[Solved] You have a 2D numpy array data with shape (100, 50). You want to add a new dimension at the front to represent batch size 1, making the shape (1,... Which code correctly does this using np.newaxis? | NumPy

NumPy - Array Manipulation

You have a 2D numpy array data with shape (100, 50). You want to add a new dimension at the front to represent batch size 1, making the shape (1, 100, 50). Which code correctly does this using np.newaxis?

Adata[np.newaxis:]

Bdata[np.newaxis, :, :]

Cdata[:, :, np.newaxis]

Ddata[:, np.newaxis, :]

Step-by-Step Solution

Solution:

Step 1: Understand the original shape and desired shape
Original shape is (100, 50). We want to add a new axis at the front to get (1, 100, 50).
Step 2: Use np.newaxis at the front index
Using data[np.newaxis, :, :] adds a new axis at position 0, resulting in shape (1, 100, 50).
Step 3: Check other options
data[np.newaxis:] does not add a new dimension (acts as slice data[:], shape (100,50)). data[:, np.newaxis, :] adds axis in middle (100, 1, 50), data[:, :, np.newaxis] adds axis at end (100, 50, 1).
Final Answer:
data[np.newaxis, :, :] -> Option B
Quick Check:
New axis front = data[np.newaxis, :, :] [OK]

Quick Trick: Add np.newaxis at front index for batch dimension [OK]

Common Mistakes:

Adding newaxis in wrong position
Using fewer indices than array dimensions
Confusing axis order for shape

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Which code correctly does this using np.newaxis?

Step 1: Understand the original shape and desired shape

Step 2: Use np.newaxis at the front index

Step 3: Check other options

Final Answer:

Quick Check:

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