I have data in a list type format of NumPy arrays

[array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]),
array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]),
array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]),
array([[ 0.00353654]]), array([[ 0.00353654]]), array([[ 0.00353654]]),
array([[ 0.00353654]])]

I am trying to get this into a polyfit function:

m1 = np.polyfit(x, y, deg=2)

But it is returning this error: TypeError: expected 1D vector for x

I am thinking that as of now, I need to do something like flatten my data into something like this:

[0.00353654, 0.00353654, 0.00353654, 0.00353654, 0.00353654, 0.00353654 ...]

I already tested list comprehension which usually works well on lists, but this as expected has not worked:

[val for sublist in risks for val in sublist]

What is the best solution to this?