[SPARK-35012][PYTHON] Port Koalas DataFrame-related unit tests into PySpark

### What changes were proposed in this pull request?
Now that we merged the Koalas main code into the PySpark code base (#32036), we should port the Koalas DataFrame-related unit tests to PySpark.

### Why are the changes needed?
Currently, the pandas-on-Spark modules are not fully tested. We should enable the DataFrame-related unit tests first.

### Does this PR introduce _any_ user-facing change?
No.

### How was this patch tested?
Enable DataFrame-related unit tests.

Closes #32131 from xinrong-databricks/port.test_dataframe_related.

Lead-authored-by: Xinrong Meng <xinrong.meng@databricks.com>
Co-authored-by: xinrong-databricks <47337188+xinrong-databricks@users.noreply.github.com>
Signed-off-by: Takuya UESHIN <ueshin@databricks.com>

Author: xinrong-meng

dev/sparktestsupport/modules.py

@@ -612,6 +612,9 @@ def __hash__(self):
         "pyspark.pandas.typedef.typehints",
         # unittests
         "pyspark.pandas.tests.test_dataframe",
+        "pyspark.pandas.tests.test_dataframe_conversion",
+        "pyspark.pandas.tests.test_dataframe_spark_io",
+        "pyspark.pandas.tests.test_frame_spark",
         "pyspark.pandas.tests.test_ops_on_diff_frames",
         "pyspark.pandas.tests.test_ops_on_diff_frames_groupby",
         "pyspark.pandas.tests.test_ops_on_diff_frames_groupby_expanding",

