BUG: Unexpected behavior when assigning multi-dimensional array to DataFrame column

[Socob]

• I have searched the [pandas] tag on StackOverflow for similar questions.

• I have asked my usage related question on StackOverflow.

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Question about pandas

My question is essentially the same as the StackOverflow question “Unexpected behavior in assigning 2d numpy array to pandas DataFrame”, which, although it has an accepted answer, states in an edit to the question text:

Since the bounty is going to expiry [sic], I accepted the most voted answer. But it does not provide a answer to the above questions.

I agree, and still don’t understand the behavior described in the question, which I will restate here:
Given the following code:

import pandas
import numpy
df = pandas.DataFrame(numpy.zeros((4, 1)), columns=['A'])
y = numpy.random.randn(4, 2)
df['A'] = y

which results in (e.g.)

df
#           A
# 0  0.994449
# 1 -0.280376
# 2 -0.993288
# 3  0.009625
y
# array([[ 0.99444899, -0.80571928],
#        [-0.28037615, -0.47071158],
#        [-0.99328776, -0.15674664],
#        [ 0.00962502,  1.24896221]])

I expect it to throw an exception because of shape mismatch. But pandas silently accepted the assignment: y's first column is assigned to df.

Is this an intentional design? If yes, what is the rationale behind?

[phofl]

Yeah this is a bug, would agree with anerror here

[Mxchaeltrxn]

take