ENH: applymap get kwargs #39987

doc/source/whatsnew/v1.3.0.rst

@@ -128,6 +128,7 @@ Other enhancements
 - :meth:`.Rolling.sum`, :meth:`.Expanding.sum`, :meth:`.Rolling.mean`, :meth:`.Expanding.mean`, :meth:`.Rolling.median`, :meth:`.Expanding.median`, :meth:`.Rolling.max`, :meth:`.Expanding.max`, :meth:`.Rolling.min`, and :meth:`.Expanding.min` now support ``Numba`` execution with the ``engine`` keyword (:issue:`38895`)
 - :meth:`DataFrame.apply` can now accept NumPy unary operators as strings, e.g. ``df.apply("sqrt")``, which was already the case for :meth:`Series.apply` (:issue:`39116`)
 - :meth:`DataFrame.apply` can now accept non-callable DataFrame properties as strings, e.g. ``df.apply("size")``, which was already the case for :meth:`Series.apply` (:issue:`39116`)
+- :meth:`DataFrame.applymap` can now accept kwargs to pass on to func (:issue:`39987`)
 - Disallow :class:`DataFrame` indexer for ``iloc`` for :meth:`Series.__getitem__` and :meth:`DataFrame.__getitem__`, (:issue:`39004`)
 - :meth:`Series.apply` can now accept list-like or dictionary-like arguments that aren't lists or dictionaries, e.g. ``ser.apply(np.array(["sum", "mean"]))``, which was already the case for :meth:`DataFrame.apply` (:issue:`39140`)
 - :meth:`DataFrame.plot.scatter` can now accept a categorical column as the argument to ``c`` (:issue:`12380`, :issue:`31357`)

pandas/core/frame.py

@@ -13,6 +13,7 @@
 import collections
 from collections import abc
 import datetime
+import functools
 from io import StringIO
 import itertools
 import mmap
@@ -3332,7 +3333,6 @@ def _ixs(self, i: int, axis: int = 0):
 
             # this is a cached value, mark it so
             result._set_as_cached(label, self)
-
             return result
 
     def _get_column_array(self, i: int) -> ArrayLike:
@@ -8440,7 +8440,7 @@ def apply(
         return op.apply()
 
     def applymap(
-        self, func: PythonFuncType, na_action: Optional[str] = None
+        self, func: PythonFuncType, na_action: Optional[str] = None, **kwargs
     ) -> DataFrame:
         """
         Apply a function to a Dataframe elementwise.
@@ -8454,6 +8454,9 @@ def applymap(
             Python function, returns a single value from a single value.
         na_action : {None, 'ignore'}, default None
             If ‘ignore’, propagate NaN values, without passing them to func.
+        **kwargs
+            Additional keyword arguments to pass as keywords arguments to
+            `func`.
 
             .. versionadded:: 1.2
 
@@ -8508,6 +8511,7 @@ def applymap(
                 f"na_action must be 'ignore' or None. Got {repr(na_action)}"
             )
         ignore_na = na_action == "ignore"
+        func = functools.partial(func, **kwargs)
 
         # if we have a dtype == 'M8[ns]', provide boxed values
         def infer(x):

pandas/tests/apply/test_frame_apply.py

@@ -560,6 +560,12 @@ def test_applymap(float_frame):
             tm.assert_frame_equal(result, expected)
 
 
+def test_applymap_kwargs():
+    result = DataFrame([[1, 2], [3, 4]]).applymap(lambda x, y: x + y, y=2)
+    expected = DataFrame([[3, 4], [5, 6]])
+    tm.assert_frame_equal(result, expected)
+
+
 def test_applymap_na_ignore(float_frame):
     # GH 23803
     strlen_frame = float_frame.applymap(lambda x: len(str(x)))