String formatting > fstring

pandas/errors/__init__.py

@@ -167,9 +167,7 @@ class AbstractMethodError(NotImplementedError):
     def __init__(self, class_instance, methodtype="method"):
         types = {"method", "classmethod", "staticmethod", "property"}
         if methodtype not in types:
-            msg = "methodtype must be one of {}, got {} instead.".format(
-                methodtype, types
-            )
+            msg = f"methodtype must be one of {methodtype}, got {types} instead."
             raise ValueError(msg)
         self.methodtype = methodtype
         self.class_instance = class_instance
@@ -179,5 +177,5 @@ def __str__(self) -> str:
             name = self.class_instance.__name__
         else:
             name = self.class_instance.__class__.__name__
-        msg = "This {methodtype} must be defined in the concrete class {name}"
-        return msg.format(methodtype=self.methodtype, name=name)
+        msg = f"This {self.methodtype} must be defined in the concrete class {name}"
+        return msg

pandas/tests/arrays/interval/test_ops.py

@@ -83,8 +83,6 @@ def test_overlaps_na(self, constructor, start_shift):
     )
     def test_overlaps_invalid_type(self, constructor, other):
         interval_container = constructor.from_breaks(range(5))
-        msg = "`other` must be Interval-like, got {other}".format(
-            other=type(other).__name__
-        )
+        msg = f"`other` must be Interval-like, got {type(other).__name__}"
         with pytest.raises(TypeError, match=msg):
             interval_container.overlaps(other)

pandas/tests/arrays/sparse/test_array.py

@@ -1007,7 +1007,7 @@ def test_cumsum(self, data, expected, numpy):
                 np.cumsum(SparseArray(data), out=out)
         else:
             axis = 1  # SparseArray currently 1-D, so only axis = 0 is valid.
-            msg = "axis\\(={axis}\\) out of bounds".format(axis=axis)
+            msg = f"axis\\(={axis}\\) out of bounds"
             with pytest.raises(ValueError, match=msg):
                 SparseArray(data).cumsum(axis=axis)
 

pandas/tests/arrays/sparse/test_libsparse.py

@@ -596,6 +596,6 @@ def _check_case(xloc, xlen, yloc, ylen, eloc, elen):
 
     @pytest.mark.parametrize("opname", ["add", "sub", "mul", "truediv", "floordiv"])
     def test_op(self, opname):
-        sparse_op = getattr(splib, "sparse_{opname}_float64".format(opname=opname))
+        sparse_op = getattr(splib, f"sparse_{opname}_float64")
         python_op = getattr(operator, opname)
         self._op_tests(sparse_op, python_op)

pandas/tests/extension/arrow/arrays.py

@@ -33,7 +33,7 @@ def construct_from_string(cls, string):
         if string == cls.name:
             return cls()
         else:
-            raise TypeError("Cannot construct a '{}' from '{}'".format(cls, string))
+            raise TypeError(f"Cannot construct a '{cls}' from '{string}'")
 
     @classmethod
     def construct_array_type(cls):
@@ -56,7 +56,7 @@ def construct_from_string(cls, string):
         if string == cls.name:
             return cls()
         else:
-            raise TypeError("Cannot construct a '{}' from '{}'".format(cls, string))
+            raise TypeError(f"Cannot construct a '{cls}' from '{string}'")
 
     @classmethod
     def construct_array_type(cls):
@@ -79,7 +79,7 @@ def _from_sequence(cls, scalars, dtype=None, copy=False):
         return cls.from_scalars(scalars)
 
     def __repr__(self):
-        return "{cls}({data})".format(cls=type(self).__name__, data=repr(self._data))
+        return f"{type(self).__name__}({repr(self._data)})"
 
     def __getitem__(self, item):
         if pd.api.types.is_scalar(item):

pandas/tests/extension/base/printing.py

@@ -19,7 +19,7 @@ def test_array_repr(self, data, size):
 
         result = repr(data)
         assert data.__class__.__name__ in result
-        assert "Length: {}".format(len(data)) in result
+        assert f"Length: {len(data)}" in result
         assert str(data.dtype) in result
         if size == "big":
             assert "..." in result

pandas/tests/extension/decimal/array.py

@@ -23,7 +23,7 @@ def __init__(self, context=None):
         self.context = context or decimal.getcontext()
 
     def __repr__(self) -> str:
-        return "DecimalDtype(context={})".format(self.context)
+        return f"DecimalDtype(context={self.context})"
 
     @classmethod
     def construct_array_type(cls):
@@ -40,7 +40,7 @@ def construct_from_string(cls, string):
         if string == cls.name:
             return cls()
         else:
-            raise TypeError("Cannot construct a '{}' from '{}'".format(cls, string))
+            raise TypeError(f"Cannot construct a '{cls}' from '{string}'")
 
