DOC: Deprecate null_counts parameter of DataFrame.info

doc/source/whatsnew/v1.2.0.rst

@@ -480,6 +480,7 @@ Deprecations
 - The ``how`` keyword in :meth:`PeriodIndex.astype` is deprecated and will be removed in a future version, use ``index.to_timestamp(how=how)`` instead (:issue:`37982`)
 - Deprecated :meth:`Index.asi8` for :class:`Index` subclasses other than :class:`DatetimeIndex`, :class:`TimedeltaIndex`, and :class:`PeriodIndex` (:issue:`37877`)
 - The ``inplace`` parameter of :meth:`Categorical.remove_unused_categories` is deprecated and will be removed in a future version (:issue:`37643`)
+- The ``null_counts`` parameter of :meth:`DataFrame.info` is deprecated and will be removed in a future version (:issue:`37999`)
 
 .. ---------------------------------------------------------------------------
 

pandas/core/frame.py

@@ -2531,14 +2531,17 @@ def to_html(
                 is used. By default, the setting in
                 ``pandas.options.display.max_info_columns`` is used."""
         ),
-        null_counts_sub=dedent(
+        show_counts_sub=dedent(
             """\
-            null_counts : bool, optional
+            show_counts : bool, optional
                 Whether to show the non-null counts. By default, this is shown
                 only if the DataFrame is smaller than
                 ``pandas.options.display.max_info_rows`` and
                 ``pandas.options.display.max_info_columns``. A value of True always
-                shows the counts, and False never shows the counts."""
+                shows the counts, and False never shows the counts.
+            null_counts : bool, optional
+                .. deprecated:: 1.2.0
+                    Use show_counts instead."""
         ),
         examples_sub=dedent(
             """\
@@ -2639,8 +2642,16 @@ def info(
         buf: Optional[IO[str]] = None,
         max_cols: Optional[int] = None,
         memory_usage: Optional[Union[bool, str]] = None,
+        show_counts: Optional[bool] = None,
         null_counts: Optional[bool] = None,
     ) -> None:
+        if null_counts is not None and show_counts is None:
+            warnings.warn(
+                "null_counts is deprecated. Use show_counts instead",
+                FutureWarning,
+                stacklevel=2,
+            )
+            show_counts = null_counts
         info = DataFrameInfo(
             data=self,
             memory_usage=memory_usage,
@@ -2649,7 +2660,7 @@ def info(
             buf=buf,
             max_cols=max_cols,
             verbose=verbose,
-            show_counts=null_counts,
+            show_counts=show_counts,
         )
 
     def memory_usage(self, index=True, deep=False) -> Series:

pandas/io/formats/info.py

@@ -203,7 +203,7 @@ def render(
             consume the same memory amount for corresponding dtypes. With deep
             memory introspection, a real memory usage calculation is performed
             at the cost of computational resources.
-        %(null_counts_sub)s
+        %(show_counts_sub)s
 
         Returns
         -------

pandas/tests/io/formats/test_format.py

@@ -177,9 +177,9 @@ def test_show_null_counts(self):
         df = DataFrame(1, columns=range(10), index=range(10))
         df.iloc[1, 1] = np.nan
 
-        def check(null_counts, result):
+        def check(show_counts, result):
             buf = StringIO()
-            df.info(buf=buf, null_counts=null_counts)
+            df.info(buf=buf, show_counts=show_counts)
             assert ("non-null" in buf.getvalue()) is result
 
         with option_context(
@@ -194,6 +194,11 @@ def check(null_counts, result):
             check(True, False)
             check(False, False)
 
+        with tm.assert_produces_warning(FutureWarning):  # GH37999
+            buf = StringIO()
+            df.info(buf=buf, null_counts=True)
+            assert "non-null" in buf.getvalue()
+
     def test_repr_truncation(self):
         max_len = 20
         with option_context("display.max_colwidth", max_len):

pandas/tests/io/formats/test_info.py

@@ -161,7 +161,7 @@ def test_info_verbose_with_counts_spacing(
     """Test header column, spacer, first line and last line in verbose mode."""
     frame = DataFrame(np.random.randn(3, size))
     buf = StringIO()
-    frame.info(verbose=True, null_counts=True, buf=buf)
+    frame.info(verbose=True, show_counts=True, buf=buf)
     all_lines = buf.getvalue().splitlines()
     # Here table would contain only header, separator and table lines
     # dframe repr, index summary, memory usage and dtypes are excluded
@@ -480,7 +480,7 @@ def test_info_int_columns():
     # GH#37245
     df = DataFrame({1: [1, 2], 2: [2, 3]}, index=["A", "B"])
     buf = StringIO()
-    df.info(null_counts=True, buf=buf)
+    df.info(show_counts=True, buf=buf)
     result = buf.getvalue()
     expected = textwrap.dedent(
         """\