FEAT: Implement df.applymap and Series.apply [DO NOT UPSTREAM] (modin…

…-project#9)

Co-authored-by: Mahesh Vashishtha <mvashishtha@users.noreply.github.com>
---------

Co-authored-by: Mahesh Vashishtha <mvashishtha@users.noreply.github.com>

modin/pandas/base.py

@@ -873,6 +873,15 @@ def apply(
         Apply a function along an axis of the `BasePandasDataset`.
         """
         import cloudpickle
+        import pickle
+        import sys
+
+        if sys.version_info.major == 3 and sys.version_info.minor != 8:
+            version = ".".join(map(str, sys.version_info[:3]))
+            warnings.warn(
+                f"current Python version is {version}, but expected 3.8. User defined"
+                + " functions may not work as expected due to compatibility issues."
+            )
 
         def error_raiser(msg, exception):
             """Convert passed exception to the same type as pandas do and raise it."""
@@ -909,7 +918,7 @@ def error_raiser(msg, exception):
             **kwds,
         )
         query_compiler = self._query_compiler.apply(
-            cloudpickle.dumps(func),
+            cloudpickle.dumps(func, protocol=pickle.DEFAULT_PROTOCOL),
             axis,
             args=args,
             raw=raw,

modin/pandas/dataframe.py

@@ -384,11 +384,29 @@ def add_suffix(self, suffix):  # noqa: PR01, RT01, D200
         return DataFrame(query_compiler=self._query_compiler.add_suffix(suffix))
 
     def applymap(self, func, na_action: Optional[str] = None, **kwargs):
+        import cloudpickle
+        import pickle
+        import sys
+
+        if sys.version_info.major == 3 and sys.version_info.minor != 8:
+            version = ".".join(map(str, sys.version_info[:3]))
+            warnings.warn(
+                f"current Python version is {version}, but expected 3.8. User defined"
+                + " functions may not work as expected due to compatibility issues."
+            )
+
         if not callable(func):
             raise ValueError("'{0}' object is not callable".format(type(func)))
+        if na_action not in ("ignore", None):
+            raise ValueError(f"na_action must be 'ignore' or None. Got {na_action}")
+
+        output_meta = self._to_pandas().applymap(func, na_action=na_action, **kwargs)
         return DataFrame(
             query_compiler=self._query_compiler.applymap(
-                func, na_action=na_action, **kwargs
+                cloudpickle.dumps(func, protocol=pickle.DEFAULT_PROTOCOL),
+                na_action=na_action,
+                output_meta=output_meta,
+                **kwargs,
             )
         )
 

modin/pandas/series.py

@@ -609,6 +609,15 @@ def apply(
         """
         Invoke function on values of Series.
         """
+        import sys
+
+        if sys.version_info.major == 3 and sys.version_info.minor != 8:
+            version = ".".join(map(str, sys.version_info[:3]))
+            warnings.warn(
+                f"current Python version is {version}, but expected 3.8. User defined"
+                + " functions may not work as expected due to compatibility issues."
+            )
+
         self._validate_function(func)
         # apply and aggregate have slightly different behaviors, so we have to use
         # each one separately to determine the correct return type. In the case of
@@ -1203,17 +1212,30 @@ def map(self, arg, na_action=None):  # noqa: PR01, RT01, D200
         """
         Map values of Series according to input correspondence.
         """
+        import cloudpickle
+        import pickle
+        import sys
+
+        if sys.version_info.major == 3 and sys.version_info.minor != 8:
+            version = ".".join(map(str, sys.version_info[:3]))
+            warnings.warn(
+                f"current Python version is {version}, but expected 3.8. User defined"
+                + " functions may not work as expected due to compatibility issues."
+            )
+
         if not callable(arg) and hasattr(arg, "get"):
             mapper = arg
 
             def arg(s):
                 return mapper.get(s, np.nan)
 
+        output_meta = self._to_pandas().map(arg, na_action)
+
+        func = lambda s: s if pandas.isnull(s) and na_action else arg(s)
         return self.__constructor__(
             query_compiler=self._query_compiler.applymap(
-                lambda s: arg(s)
-                if pandas.isnull(s) is not True or na_action is None
-                else s
+                cloudpickle.dumps(func, protocol=pickle.DEFAULT_PROTOCOL),
+                output_meta=output_meta,
             )
         )