Closes #3023 to_markdown

PROTO_tests/tests/dataframe_test.py

@@ -1015,6 +1015,34 @@ def test_memory_usage(self):
         )
         assert_series_equal(ak_memory_usage.to_pandas(), pd_memory_usage)
 
+    def test_to_markdown(self):
+        df = ak.DataFrame({"animal_1": ["elk", "pig"], "animal_2": ["dog", "quetzal"]})
+        assert (
+            df.to_markdown() == "+----+------------+------------+\n"
+            "|    | animal_1   | animal_2   |\n"
+            "+====+============+============+\n"
+            "|  0 | elk        | dog        |\n"
+            "+----+------------+------------+\n"
+            "|  1 | pig        | quetzal    |\n"
+            "+----+------------+------------+"
+        )
+
+        assert (
+            df.to_markdown(index=False) == "+------------+------------+\n"
+            "| animal_1   | animal_2   |\n"
+            "+============+============+\n"
+            "| elk        | dog        |\n"
+            "+------------+------------+\n"
+            "| pig        | quetzal    |\n"
+            "+------------+------------+"
+        )
+
+        assert df.to_markdown(tablefmt="grid") == df.to_pandas().to_markdown(tablefmt="grid")
+        assert df.to_markdown(tablefmt="grid", index=False) == df.to_pandas().to_markdown(
+            tablefmt="grid", index=False
+        )
+        assert df.to_markdown(tablefmt="jira") == df.to_pandas().to_markdown(tablefmt="jira")
+
 
 def pda_to_str_helper(pda):
     return ak.array([f"str {i}" for i in pda.to_list()])

PROTO_tests/tests/series_test.py

@@ -244,3 +244,53 @@ def test_map(self):
         result = c.map({1.0: "a", 2.2: "b", 4.4: "c", 5.0: "d", 6.0: "e"})
         assert result.index.values.to_list() == [5, 4, 2, 3, 1]
         assert result.values.to_list() == ["a", "a", "b", "b", "c"]
+
+    def test_to_markdown(self):
+        s = ak.Series(["elk", "pig", "dog", "quetzal"], name="animal")
+        assert (
+            s.to_markdown() == "+----+----------+\n"
+            "|    | animal   |\n"
+            "+====+==========+\n"
+            "|  0 | elk      |\n"
+            "+----+----------+\n"
+            "|  1 | pig      |\n"
+            "+----+----------+\n"
+            "|  2 | dog      |\n"
+            "+----+----------+\n"
+            "|  3 | quetzal  |\n"
+            "+----+----------+"
+        )
+
+        assert (
+            s.to_markdown(index=False) == "+----------+\n"
+            "| animal   |\n"
+            "+==========+\n"
+            "| elk      |\n"
+            "+----------+\n"
+            "| pig      |\n"
+            "+----------+\n"
+            "| dog      |\n"
+            "+----------+\n"
+            "| quetzal  |\n"
+            "+----------+"
+        )
+
+        assert (
+            s.to_markdown(tablefmt="grid") == "+----+----------+\n"
+            "|    | animal   |\n"
+            "+====+==========+\n"
+            "|  0 | elk      |\n"
+            "+----+----------+\n"
+            "|  1 | pig      |\n"
+            "+----+----------+\n"
+            "|  2 | dog      |\n"
+            "+----+----------+\n"
+            "|  3 | quetzal  |\n"
+            "+----+----------+"
+        )
+
+        assert s.to_markdown(tablefmt="grid") == s.to_pandas().to_markdown(tablefmt="grid")
+        assert s.to_markdown(tablefmt="grid", index=False) == s.to_pandas().to_markdown(
+            tablefmt="grid", index=False
+        )
+        assert s.to_markdown(tablefmt="jira") == s.to_pandas().to_markdown(tablefmt="jira")

arkouda/dataframe.py

@@ -2681,6 +2681,66 @@ def to_pandas(self, datalimit=maxTransferBytes, retain_index=False):
         else:
             return pd.DataFrame(data=pandas_data)
 
