You have a 1D numpy array data with shape (100,). You want to prepare it for a machine learning model that expects input shape (100, 1). Which code correctly reshapes data using np.newaxis?

hard📝 Application Q8 of 15

NumPy - Array Manipulation

You have a 1D numpy array data with shape (100,). You want to prepare it for a machine learning model that expects input shape (100, 1). Which code correctly reshapes data using np.newaxis?

Adata[np.newaxis, :]

Bdata[np.newaxis]

Cdata[:, :, np.newaxis]

Ddata[:, np.newaxis]

Step-by-Step Solution

Solution:

Step 1: Understand the target shape
The model expects shape (100, 1), meaning 100 rows and 1 column.
Step 2: Use np.newaxis to add column dimension
Adding np.newaxis after ':' adds a new axis as the second dimension, resulting in shape (100, 1).
Final Answer:
data[:, np.newaxis] -> Option D
Quick Check:
New axis as second dimension = data[:, np.newaxis] [OK]

Quick Trick: Add np.newaxis after ':' to add a column dimension [OK]

Common Mistakes:

Adding newaxis at front
Using too many indices
Not matching expected shape

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You have a 1D numpy array data with shape (100,). You want to prepare it for a machine learning model that expects input shape (100, 1). Which code correctly reshapes data using np.newaxis?

Step 1: Understand the target shape

Step 2: Use np.newaxis to add column dimension

Final Answer:

Quick Check:

Want More Practice?