Step 1: List what each attribute returns.
columns gives an Index of column names. size gives an integer. shape gives a tuple. values gives an ndarray. The question asks for an ndarray, so look at the return type first.
Step 2: Use the return type to cut options.
Only one of the four returns a NumPy ndarray. The other three return an Index object, an int and a tuple. So options 1, 2 and 3 cannot match, whatever their other details are.
Step 3: Use the second clue.
The question also says without the axes labels. The values attribute holds only the cell data. Row and column labels are left out of it.
Step 4: Test it by running code.
import pandas as pd
df = pd.DataFrame({'a':[1,2],'b':[3,4]}, index=['x','y'])
print(df.columns)
print(df.size)
print(df.shape)
print(df.values)
The four prints show Index(['a', 'b']), then 4, then (2, 2), then a 2D array [[1 3] [2 4]]. Only the last line is an array of plain values.
Step 5: Pick the answer.
The attribute is DataFrame.values, option 4.
Step 6: Extra check.
Remember the small rule for pandas attributes. Attributes are used without brackets, so df.values is correct and df.values() would fail. Values is also the one to use when a NumPy function needs the raw numbers of a table. This confirms why the question points to it.
Final Answer:
The attribute that returns the values as an ndarray is DataFrame.values, option 4.
\[ \boxed{\text{Option 4: DataFrame.values}} \]