+    def to_markdown(self, mode="wt", index=True, tablefmt="grid", storage_options=None, **kwargs):
+        r"""
+        Print DataFrame in Markdown-friendly format.
+
+        Parameters
+        ----------
+        mode : str, optional
+            Mode in which file is opened, "wt" by default.
+        index : bool, optional, default True
+            Add index (row) labels.
+        tablefmt: str = "grid"
+            Table format to call from tablulate:
+            https://pypi.org/project/tabulate/
+        storage_options: dict, optional
+            Extra options that make sense for a particular storage connection,
+            e.g. host, port, username, password, etc., if using a URL that will be parsed by fsspec,
+            e.g., starting “s3://”, “gcs://”.
+            An error will be raised if providing this argument with a non-fsspec URL.
+            See the fsspec and backend storage implementation docs for the set
+            of allowed keys and values.
+        **kwargs
+            These parameters will be passed to tabulate.
+
+        Note
+        ----
+        This function should only be called on small DataFrames as it calls pandas.DataFrame.to_markdown:
+        https://pandas.pydata.org/pandas-docs/version/1.2.4/reference/api/pandas.DataFrame.to_markdown.html
+
+        Examples
+        --------
+
+        >>> import arkouda as ak
+        >>> ak.connect()
+        >>> df = ak.DataFrame({"animal_1": ["elk", "pig"], "animal_2": ["dog", "quetzal"]})
+        >>> print(df.to_markdown())
+        +----+------------+------------+
+        |    | animal_1   | animal_2   |
+        +====+============+============+
+        |  0 | elk        | dog        |
+        +----+------------+------------+
+        |  1 | pig        | quetzal    |
+        +----+------------+------------+
+
+
+        Suppress the index:
+
+        >>> print(df.to_markdown(index = False))
+        +------------+------------+
+        | animal_1   | animal_2   |
+        +============+============+
+        | elk        | dog        |
+        +------------+------------+
+        | pig        | quetzal    |
+        +------------+------------+
+
+        """
+        return self.to_pandas().to_markdown(
+            mode=mode, index=index, tablefmt=tablefmt, storage_options=storage_options, **kwargs
+        )
+
     def _prep_data(self, index=False, columns=None):
         # if no columns are stored, we will save all columns
         if columns is None:

arkouda/series.py

@@ -713,6 +713,69 @@ def to_pandas(self) -> pd.Series:
         else:
             return pd.Series(val.to_ndarray(), index=idx)
 
+    def to_markdown(self, mode="wt", index=True, tablefmt="grid", storage_options=None, **kwargs):
+        r"""
+        Print Series in Markdown-friendly format.
+
+        Parameters
+        ----------
+        mode : str, optional
+            Mode in which file is opened, "wt" by default.
+        index : bool, optional, default True
+            Add index (row) labels.
+        tablefmt: str = "grid"
+            Table format to call from tablulate:
+            https://pypi.org/project/tabulate/
+        storage_options: dict, optional
+            Extra options that make sense for a particular storage connection,
+            e.g. host, port, username, password, etc., if using a URL that will be parsed by fsspec,
+            e.g., starting “s3://”, “gcs://”.
+            An error will be raised if providing this argument with a non-fsspec URL.
+            See the fsspec and backend storage implementation docs for the set
+            of allowed keys and values.
+
+        **kwargs
+            These parameters will be passed to tabulate.
+
+        Note
+        ----
+        This function should only be called on small Series as it calls pandas.Series.to_markdown:
+        https://pandas.pydata.org/docs/reference/api/pandas.Series.to_markdown.html
+
+        Examples
+        --------
+
+        >>> import arkouda as ak
+        >>> ak.connect()
+        >>> s = ak.Series(["elk", "pig", "dog", "quetzal"], name="animal")
+        >>> print(s.to_markdown())
+        |    | animal   |
+        |---:|:---------|
+        |  0 | elk      |
+        |  1 | pig      |
+        |  2 | dog      |
+        |  3 | quetzal  |
+
+        Output markdown with a tabulate option.
+
+        >>> print(s.to_markdown(tablefmt="grid"))
+        +----+----------+
+        |    | animal   |
+        +====+==========+
+        |  0 | elk      |
+        +----+----------+
+        |  1 | pig      |
+        +----+----------+
+        |  2 | dog      |
+        +----+----------+
+        |  3 | quetzal  |
+        +----+----------+
+
+        """
+        return self.to_pandas().to_markdown(
+            mode=mode, index=index, tablefmt=tablefmt, storage_options=storage_options, **kwargs
+        )
+
     @typechecked()
     def to_list(self) -> list:
         p = self.to_pandas()

tests/dataframe_test.py

@@ -1398,6 +1398,37 @@ def test_multi_col_merge(self):
                     # assert_frame_equal(sorted_ak.to_pandas()[sorted_columns],
                     # sorted_pd[sorted_columns])
 
