Repository: modin-project/modin

Issue:
test-docs job is failing in push-to-master workflow
https://github.com/modin-project/modin/runs/5854545224?check_suite_focus=true


Discussion:

Resolving patch:
diff --git a/modin/pandas/general.py b/modin/pandas/general.py
--- a/modin/pandas/general.py
+++ b/modin/pandas/general.py
@@ -370,12 +370,32 @@ def unique(values):  # noqa: PR01, RT01, D200
     return Series(values).unique()
 
 
-@_inherit_docstrings(pandas.value_counts, apilink="pandas.value_counts")
+# Adding docstring since pandas docs don't have web section for this function.
 def value_counts(
     values, sort=True, ascending=False, normalize=False, bins=None, dropna=True
-):  # noqa: PR01, RT01, D200
+):
     """
     Compute a histogram of the counts of non-null values.
+
+    Parameters
+    ----------
+    values : ndarray (1-d)
+        Values to perform computation.
+    sort : bool, default: True
+        Sort by values.
+    ascending : bool, default: False
+        Sort in ascending order.
+    normalize : bool, default: False
+        If True then compute a relative histogram.
+    bins : integer, optional
+        Rather than count values, group them into half-open bins,
+        convenience for pd.cut, only works with numeric data.
+    dropna : bool, default: True
+        Don't include counts of NaN.
+
+    Returns
+    -------
+    Series
     """
     return Series(values).value_counts(
         sort=sort,
@@ -673,12 +693,30 @@ def crosstab(
     return DataFrame(pandas_crosstab)
 
 
-@_inherit_docstrings(pandas.lreshape, apilink="pandas.lreshape")
-def lreshape(
-    data: DataFrame, groups, dropna=True, label=None
-):  # noqa: PR01, RT01, D200
+# Adding docstring since pandas docs don't have web section for this function.
+def lreshape(data: DataFrame, groups, dropna=True, label=None):
     """
-    Reshape wide-format data to long.
+    Reshape wide-format data to long. Generalized inverse of ``DataFrame.pivot``.
+
+    Accepts a dictionary, `groups`, in which each key is a new column name
+    and each value is a list of old column names that will be "melted" under
+    the new column name as part of the reshape.
+
+    Parameters
+    ----------
+    data : DataFrame
+        The wide-format DataFrame.
+    groups : dict
+        Dictionary in the form: `{new_name : list_of_columns}`.
+    dropna : bool, default: True
+        Whether include columns whose entries are all NaN or not.
+    label : optional
+        Deprecated parameter.
+
+    Returns
+    -------
+    DataFrame
+        Reshaped DataFrame.
     """
     if not isinstance(data, DataFrame):
         raise ValueError("can not lreshape with instance of type {}".format(type(data)))
diff --git a/modin/pandas/io.py b/modin/pandas/io.py
--- a/modin/pandas/io.py
+++ b/modin/pandas/io.py
@@ -610,16 +610,48 @@ def read_spss(
     )
 
 
-@_inherit_docstrings(pandas.to_pickle, apilink="pandas.to_pickle")
+# Adding docstring since pandas docs don't have web section for this function.
 def to_pickle(
     obj: Any,
     filepath_or_buffer,
     compression: CompressionOptions = "infer",
     protocol: int = pickle.HIGHEST_PROTOCOL,
     storage_options: StorageOptions = None,
-):  # noqa: PR01, RT01, D200
+):  # noqa: RT01
     """
     Pickle (serialize) object to file.
+
+    Parameters
+    ----------
+    obj : any object
+        Any python object.
+    filepath_or_buffer : str, path object, or file-like object
+        String, path object (implementing `os.PathLike[str]`), or file-like
+        object implementing a binary ``write()`` function.
+    compression : str or dict, default: 'infer'
+        For on-the-fly compression of the output data. If `infer` and `filepath_or_buffer`
+        path-like, then detect compression from the following extensions: '.gz',
+        '.bz2', '.zip', '.xz', or '.zst' (otherwise no compression). Set to
+        `None` for no compression. Can also be a dict with key `method` set
+        to one of {`zip`, `gzip`, `bz2`, `zstd`} and other
+        key-value pairs are forwarded to ``zipfile.ZipFile``, ``gzip.GzipFile``,
+        ``bz2.BZ2File``, or ``zstandard.ZstdDecompressor``, respectively. As an
+        example, the following could be passed for faster compression and to create
+        a reproducible gzip archive:
+        `compression={'method': 'gzip', 'compresslevel': 1, 'mtime': 1}`.
+    protocol : int, default: pickle.HIGHEST_PROTOCOL
+        Int which indicates which protocol should be used by the pickler,
+        default HIGHEST_PROTOCOL. The possible values for this parameter depend
+        on the version of Python. For Python 2.x, possible values are 0, 1, 2.
+        For Python>=3.0, 3 is a valid value. For Python >= 3.4, 4 is a valid value.
+        A negative value for the protocol parameter is equivalent to setting its value to
+        HIGHEST_PROTOCOL.
+    storage_options : dict, optional
+        Extra options that make sense for a particular storage connection, e.g.
+        host, port, username, password, etc. For HTTP(S) URLs the key-value pairs
+        are forwarded to ``urllib`` as header options. For other URLs (e.g.
+        starting with "s3://", and "gcs://") the key-value pairs are forwarded to
+        ``fsspec``. Please see ``fsspec`` and ``urllib`` for more details.
     """
     Engine.subscribe(_update_engine)
     from modin.core.execution.dispatching.factories.dispatcher import FactoryDispatcher
@@ -706,7 +738,7 @@ def read_xml(
     )
 
 
-@_inherit_docstrings(pandas.HDFStore, apilink="pandas.HDFStore")
+@_inherit_docstrings(pandas.HDFStore)
 class HDFStore(pandas.HDFStore):  # noqa: PR01, D200
     """
     Dict-like IO interface for storing pandas objects in PyTables.
@@ -763,7 +795,7 @@ def return_handler(*args, **kwargs):
         return method
 
 
-@_inherit_docstrings(pandas.ExcelFile, apilink="pandas.ExcelFile")
+@_inherit_docstrings(pandas.ExcelFile)
 class ExcelFile(pandas.ExcelFile):  # noqa: PR01, D200
     """
     Class for parsing tabular excel sheets into DataFrame objects.


Test patch: