Add tests to check to_csv for dtypes - float16, float32, float64 and quoting option enabled

Author: akj2018

pandas/tests/frame/methods/test_to_csv.py

@@ -1316,6 +1316,40 @@ def test_to_csv_quoting(self):
         expected = tm.convert_rows_list_to_csv_str(expected_rows)
         assert df.to_csv(quoting=csv.QUOTE_ALL) == expected
 
+    @pytest.mark.parametrize("data, dtype, expected_rows", 
+        [
+            # Test Case 1: float16 precision
+            (
+                {"col": [8.57, 0.156, -0.312, 123.3, -54.5, np.nan]},
+                "float16",
+                ['"","col"', '0,8.57', '1,0.156', '2,-0.312', '3,123.3', '4,-54.5', '5,""']
+            ),
+
+            # Test Case 2: float32 precision
+            (
+                {"col": [8.57, 1.234567, -2.345678, 1e6, -1.5e6, np.nan]}, 
+                "float32",
+                ['"","col"', '0,8.57', '1,1.234567', '2,-2.345678', '3,1000000.0', '4,-1500000.0', '5,""']
+            ),
+
+            # Test Case 3: float64 precision
+            (
+                {"col": [8.57, 3.141592653589793, -2.718281828459045, 1.01e12, -5.67e11, np.nan]},
+                "float64",
+                ['"","col"', '0,8.57', '1,3.141592653589793', '2,-2.718281828459045', 
+                '3,1010000000000.0', '4,-567000000000.0', '5,""']
+            ),
+        ]
+    )
+    def test_to_csv_decimal_and_nonnumeric_quoting(self, data, dtype, expected_rows):
+        # https://github.com/pandas-dev/pandas/issues/60699
+        # combination of float dtype, no special formatting and 
+        # quoting is specified (quoting=csv.QUOTE_NONNUMERIC)
+        df = pd.DataFrame(data, dtype=dtype)
+        result = df.to_csv(quoting=csv.QUOTE_NONNUMERIC) 
+        expected = tm.convert_rows_list_to_csv_str(expected_rows)
+        assert result == expected
+
     def test_period_index_date_overflow(self):
         # see gh-15982