_arr = np.array(obj)
    
    # Performing multi-dimensional indexing
    result = obj_arr[:, None]
  

Here, we first convert `obj` to a numpy array using `np.array()`. Then, with the corrected syntax `[:, None]`, we can successfully perform multi-dimensional indexing. The resulting `result` variable would hold the desired indexed array.

In summary, to address the error message, you must convert the object into a numpy array using `np.array()` before performing multi-dimensional indexing operations.