sync "inplace" document strings anywhere possible

pandas/core/frame.py

@@ -240,7 +240,7 @@
         If 1 or 'columns': apply function to each row.""",
     "inplace": """
     inplace : bool, default False
-        If True, performs operation inplace and returns None.""",
+        Whether to modify the DataFrame rather than creating a new one.""",
     "optional_by": """
         by : str or list of str
             Name or list of names to sort by.
@@ -4071,8 +4071,7 @@ def query(self, expr: str, inplace: bool = False, **kwargs):
                 Expanding functionality of backtick quoting for more than only spaces.
 
         inplace : bool
-            Whether the query should modify the data in place or return
-            a modified copy.
+            Whether to modify the DataFrame rather than creating a new one.
         **kwargs
             See the documentation for :func:`eval` for complete details
             on the keyword arguments accepted by :meth:`DataFrame.query`.
@@ -5175,8 +5174,8 @@ def rename(
         copy : bool, default True
             Also copy underlying data.
         inplace : bool, default False
-            Whether to return a new DataFrame. If True then value of copy is
-            ignored.
+            Whether to modify the DataFrame rather than creating a new one.
+            If True then value of copy is ignored.
         level : int or level name, default None
             In case of a MultiIndex, only rename labels in the specified
             level.
@@ -5607,7 +5606,7 @@ def set_index(
         append : bool, default False
             Whether to append columns to existing index.
         inplace : bool, default False
-            If True, modifies the DataFrame in place (do not create a new object).
+            Whether to modify the DataFrame rather than creating a new one.
         verify_integrity : bool, default False
             Check the new index for duplicates. Otherwise defer the check until
             necessary. Setting to False will improve the performance of this
@@ -5884,7 +5883,7 @@ def reset_index(
             Do not try to insert index into dataframe columns. This resets
             the index to the default integer index.
         inplace : bool, default False
-            Modify the DataFrame in place (do not create a new object).
+            Whether to modify the DataFrame rather than creating a new one.
         col_level : int or str, default 0
             If the columns have multiple levels, determines which level the
             labels are inserted into. By default it is inserted into the first
@@ -6171,7 +6170,7 @@ def dropna(
             Labels along other axis to consider, e.g. if you are dropping rows
             these would be a list of columns to include.
         inplace : bool, default False
-            If True, do operation inplace and return None.
+            Whether to modify the DataFrame rather than creating a new one.
 
         Returns
         -------
@@ -6317,7 +6316,7 @@ def drop_duplicates(
             - ``last`` : Drop duplicates except for the last occurrence.
             - False : Drop all duplicates.
         inplace : bool, default False
-            Whether to drop duplicates in place or to return a copy.
+            Whether to modify the DataFrame rather than creating a new one.
         ignore_index : bool, default False
             If True, the resulting axis will be labeled 0, 1, …, n - 1.
 
@@ -6691,7 +6690,7 @@ def sort_index(  # type: ignore[override]
             Sort ascending vs. descending. When the index is a MultiIndex the
             sort direction can be controlled for each level individually.
         inplace : bool, default False
-            If True, perform operation in-place.
+            Whether to modify the DataFrame rather than creating a new one.
         kind : {'quicksort', 'mergesort', 'heapsort', 'stable'}, default 'quicksort'
             Choice of sorting algorithm. See also :func:`numpy.sort` for more
             information. `mergesort` and `stable` are the only stable algorithms. For