ENH: Use stacklevel in warnings

pandas/core/algorithms.py

@@ -35,6 +35,7 @@
     npt,
 )
 from pandas.util._decorators import doc
+from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.cast import (
     construct_1d_object_array_from_listlike,
@@ -1550,7 +1551,7 @@ def searchsorted(
 _diff_special = {"float64", "float32", "int64", "int32", "int16", "int8"}
 
 
-def diff(arr, n: int, axis: int = 0, stacklevel: int = 3):
+def diff(arr, n: int, axis: int = 0):
     """
     difference of n between self,
     analogous to s-s.shift(n)
@@ -1596,7 +1597,7 @@ def diff(arr, n: int, axis: int = 0, stacklevel: int = 3):
                 "dtype lost in 'diff()'. In the future this will raise a "
                 "TypeError. Convert to a suitable dtype prior to calling 'diff'.",
                 FutureWarning,
-                stacklevel=stacklevel,
+                stacklevel=find_stack_level(),
             )
             arr = np.asarray(arr)
             dtype = arr.dtype

pandas/core/arraylike.py

@@ -337,7 +337,9 @@ def reconstruct(result):
                         "Consider explicitly converting the DataFrame "
                         "to an array with '.to_numpy()' first."
                     )
-                    warnings.warn(msg.format(ufunc), FutureWarning, stacklevel=4)
+                    warnings.warn(
+                        msg.format(ufunc), FutureWarning, stacklevel=find_stack_level()
+                    )
                     return result
                 raise NotImplementedError
             return result

pandas/core/arrays/datetimelike.py

@@ -416,13 +416,12 @@ def astype(self, dtype, copy: bool = True):
         elif is_integer_dtype(dtype):
             # we deliberately ignore int32 vs. int64 here.
             # See https://github.com/pandas-dev/pandas/issues/24381 for more.
-            level = find_stack_level()
             warnings.warn(
                 f"casting {self.dtype} values to int64 with .astype(...) is "
                 "deprecated and will raise in a future version. "
                 "Use .view(...) instead.",
                 FutureWarning,
-                stacklevel=level,
+                stacklevel=find_stack_level(),
             )
 
             values = self.asi8

pandas/core/dtypes/cast.py

@@ -969,13 +969,12 @@ def astype_dt64_to_dt64tz(
             # this should be the only copy
             values = values.copy()
 
-        level = find_stack_level()
         warnings.warn(
             "Using .astype to convert from timezone-naive dtype to "
             "timezone-aware dtype is deprecated and will raise in a "
             "future version.  Use ser.dt.tz_localize instead.",
             FutureWarning,
-            stacklevel=level,
+            stacklevel=find_stack_level(),
         )
 
         # GH#33401 this doesn't match DatetimeArray.astype, which
@@ -986,13 +985,12 @@ def astype_dt64_to_dt64tz(
         # DatetimeArray/DatetimeIndex.astype behavior
         if values.tz is None and aware:
             dtype = cast(DatetimeTZDtype, dtype)
-            level = find_stack_level()
             warnings.warn(
                 "Using .astype to convert from timezone-naive dtype to "
                 "timezone-aware dtype is deprecated and will raise in a "
                 "future version.  Use obj.tz_localize instead.",
                 FutureWarning,
-                stacklevel=level,
+                stacklevel=find_stack_level(),
             )
 
             return values.tz_localize(dtype.tz)
@@ -1006,14 +1004,13 @@ def astype_dt64_to_dt64tz(
             return result
 
         elif values.tz is not None:
-            level = find_stack_level()
             warnings.warn(
                 "Using .astype to convert from timezone-aware dtype to "
                 "timezone-naive dtype is deprecated and will raise in a "
                 "future version.  Use obj.tz_localize(None) or "
                 "obj.tz_convert('UTC').tz_localize(None) instead",
                 FutureWarning,
-                stacklevel=level,
+                stacklevel=find_stack_level(),
             )
 
             result = values.tz_convert("UTC").tz_localize(None)

pandas/core/generic.py

@@ -487,9 +487,10 @@ def _data(self):
     @property
     def _AXIS_NUMBERS(self) -> dict[str, int]:
         """.. deprecated:: 1.1.0"""
-        level = self.ndim + 1
         warnings.warn(
-            "_AXIS_NUMBERS has been deprecated.", FutureWarning, stacklevel=level
+            "_AXIS_NUMBERS has been deprecated.",
+            FutureWarning,
+            stacklevel=find_stack_level(),
         )
         return {"index": 0}
 

pandas/core/groupby/grouper.py

@@ -21,6 +21,7 @@
 )
 from pandas.errors import InvalidIndexError
 from pandas.util._decorators import cache_readonly
+from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.cast import sanitize_to_nanoseconds
 from pandas.core.dtypes.common import (
@@ -964,8 +965,6 @@ def _check_deprecated_resample_kwargs(kwargs, origin):
         From where this function is being called; either Grouper or TimeGrouper. Used
         to determine an approximate stacklevel.
     """
-    from pandas.core.resample import TimeGrouper
-
     # Deprecation warning of `base` and `loffset` since v1.1.0:
     # we are raising the warning here to be able to set the `stacklevel`
     # properly since we need to raise the `base` and `loffset` deprecation
@@ -975,11 +974,6 @@ def _check_deprecated_resample_kwargs(kwargs, origin):
     #   core/groupby/grouper.py::Grouper
     # raising these warnings from TimeGrouper directly would fail the test:
     #   tests/resample/test_deprecated.py::test_deprecating_on_loffset_and_base
-    # hacky way to set the stacklevel: if cls is TimeGrouper it means
-    # that the call comes from a pandas internal call of resample,
-    # otherwise it comes from pd.Grouper
-    stacklevel = (5 if origin is TimeGrouper else 2) + 1
-    # the + 1 is for this helper function, check_deprecated_resample_kwargs
 