+    def test_to_markdown(self):
+        df = ak.DataFrame({"animal_1": ["elk", "pig"], "animal_2": ["dog", "quetzal"]})
+        self.assertEqual(
+            df.to_markdown(),
+            "+----+------------+------------+\n"
+            "|    | animal_1   | animal_2   |\n"
+            "+====+============+============+\n"
+            "|  0 | elk        | dog        |\n"
+            "+----+------------+------------+\n"
+            "|  1 | pig        | quetzal    |\n"
+            "+----+------------+------------+",
+        )
+
+        self.assertEqual(
+            df.to_markdown(index=False),
+            "+------------+------------+\n"
+            "| animal_1   | animal_2   |\n"
+            "+============+============+\n"
+            "| elk        | dog        |\n"
+            "+------------+------------+\n"
+            "| pig        | quetzal    |\n"
+            "+------------+------------+",
+        )
+
+        self.assertEqual(df.to_markdown(tablefmt="grid"), df.to_pandas().to_markdown(tablefmt="grid"))
+        self.assertEqual(
+            df.to_markdown(tablefmt="grid", index=False),
+            df.to_pandas().to_markdown(tablefmt="grid", index=False),
+        )
+        self.assertEqual(df.to_markdown(tablefmt="jira"), df.to_pandas().to_markdown(tablefmt="jira"))
+
 
 def pda_to_str_helper(pda):
     return ak.array([f"str {i}" for i in pda.to_list()])

tests/series_test.py

@@ -101,6 +101,58 @@ def test_shape(self):
         (l,) = s.shape
         self.assertEqual(l, 3)
 
+    def test_to_markdown(self):
+        s = ak.Series(["elk", "pig", "dog", "quetzal"], name="animal")
+        self.assertEqual(
+            s.to_markdown(),
+            "+----+----------+\n"
+            "|    | animal   |\n"
+            "+====+==========+\n"
+            "|  0 | elk      |\n"
+            "+----+----------+\n"
+            "|  1 | pig      |\n"
+            "+----+----------+\n"
+            "|  2 | dog      |\n"
+            "+----+----------+\n"
+            "|  3 | quetzal  |\n"
+            "+----+----------+",
+        )
+        self.assertEqual(
+            s.to_markdown(index=False),
+            "+----------+\n"
+            "| animal   |\n"
+            "+==========+\n"
+            "| elk      |\n"
+            "+----------+\n"
+            "| pig      |\n"
+            "+----------+\n"
+            "| dog      |\n"
+            "+----------+\n"
+            "| quetzal  |\n"
+            "+----------+",
+        )
+        self.assertEqual(
+            s.to_markdown(tablefmt="grid"),
+            "+----+----------+\n"
+            "|    | animal   |\n"
+            "+====+==========+\n"
+            "|  0 | elk      |\n"
+            "+----+----------+\n"
+            "|  1 | pig      |\n"
+            "+----+----------+\n"
+            "|  2 | dog      |\n"
+            "+----+----------+\n"
+            "|  3 | quetzal  |\n"
+            "+----+----------+",
+        )
+
+        self.assertEqual(s.to_markdown(tablefmt="grid"), s.to_pandas().to_markdown(tablefmt="grid"))
+        self.assertEqual(
+            s.to_markdown(tablefmt="grid", index=False),
+            s.to_pandas().to_markdown(tablefmt="grid", index=False),
+        )
+        self.assertEqual(s.to_markdown(tablefmt="jira"), s.to_pandas().to_markdown(tablefmt="jira"))
+
     def test_add(self):
         i = ak.arange(3)
         v = ak.arange(3, 6, 1)