CLN: String formatting % -> f-strings, flake8

Author: Petr Baev

pandas/core/indexing.py

@@ -303,9 +303,7 @@ def _has_valid_positional_setitem_indexer(self, indexer) -> bool:
                             f"{self.name} cannot enlarge its target object"
                         )
                 elif isinstance(i, dict):
-                    raise IndexError(
-                        f"{self.name} cannot enlarge its target object"
-                    )
+                    raise IndexError(f"{self.name} cannot enlarge its target object")
 
         return True
 
@@ -1167,7 +1165,7 @@ def _validate_read_indexer(
             if missing == len(indexer):
                 raise KeyError(
                     f"None of [{key}] are in the [{self.obj._get_axis_name(axis)}]"
-                    )
+                )
 
             # We (temporarily) allow for some missing keys with .loc, except in
             # some cases (e.g. setting) in which "raise_missing" will be False
@@ -1902,17 +1900,14 @@ def _validate_key(self, key, axis: int):
 
             # check that the key has a numeric dtype
             if not is_numeric_dtype(arr.dtype):
-                raise IndexError(
-                    f".iloc requires numeric indexers, got {arr}"
-                )
+                raise IndexError(f".iloc requires numeric indexers, got {arr}")
 
             # check that the key does not exceed the maximum size of the index
             if len(arr) and (arr.max() >= len_axis or arr.min() < -len_axis):
                 raise IndexError("positional indexers are out-of-bounds")
         else:
             raise ValueError(
-                "Can only index by location with "
-                f"a [{self._valid_types}]"
+                "Can only index by location with " f"a [{self._valid_types}]"
             )
 
     def _has_valid_setitem_indexer(self, indexer):
@@ -2061,8 +2056,7 @@ def _convert_to_indexer(self, obj, axis: int, raise_missing: bool = False):
             return obj
         except ValueError:
             raise ValueError(
-                "Can only index by location with "
-                f"a [{self._valid_types}]"
+                "Can only index by location with " f"a [{self._valid_types}]"
             )
 
 

pandas/core/internals/blocks.py

@@ -144,8 +144,10 @@ def _check_ndim(self, values, ndim):
             ndim = values.ndim
 
         if self._validate_ndim and values.ndim != ndim:
-            raise ValueError("Wrong number of dimensions. "
-                             f"values.ndim != ndim [{values.ndim} != {ndim}]")
+            raise ValueError(
+                "Wrong number of dimensions. "
+                f"values.ndim != ndim [{values.ndim} != {ndim}]"
+            )
         return ndim
 
     @property
@@ -268,8 +270,10 @@ def __repr__(self) -> str:
         else:
 
             shape = " x ".join(pprint_thing(s) for s in self.shape)
-            result = f"{name}: {pprint_thing(self.mgr_locs.indexer)}, " \
-                     f"{shape}, dtype: {self.dtype}"
+            result = (
+                f"{name}: {pprint_thing(self.mgr_locs.indexer)}, "
+                f"{shape}, dtype: {self.dtype}"
+            )
 
         return result
 
@@ -1032,8 +1036,7 @@ def coerce_to_target_dtype(self, other):
                 return self.astype(object)
 
             raise AssertionError(
-                "possible recursion in "
-                f"coerce_to_target_dtype: {self} {other}"
+                "possible recursion in " f"coerce_to_target_dtype: {self} {other}"
             )
 
         elif self.is_timedelta or is_timedelta64_dtype(dtype):
@@ -1043,8 +1046,7 @@ def coerce_to_target_dtype(self, other):
                 return self.astype(object)
 
             raise AssertionError(
-                "possible recursion in "
-                f"coerce_to_target_dtype: {self} {other}"
+                "possible recursion in " f"coerce_to_target_dtype: {self} {other}"
             )
 
         try:
@@ -1189,8 +1191,7 @@ def _interpolate(
         if method in ("krogh", "piecewise_polynomial", "pchip"):
             if not index.is_monotonic:
                 raise ValueError(
-                    f"{method} interpolation requires that the "
-                    "index be monotonic."
+                    f"{method} interpolation requires that the " "index be monotonic."
                 )
         # process 1-d slices in the axis direction
 

pandas/core/internals/construction.py

@@ -167,8 +167,7 @@ def init_ndarray(values, index, columns, dtype=None, copy=False):
             except Exception as orig:
                 # e.g. ValueError when trying to cast object dtype to float64
                 raise ValueError(
-                    f"failed to cast to '{dtype}' (Exception "
-                    f"was: {orig})"
+                    f"failed to cast to '{dtype}' (Exception " f"was: {orig})"
                 ) from orig
 
     index, columns = _get_axes(*values.shape, index=index, columns=columns)

pandas/core/internals/managers.py

@@ -1661,9 +1661,7 @@ def construction_error(tot_items, block_shape, axes, e=None):
         raise e
     if block_shape[0] == 0:
         raise ValueError("Empty data passed with indices specified.")
-    raise ValueError(
-        f"Shape of passed values is {passed}, indices imply {implied}"
-    )
+    raise ValueError(f"Shape of passed values is {passed}, indices imply {implied}")
 
 
 # -----------------------------------------------------------------------

pandas/core/resample.py

@@ -1187,7 +1187,8 @@ def _downsample(self, how, **kwargs):
 
         raise IncompatibleFrequency(
             f"Frequency {ax.freq} cannot be resampled to {self.freq}, "
-            f"as they are not sub or super periods")
+            f"as they are not sub or super periods"
+        )
 
     def _upsample(self, method, limit=None, fill_value=None):
         """