python/pyspark/pandas/tests/test_dataframe_conversion.py

@@ -0,0 +1,274 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import os
+import shutil
+import string
+import tempfile
+import unittest
+
+import numpy as np
+import pandas as pd
+
+from pyspark import pandas as pp
+from distutils.version import LooseVersion
+from pyspark.pandas.testing.utils import ReusedSQLTestCase, SQLTestUtils, TestUtils
+
+
+class DataFrameConversionTest(ReusedSQLTestCase, SQLTestUtils, TestUtils):
+    """Test cases for "small data" conversion and I/O."""
+
+    def setUp(self):
+        self.tmp_dir = tempfile.mkdtemp(prefix=DataFrameConversionTest.__name__)
+
+    def tearDown(self):
+        shutil.rmtree(self.tmp_dir, ignore_errors=True)
+
+    @property
+    def pdf(self):
+        return pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]}, index=[0, 1, 3])
+
+    @property
+    def kdf(self):
+        return pp.from_pandas(self.pdf)
+
+    @staticmethod
+    def strip_all_whitespace(str):
+        """A helper function to remove all whitespace from a string."""
+        return str.translate({ord(c): None for c in string.whitespace})
+
+    def test_to_html(self):
+        expected = self.strip_all_whitespace(
+            """
+            <table border="1" class="dataframe">
+              <thead>
+                <tr style="text-align: right;"><th></th><th>a</th><th>b</th></tr>
+              </thead>
+              <tbody>
+                <tr><th>0</th><td>1</td><td>4</td></tr>
+                <tr><th>1</th><td>2</td><td>5</td></tr>
+                <tr><th>3</th><td>3</td><td>6</td></tr>
+              </tbody>
+            </table>
+            """
+        )
+        got = self.strip_all_whitespace(self.kdf.to_html())
+        self.assert_eq(got, expected)
+
+        # with max_rows set
+        expected = self.strip_all_whitespace(
+            """
+            <table border="1" class="dataframe">
+              <thead>
+                <tr style="text-align: right;"><th></th><th>a</th><th>b</th></tr>
+              </thead>
+              <tbody>
+                <tr><th>0</th><td>1</td><td>4</td></tr>
+                <tr><th>1</th><td>2</td><td>5</td></tr>
+              </tbody>
+            </table>
+            """
+        )
+        got = self.strip_all_whitespace(self.kdf.to_html(max_rows=2))
+        self.assert_eq(got, expected)
+
+    @staticmethod
+    def get_excel_dfs(koalas_location, pandas_location):
+        return {
+            "got": pd.read_excel(koalas_location, index_col=0),
+            "expected": pd.read_excel(pandas_location, index_col=0),
+        }
+
+    @unittest.skip("openpyxl")
+    def test_to_excel(self):
+        with self.temp_dir() as dirpath:
+            pandas_location = dirpath + "/" + "output1.xlsx"
+            koalas_location = dirpath + "/" + "output2.xlsx"
+
+            pdf = self.pdf
+            kdf = self.kdf
+            kdf.to_excel(koalas_location)
+            pdf.to_excel(pandas_location)
+            dataframes = self.get_excel_dfs(koalas_location, pandas_location)
+            self.assert_eq(dataframes["got"], dataframes["expected"])
+
+            kdf.a.to_excel(koalas_location)
+            pdf.a.to_excel(pandas_location)
+            dataframes = self.get_excel_dfs(koalas_location, pandas_location)
+            self.assert_eq(dataframes["got"], dataframes["expected"])
+
+            pdf = pd.DataFrame({"a": [1, None, 3], "b": ["one", "two", None]}, index=[0, 1, 3])
+
+            kdf = pp.from_pandas(pdf)
+
+            kdf.to_excel(koalas_location, na_rep="null")
+            pdf.to_excel(pandas_location, na_rep="null")
+            dataframes = self.get_excel_dfs(koalas_location, pandas_location)
+            self.assert_eq(dataframes["got"], dataframes["expected"])
+
+            pdf = pd.DataFrame({"a": [1.0, 2.0, 3.0], "b": [4.0, 5.0, 6.0]}, index=[0, 1, 3])
+
+            kdf = pp.from_pandas(pdf)
+
+            kdf.to_excel(koalas_location, float_format="%.1f")
+            pdf.to_excel(pandas_location, float_format="%.1f")
+            dataframes = self.get_excel_dfs(koalas_location, pandas_location)
+            self.assert_eq(dataframes["got"], dataframes["expected"])
+
+            kdf.to_excel(koalas_location, header=False)
+            pdf.to_excel(pandas_location, header=False)
+            dataframes = self.get_excel_dfs(koalas_location, pandas_location)
+            self.assert_eq(dataframes["got"], dataframes["expected"])
+
+            kdf.to_excel(koalas_location, index=False)
+            pdf.to_excel(pandas_location, index=False)
+            dataframes = self.get_excel_dfs(koalas_location, pandas_location)
+            self.assert_eq(dataframes["got"], dataframes["expected"])
+
+    def test_to_json(self):
+        pdf = self.pdf
+        kdf = pp.from_pandas(pdf)
+
+        self.assert_eq(kdf.to_json(orient="records"), pdf.to_json(orient="records"))
+
+    def test_to_json_negative(self):
+        kdf = pp.from_pandas(self.pdf)
+
+        with self.assertRaises(NotImplementedError):
+            kdf.to_json(orient="table")
+
+        with self.assertRaises(NotImplementedError):
+            kdf.to_json(lines=False)
+
+    def test_read_json_negative(self):
+        with self.assertRaises(NotImplementedError):
+            pp.read_json("invalid", lines=False)
+
