sdks/python: replace applymap with map in DataFrame

sdks/python/apache_beam/dataframe/frames_test.py

@@ -886,7 +886,7 @@ def test_applymap_na_action(self):
     # doctest framework
     df = pd.DataFrame([[pd.NA, 2.12], [3.356, 4.567]])
     self._run_test(
-        lambda df: df.applymap(lambda x: len(str(x)), na_action='ignore'),
+        lambda df: df.map(lambda x: len(str(x)), na_action='ignore'),
         df,
         # TODO: generate proxy using naive type inference on fn
         check_proxy=False)

sdks/python/apache_beam/runners/interactive/display/pcoll_visualization.py

@@ -26,7 +26,6 @@
 import datetime
 import html
 import logging
-import warnings
 from datetime import timedelta
 from typing import Optional
 
@@ -351,11 +350,7 @@ def display(self, updating_pv=None):
     ]
     # String-ify the dictionaries for display because elements of type dict
     # cannot be ordered.
-    with warnings.catch_warnings():
-      # TODO(yathu) switch to use DataFrame.map when dropped pandas<2.1 support
-      warnings.filterwarnings(
-          "ignore", message="DataFrame.applymap has been deprecated")
-      data = data.applymap(lambda x: str(x) if isinstance(x, dict) else x)
+    data = data.map(lambda x: str(x) if isinstance(x, dict) else x)
 
     if updating_pv:
       # Only updates when data is not empty. Otherwise, consider it a bad
@@ -420,7 +415,7 @@ def _display_dataframe(self, data, update=None):
     format_window_info_in_dataframe(data)
     # Convert the dataframe into rows, each row looks like
     # [column_1_val, column_2_val, ...].
-    rows = data.applymap(lambda x: str(x)).to_dict('split')['data']
+    rows = data.map(lambda x: str(x)).to_dict('split')['data']
     # Convert each row into dict where keys are column index in the datatable
     # to be rendered and values are data from the dataframe. Column index 0 is
     # left out to hold the int index (not part of the data) from dataframe.