GH-33377: [Python] Table.drop should support passing a single column

python/pyarrow/table.pxi

@@ -4664,24 +4664,24 @@ cdef class Table(_PandasConvertible):
 
         return pyarrow_wrap_table(c_table)
 
-    def drop(self, columns):
+    def drop_columns(self, columns):
         """
         Drop one or more columns and return a new table.
 
         Parameters
         ----------
-        columns : list of str
-            List of field names referencing existing columns.
+        columns : str or list[str]
+            Field name(s) referencing existing column(s).
 
         Raises
         ------
         KeyError
-            If any of the passed columns name are not existing.
+            If any of the passed column names do not exist.
 
         Returns
         -------
         Table
-            New table without the columns.
+            New table without the column(s).
 
         Examples
         --------
@@ -4693,19 +4693,22 @@ cdef class Table(_PandasConvertible):
 
         Drop one column:
 
-        >>> table.drop(["animals"])
+        >>> table.drop_columns("animals")
         pyarrow.Table
         n_legs: int64
         ----
         n_legs: [[2,4,5,100]]
 
-        Drop more columns:
+        Drop one or more columns:
 
-        >>> table.drop(["n_legs", "animals"])
+        >>> table.drop_columns(["n_legs", "animals"])
         pyarrow.Table
         ...
         ----
         """
+        if isinstance(columns, str):
+            columns = [columns]
+
         indices = []
         for col in columns:
             idx = self.schema.get_field_index(col)
@@ -4722,6 +4725,10 @@ cdef class Table(_PandasConvertible):
 
         return table
 
+    def drop(self, columns):
+        """Alias of Table.drop_columns, but kept for backwards compatibility."""
+        return self.drop_columns(columns)
+
     def group_by(self, keys):
         """Declare a grouping over the columns of the table.
 

python/pyarrow/tests/test_dataset.py

@@ -3906,7 +3906,7 @@ def test_write_dataset_with_scanner(tempdir):
         load_back = ds.dataset(tempdir2, format='ipc', partitioning=["b"])
         load_back_table = load_back.to_table()
         assert dict(load_back_table.to_pydict()
-                    ) == table.drop(["a"]).to_pydict()
+                    ) == table.drop_columns("a").to_pydict()
 
 
 @pytest.mark.parquet

python/pyarrow/tests/test_table.py

@@ -1050,17 +1050,40 @@ def test_table_set_column():
     assert t2.equals(expected)
 
 
-def test_table_drop():
+def test_table_drop_columns():
     """ drop one or more columns given labels"""
     a = pa.array(range(5))
     b = pa.array([-10, -5, 0, 5, 10])
     c = pa.array(range(5, 10))
 
+    table = pa.Table.from_arrays([a, b, c], names=('a', 'b', 'c'))
+    t2 = table.drop_columns(['a', 'b'])
+    t3 = table.drop_columns('a')
+
+    exp_t2 = pa.Table.from_arrays([c], names=('c',))
+    assert exp_t2.equals(t2)
+    exp_t3 = pa.Table.from_arrays([b, c], names=('b', 'c',))
+    assert exp_t3.equals(t3)
+
+    # -- raise KeyError if column not in Table
+    with pytest.raises(KeyError, match="Column 'd' not found"):
+        table.drop_columns(['d'])
+
+
+def test_table_drop():
+    """ verify the alias of drop_columns is working"""
+    a = pa.array(range(5))
+    b = pa.array([-10, -5, 0, 5, 10])
+    c = pa.array(range(5, 10))
+
     table = pa.Table.from_arrays([a, b, c], names=('a', 'b', 'c'))
     t2 = table.drop(['a', 'b'])
+    t3 = table.drop('a')
 
-    exp = pa.Table.from_arrays([c], names=('c',))
-    assert exp.equals(t2)
+    exp_t2 = pa.Table.from_arrays([c], names=('c',))
+    assert exp_t2.equals(t2)
+    exp_t3 = pa.Table.from_arrays([b, c], names=('b', 'c',))
+    assert exp_t3.equals(t3)
 
     # -- raise KeyError if column not in Table
     with pytest.raises(KeyError, match="Column 'd' not found"):