Fixed all warning.warn messages for space,full-stop etc issues (#43163)

* Fixed all warning.warn messages for space,fullstop etc issues * fix ppe 8 issues reported * fix ppe 8 issues reported * fix ppe 8 issues reported * After precommit * fixed the expected variable * fixed flake8

Author: Kavya9986

pandas/__init__.py

@@ -207,7 +207,7 @@ def __getattr__(name):
  warnings.warn(
  "The pandas.np module is deprecated "
  "and will be removed from pandas in a future version. "
- "Import numpy directly instead",
+ "Import numpy directly instead.",
  FutureWarning,
  stacklevel=2,
  )
@@ -218,7 +218,7 @@ def __getattr__(name):
  elif name in {"SparseSeries", "SparseDataFrame"}:
  warnings.warn(
  f"The {name} class is removed from pandas. Accessing it from "
- "the top-level namespace will also be removed in the next version",
+ "the top-level namespace will also be removed in the next version.",
  FutureWarning,
  stacklevel=2,
  )

pandas/_libs/parsers.pyx

@@ -1000,7 +1000,7 @@ cdef class TextReader:
  if col_dtype is not None:
  warnings.warn((f"Both a converter and dtype were specified "
  f"for column {name} - only the converter will "
- f"be used"), ParserWarning,
+ f"be used."), ParserWarning,
  stacklevel=5)
  results[i] = _apply_converter(conv, self.parser, i, start, end)
  continue

pandas/_libs/tslibs/nattype.pyx

@@ -143,7 +143,7 @@ cdef class _NaT(datetime):
  return True
  warnings.warn(
  "Comparison of NaT with datetime.date is deprecated in "
- "order to match the standard library behavior.  "
+ "order to match the standard library behavior. "
  "In a future version these will be considered non-comparable.",
  FutureWarning,
  stacklevel=1,

pandas/_libs/tslibs/offsets.pyx

@@ -696,15 +696,15 @@ cdef class BaseOffset:
 
  def onOffset(self, dt) -> bool:
  warnings.warn(
- "onOffset is a deprecated, use is_on_offset instead",
+ "onOffset is a deprecated, use is_on_offset instead.",
  FutureWarning,
  stacklevel=1,
  )
  return self.is_on_offset(dt)
 
  def isAnchored(self) -> bool:
  warnings.warn(
- "isAnchored is a deprecated, use is_anchored instead",
+ "isAnchored is a deprecated, use is_anchored instead.",
  FutureWarning,
  stacklevel=1,
  )

pandas/_libs/tslibs/timedeltas.pyx

@@ -571,7 +571,7 @@ cdef inline timedelta_from_spec(object number, object frac, object unit):
  if unit in ["M", "Y", "y"]:
  warnings.warn(
  "Units 'M', 'Y' and 'y' do not represent unambiguous "
- "timedelta values and will be removed in a future version",
+ "timedelta values and will be removed in a future version.",
  FutureWarning,
  stacklevel=2,
  )

pandas/_libs/tslibs/timestamps.pyx

@@ -171,7 +171,7 @@ cdef class _Timestamp(ABCTimestamp):
  @property
  def freq(self):
  warnings.warn(
- "Timestamp.freq is deprecated and will be removed in a future version",
+ "Timestamp.freq is deprecated and will be removed in a future version.",
  FutureWarning,
  stacklevel=1,
  )
@@ -235,8 +235,8 @@ cdef class _Timestamp(ABCTimestamp):
  # We follow the stdlib datetime behavior of never being equal
  warnings.warn(
  "Comparison of Timestamp with datetime.date is deprecated in "
- "order to match the standard library behavior.  "
- "In a future version these will be considered non-comparable."
+ "order to match the standard library behavior. "
+ "In a future version these will be considered non-comparable. "
  "Use 'ts == pd.Timestamp(date)' or 'ts.date() == date' instead.",
  FutureWarning,
  stacklevel=1,
@@ -425,7 +425,7 @@ cdef class _Timestamp(ABCTimestamp):
  warnings.warn(
  "Timestamp.freq is deprecated and will be removed in a future "
  "version. When you have a freq, use "
- f"freq.{field}(timestamp) instead",
+ f"freq.{field}(timestamp) instead.",
  FutureWarning,
  stacklevel=1,
  )
@@ -858,7 +858,7 @@ cdef class _Timestamp(ABCTimestamp):
  NaT
  """
  if self.nanosecond != 0 and warn:
- warnings.warn("Discarding nonzero nanoseconds in conversion",
+ warnings.warn("Discarding nonzero nanoseconds in conversion.",
  UserWarning, stacklevel=2)
 
  return datetime(self.year, self.month, self.day,

pandas/core/arrays/datetimelike.py

@@ -1186,7 +1186,7 @@ def _addsub_object_array(self, other: np.ndarray, op):
 
  warnings.warn(
  "Adding/subtracting object-dtype array to "
- f"{type(self).__name__} not vectorized",
+ f"{type(self).__name__} not vectorized.",
  PerformanceWarning,
  )
 

pandas/core/arrays/datetimes.py

@@ -744,7 +744,7 @@ def _add_offset(self, offset) -> DatetimeArray:
 
  except NotImplementedError:
  warnings.warn(
- "Non-vectorized DateOffset being applied to Series or DatetimeIndex",
+ "Non-vectorized DateOffset being applied to Series or DatetimeIndex.",
  PerformanceWarning,
  )
  result = self.astype("O") + offset
@@ -1186,8 +1186,8 @@ def to_perioddelta(self, freq) -> TimedeltaArray:
  # Deprecaation GH#34853
  warnings.warn(
  "to_perioddelta is deprecated and will be removed in a "
- "future version.  "
- "Use `dtindex - dtindex.to_period(freq).to_timestamp()` instead",
+ "future version. "
+ "Use `dtindex - dtindex.to_period(freq).to_timestamp()` instead.",
  FutureWarning,
  # stacklevel chosen to be correct for when called from DatetimeIndex
  stacklevel=3,
@@ -1353,7 +1353,7 @@ def weekofyear(self):
  warnings.warn(
  "weekofyear and week have been deprecated, please use "
  "DatetimeIndex.isocalendar().week instead, which returns "
- "a Series.  To exactly reproduce the behavior of week and "
+ "a Series. To exactly reproduce the behavior of week and "
  "weekofyear and return an Index, you may call "
  "pd.Int64Index(idx.isocalendar().week)",
  FutureWarning,

pandas/core/arrays/sparse/array.py

@@ -407,7 +407,7 @@ def __init__(
  if is_datetime64tz_dtype(data.dtype):
  warnings.warn(
  f"Creating SparseArray from {data.dtype} data "
- "loses timezone information.  Cast to object before "
+ "loses timezone information. Cast to object before "
  "sparse to retain timezone information.",
  UserWarning,
  stacklevel=2,

pandas/core/computation/align.py

@@ -124,7 +124,7 @@ def _align_core(terms):
  w = (
  f"Alignment difference on axis {axis} is larger "
  f"than an order of magnitude on term {repr(terms[i].name)}, "
- f"by more than {ordm:.4g}; performance may suffer"
+ f"by more than {ordm:.4g}; performance may suffer."
  )
  warnings.warn(w, category=PerformanceWarning, stacklevel=6)