in python, pls explain and make sure the answer is correct, will upvote!

Use the .drop() method to drop both the rank1 and rank2 columns you created in fruit_info_mod1. Note that drop does not change the table, but instead returns a new table with fewer columns or rows. In this case, assign the result to fruit_info_original. Hint: Look through the documentation (follow the link!) to see how you can drop multiple columns of a Pandas dataframe at once using a list of column names. Nifty trick: Use df . columns [df . columns.str.startswith ( 'STRING' )] to retrieve all indices starting with convert an index to an array of index names to obtain a list of column names to drop. Combining these gives df.columns [df. columns.str.startswith( 'STRING') ] .values.tolist(), and will return a list of all column names starting with . This can be used in conjunction with the hint to remove all columns starting with rank. fruit_info_original = fruit_info_mod1.drop(columns=['rank1', 'rank2'], axis = 1) \# print fruit_info_original 50]: grader. check( "q0_c") 50] : q0_c results: q0_c - 1 result: Test case failed Trying: fruit_info_original.shape ==(4,2) Expecting: True Line 1, in q0_c 0 Failed example: fruit_info_original.shape ==(4,2) Expected: True Got: False q0_c - 2 result: Test case failed Trying: (fruit_info_original.columns == ['fruit', 'color']).all() Expecting: True Line 1, in q0_c 1 Failed example: (fruit_info_original.columns == ['fruit', 'color']).all() Exception raised: Traceback (most recent call last): File "/Users/erica/opt/anaconda3/lib/python3.8/doctest.py", line 1336, in _run exec (compile (example.source, filename, "single", File"", line 1, in (fruit_info_original.columns == ['fruit', 'color']).all() File "/Users/erica/opt/anaconda3/lib/python3.8/site-packages/pandas/core/indexes/base.py", line 136, in cmp _method result = ops.comp_method_OBJECT_ARRAY (op, self._values, other) File "/Users/erica/opt/anaconda3/lib/python3.8/site-packages/pandas/core/ops/array_ops.py", line 53, in com p_method_OBJECT_ARRAY raise ValueError("Shapes must match", x.shape, y.shape)