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I want to check if a numpy array is multidimensional or not?
V = [[ -7.94627203e+01 -1.81562235e+02 -3.05418070e+02 -2.38451033e+02][ 9.43740653e+01 1.69312771e+02 1.68545575e+01 -1.44450299e+02][ 5.61599000e+00 8.76135909e+01 1.18959245e+02 -1.44049237e+02]]
How can I do that in numpy?
429
Look for array. shape: if it comes like (2,) means digit at first place but nothing after after comma,its 1D. Else if it comes like (2,10) means two digits with comma,its 2D.
Check if the Numpy array is Nan in Python To check for Nan values in a Numpy array we can use the function Np. isNan(). The output array is true for the indices that are Nan in the original array and false for the rest.
Method 1: numpy. any() to check if the NumPy array is empty in Python. numpy. any() method is used to test whether any array element along a given axis evaluates to True.
To find the shape (or dimensions) of a nested list or tuple in Python, iterate over each element in the list or tuple and identify its length with the built-in len() function.
Use the .ndim property of the ndarray:
>>> a = np.array([[ -7.94627203e+01, -1.81562235e+02, -3.05418070e+02, -2.38451033e+02],[ 9.43740653e+01, 1.69312771e+02, 1.68545575e+01, -1.44450299e+02],[ 5.61599000e+00, 8.76135909e+01, 1.18959245e+02, -1.44049237e+02]])
>>> a.ndim
2
In some cases, you should also add np.squeeze() to make sure there are no "empty" dimensions
>>> a = np.array([[1,2,3]])
>>> a.ndim
2
>>> a = np.squeeze(a)
>>> a .ndim
1
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