+    def test_to_json_with_path(self):
+        pdf = pd.DataFrame({"a": [1], "b": ["a"]})
+        kdf = pp.DataFrame(pdf)
+
+        kdf.to_json(self.tmp_dir, num_files=1)
+        expected = pdf.to_json(orient="records")
+
+        output_paths = [path for path in os.listdir(self.tmp_dir) if path.startswith("part-")]
+        assert len(output_paths) > 0
+        output_path = "%s/%s" % (self.tmp_dir, output_paths[0])
+        self.assertEqual("[%s]" % open(output_path).read().strip(), expected)
+
+    def test_to_json_with_partition_cols(self):
+        pdf = pd.DataFrame({"a": [1, 2, 3], "b": ["a", "b", "c"]})
+        kdf = pp.DataFrame(pdf)
+
+        kdf.to_json(self.tmp_dir, partition_cols="b", num_files=1)
+
+        partition_paths = [path for path in os.listdir(self.tmp_dir) if path.startswith("b=")]
+        assert len(partition_paths) > 0
+        for partition_path in partition_paths:
+            column, value = partition_path.split("=")
+            expected = pdf[pdf[column] == value].drop("b", axis=1).to_json(orient="records")
+
+            output_paths = [
+                path
+                for path in os.listdir("%s/%s" % (self.tmp_dir, partition_path))
+                if path.startswith("part-")
+            ]
+            assert len(output_paths) > 0
+            output_path = "%s/%s/%s" % (self.tmp_dir, partition_path, output_paths[0])
+            with open(output_path) as f:
+                self.assertEqual("[%s]" % open(output_path).read().strip(), expected)
+
+    @unittest.skip("Pyperclip could not find a copy/paste mechanism for Linux.")
+    def test_to_clipboard(self):
+        pdf = self.pdf
+        kdf = self.kdf
+
+        self.assert_eq(kdf.to_clipboard(), pdf.to_clipboard())
+        self.assert_eq(kdf.to_clipboard(excel=False), pdf.to_clipboard(excel=False))
+        self.assert_eq(
+            kdf.to_clipboard(sep=";", index=False), pdf.to_clipboard(sep=";", index=False)
+        )
+
+    def test_to_latex(self):
+        pdf = self.pdf
+        kdf = self.kdf
+
+        self.assert_eq(kdf.to_latex(), pdf.to_latex())
+        self.assert_eq(kdf.to_latex(col_space=2), pdf.to_latex(col_space=2))
+        self.assert_eq(kdf.to_latex(header=True), pdf.to_latex(header=True))
+        self.assert_eq(kdf.to_latex(index=False), pdf.to_latex(index=False))
+        self.assert_eq(kdf.to_latex(na_rep="-"), pdf.to_latex(na_rep="-"))
+        self.assert_eq(kdf.to_latex(float_format="%.1f"), pdf.to_latex(float_format="%.1f"))
+        self.assert_eq(kdf.to_latex(sparsify=False), pdf.to_latex(sparsify=False))
+        self.assert_eq(kdf.to_latex(index_names=False), pdf.to_latex(index_names=False))
+        self.assert_eq(kdf.to_latex(bold_rows=True), pdf.to_latex(bold_rows=True))
+        self.assert_eq(kdf.to_latex(decimal=","), pdf.to_latex(decimal=","))
+        if LooseVersion(pd.__version__) < LooseVersion("1.0.0"):
+            self.assert_eq(kdf.to_latex(encoding="ascii"), pdf.to_latex(encoding="ascii"))
+
+    def test_to_records(self):
+        if LooseVersion(pd.__version__) >= LooseVersion("0.24.0"):
+            pdf = pd.DataFrame({"A": [1, 2], "B": [0.5, 0.75]}, index=["a", "b"])
+
+            kdf = pp.from_pandas(pdf)
+
+            self.assert_eq(kdf.to_records(), pdf.to_records())
+            self.assert_eq(kdf.to_records(index=False), pdf.to_records(index=False))
+            self.assert_eq(kdf.to_records(index_dtypes="<S2"), pdf.to_records(index_dtypes="<S2"))
+
+    def test_from_records(self):
+        # Assert using a dict as input
+        self.assert_eq(
+            pp.DataFrame.from_records({"A": [1, 2, 3]}), pd.DataFrame.from_records({"A": [1, 2, 3]})
+        )
+        # Assert using a list of tuples as input
+        self.assert_eq(
+            pp.DataFrame.from_records([(1, 2), (3, 4)]), pd.DataFrame.from_records([(1, 2), (3, 4)])
+        )
+        # Assert using a NumPy array as input
+        self.assert_eq(pp.DataFrame.from_records(np.eye(3)), pd.DataFrame.from_records(np.eye(3)))
+        # Asserting using a custom index
+        self.assert_eq(
+            pp.DataFrame.from_records([(1, 2), (3, 4)], index=[2, 3]),
+            pd.DataFrame.from_records([(1, 2), (3, 4)], index=[2, 3]),
+        )
+        # Assert excluding excluding column(s)
+        self.assert_eq(
+            pp.DataFrame.from_records({"A": [1, 2, 3], "B": [1, 2, 3]}, exclude=["B"]),
+            pd.DataFrame.from_records({"A": [1, 2, 3], "B": [1, 2, 3]}, exclude=["B"]),
+        )
+        # Assert limiting to certain column(s)
+        self.assert_eq(
+            pp.DataFrame.from_records({"A": [1, 2, 3], "B": [1, 2, 3]}, columns=["A"]),
+            pd.DataFrame.from_records({"A": [1, 2, 3], "B": [1, 2, 3]}, columns=["A"]),
+        )
+        # Assert limiting to a number of rows
+        self.assert_eq(
+            pp.DataFrame.from_records([(1, 2), (3, 4)], nrows=1),
+            pd.DataFrame.from_records([(1, 2), (3, 4)], nrows=1),
+        )
+
+
+if __name__ == "__main__":
+    from pyspark.pandas.tests.test_dataframe_conversion import *  # noqa: F401
+
+    try:
+        import xmlrunner  # type: ignore[import]
+        testRunner = xmlrunner.XMLTestRunner(output='target/test-reports', verbosity=2)
+    except ImportError:
+        testRunner = None
+    unittest.main(testRunner=testRunner, verbosity=2)