     if kwargs.get("base", None) is not None:
         warnings.warn(
@@ -989,7 +983,7 @@ def _check_deprecated_resample_kwargs(kwargs, origin):
             "\nbecomes:\n"
             '\n>>> df.resample(freq="3s", offset="2s")\n',
             FutureWarning,
-            stacklevel=stacklevel,
+            stacklevel=find_stack_level(),
         )
     if kwargs.get("loffset", None) is not None:
         warnings.warn(
@@ -1000,5 +994,5 @@ def _check_deprecated_resample_kwargs(kwargs, origin):
             '\n>>> df = df.resample(freq="3s").mean()'
             '\n>>> df.index = df.index.to_timestamp() + to_offset("8H")\n',
             FutureWarning,
-            stacklevel=stacklevel,
+            stacklevel=find_stack_level(),
         )

pandas/core/internals/array_manager.py

@@ -365,7 +365,7 @@ def diff(self: T, n: int, axis: int) -> T:
             # with axis=0 is equivalent
             assert n == 0
             axis = 0
-        return self.apply(algos.diff, n=n, axis=axis, stacklevel=5)
+        return self.apply(algos.diff, n=n, axis=axis)
 
     def interpolate(self: T, **kwargs) -> T:
         return self.apply_with_block("interpolate", swap_axis=False, **kwargs)

pandas/core/internals/blocks.py

@@ -1122,7 +1122,7 @@ def take_nd(
 
     def diff(self, n: int, axis: int = 1) -> list[Block]:
         """return block for the diff of the values"""
-        new_values = algos.diff(self.values, n, axis=axis, stacklevel=7)
+        new_values = algos.diff(self.values, n, axis=axis)
         return [self.make_block(values=new_values)]
 
     def shift(self, periods: int, axis: int = 0, fill_value: Any = None) -> list[Block]:

pandas/core/series.py

@@ -1012,7 +1012,7 @@ def _get_values_tuple(self, key):
         # mpl hackaround
         if com.any_none(*key):
             result = self._get_values(key)
-            deprecate_ndim_indexing(result, stacklevel=5)
+            deprecate_ndim_indexing(result, stacklevel=find_stack_level())
             return result
 
         if not isinstance(self.index, MultiIndex):

pandas/core/strings/accessor.py

@@ -1427,7 +1427,7 @@ def replace(
                         " In addition, single character regular expressions will "
                         "*not* be treated as literal strings when regex=True."
                     )
-                warnings.warn(msg, FutureWarning, stacklevel=3)
+                warnings.warn(msg, FutureWarning, stacklevel=find_stack_level())
 
         # Check whether repl is valid (GH 13438, GH 15055)
         if not (isinstance(repl, str) or callable(repl)):

pandas/io/excel/_base.py

@@ -519,11 +519,10 @@ def parse(
         if convert_float is None:
             convert_float = True
         else:
-            stacklevel = find_stack_level()
             warnings.warn(
                 "convert_float is deprecated and will be removed in a future version.",
                 FutureWarning,
-                stacklevel=stacklevel,
+                stacklevel=find_stack_level(),
             )
 
         validate_header_arg(header)

pandas/io/formats/style.py

@@ -28,6 +28,7 @@
 )
 from pandas.compat._optional import import_optional_dependency
 from pandas.util._decorators import doc
+from pandas.util._exceptions import find_stack_level
 
 import pandas as pd
 from pandas import (
@@ -310,7 +311,7 @@ def render(
         warnings.warn(
             "this method is deprecated in favour of `Styler.to_html()`",
             FutureWarning,
-            stacklevel=2,
+            stacklevel=find_stack_level(),
         )
         if sparse_index is None:
             sparse_index = get_option("styler.sparse.index")
@@ -1675,7 +1676,7 @@ def where(
         warnings.warn(
             "this method is deprecated in favour of `Styler.applymap()`",
             FutureWarning,
-            stacklevel=2,
+            stacklevel=find_stack_level(),
         )
 
         if other is None:
@@ -1707,7 +1708,7 @@ def set_precision(self, precision: int) -> StylerRenderer:
         warnings.warn(
             "this method is deprecated in favour of `Styler.format(precision=..)`",
             FutureWarning,
-            stacklevel=2,
+            stacklevel=find_stack_level(),
         )
         self.precision = precision
         return self.format(precision=precision, na_rep=self.na_rep)
@@ -2217,7 +2218,7 @@ def set_na_rep(self, na_rep: str) -> StylerRenderer:
         warnings.warn(
             "this method is deprecated in favour of `Styler.format(na_rep=..)`",
             FutureWarning,
-            stacklevel=2,
+            stacklevel=find_stack_level(),
         )
         self.na_rep = na_rep
         return self.format(na_rep=na_rep, precision=self.precision)
@@ -2271,7 +2272,7 @@ def hide_index(
         warnings.warn(
             "this method is deprecated in favour of `Styler.hide(axis='index')`",
             FutureWarning,
-            stacklevel=2,
+            stacklevel=find_stack_level(),
         )
         return self.hide(axis=0, level=level, subset=subset, names=names)
 
@@ -2324,7 +2325,7 @@ def hide_columns(
         warnings.warn(
             "this method is deprecated in favour of `Styler.hide(axis='columns')`",
             FutureWarning,
-            stacklevel=2,
+            stacklevel=find_stack_level(),
         )
         return self.hide(axis=1, level=level, subset=subset, names=names)