pandas Reshaping, Pivot and Melt, what does print(sorted_df.shape) print after df = pd.DataFrame({'a': [1, 1, 2], 'b': [3, 1, 2], 'orig': [0, 1, 2]})?

Answer, C. (3, 3)

A. (1, 3)

Assumes sorting collapses rows that tie on the sort key into a single row.

B. (3, 2)

Assumes sorting drops the column that was sorted on, as if it were consumed by the operation.

C. (3, 3)

Correct. sort_values only reorders the existing rows, it never adds or removes rows or columns, so a three row, three column frame stays three by three after sorting.

D. (2, 3)

Confuses the row and column counts, as though sorting transposed the frame.

sort_values is a pure reordering operation on the existing rows, it changes the sequence in which rows appear but never their number, and it never touches the set of columns at all. Any operation that would change the shape of a frame, like dropping duplicates or aggregating, is a separate step from sorting.