     @property
     def _is_numeric(self):
@@ -178,9 +178,7 @@ def _reduce(self, name, skipna=True, **kwargs):
         try:
             op = getattr(self.data, name)
         except AttributeError:
-            raise NotImplementedError(
-                "decimal does not support the {} operation".format(name)
-            )
+            raise NotImplementedError(f"decimal does not support the {name} operation")
         return op(axis=0)
 
 

pandas/tests/resample/test_datetime_index.py

@@ -146,9 +146,7 @@ def test_resample_basic_grouper(series):
 def test_resample_string_kwargs(series, keyword, value):
     # see gh-19303
     # Check that wrong keyword argument strings raise an error
-    msg = "Unsupported value {value} for `{keyword}`".format(
-        value=value, keyword=keyword
-    )
+    msg = f"Unsupported value {value} for `{keyword}`"
     with pytest.raises(ValueError, match=msg):
         series.resample("5min", **({keyword: value}))
 

pandas/tests/resample/test_time_grouper.py

@@ -89,7 +89,7 @@ def test_fails_on_no_datetime_index(name, func):
 
     msg = (
         "Only valid with DatetimeIndex, TimedeltaIndex "
-        "or PeriodIndex, but got an instance of '{}'".format(name)
+        f"or PeriodIndex, but got an instance of '{name}'"
     )
     with pytest.raises(TypeError, match=msg):
         df.groupby(Grouper(freq="D"))

pandas/tests/scalar/test_nat.py

@@ -141,7 +141,7 @@ def test_round_nat(klass, method, freq):
 )
 def test_nat_methods_raise(method):
     # see gh-9513, gh-17329
-    msg = "NaTType does not support {method}".format(method=method)
+    msg = f"NaTType does not support {method}"
 
     with pytest.raises(ValueError, match=msg):
         getattr(NaT, method)()

pandas/tests/tseries/offsets/common.py

@@ -13,18 +13,14 @@ def assert_offset_equal(offset, base, expected):
         assert actual_apply == expected
     except AssertionError:
         raise AssertionError(
-            "\nExpected: {expected}\nActual: {actual}\nFor Offset: {offset})"
-            "\nAt Date: {base}".format(
-                expected=expected, actual=actual, offset=offset, base=base
-            )
+            f"\nExpected: {expected}\nActual: {actual}\nFor Offset: {offset})"
+            f"\nAt Date: {base}"
         )
 
 
 def assert_onOffset(offset, date, expected):
     actual = offset.onOffset(date)
     assert actual == expected, (
-        "\nExpected: {expected}\nActual: {actual}\nFor Offset: {offset})"
-        "\nAt Date: {date}".format(
-            expected=expected, actual=actual, offset=offset, date=date
-        )
+        f"\nExpected: {expected}\nActual: {actual}\nFor Offset: {offset})"
+        f"\nAt Date: {date}"
     )

pandas/tseries/frequencies.py

@@ -243,7 +243,7 @@ def infer_freq(index, warn=True):
         ):
             raise TypeError(
                 "cannot infer freq from a non-convertible dtype "
-                "on a Series of {dtype}".format(dtype=index.dtype)
+                f"on a Series of {index.dtype}"
             )
         index = values
 
@@ -260,8 +260,7 @@ def infer_freq(index, warn=True):
     if isinstance(index, pd.Index) and not isinstance(index, pd.DatetimeIndex):
         if isinstance(index, (pd.Int64Index, pd.Float64Index)):
             raise TypeError(
-                "cannot infer freq from a non-convertible index "
-                "type {type}".format(type=type(index))
+                "cannot infer freq from a non-convertible index " f"type {type(index)}"
             )
         index = index.values
 
@@ -393,15 +392,15 @@ def _infer_daily_rule(self):
         if annual_rule:
             nyears = self.ydiffs[0]
             month = MONTH_ALIASES[self.rep_stamp.month]
-            alias = "{prefix}-{month}".format(prefix=annual_rule, month=month)
+            alias = f"{annual_rule}-{month}"
             return _maybe_add_count(alias, nyears)
 
         quarterly_rule = self._get_quarterly_rule()
         if quarterly_rule:
             nquarters = self.mdiffs[0] / 3
             mod_dict = {0: 12, 2: 11, 1: 10}
             month = MONTH_ALIASES[mod_dict[self.rep_stamp.month % 3]]
-            alias = "{prefix}-{month}".format(prefix=quarterly_rule, month=month)
+            alias = f"{quarterly_rule}-{month}"
             return _maybe_add_count(alias, nquarters)
 
         monthly_rule = self._get_monthly_rule()
@@ -413,7 +412,7 @@ def _infer_daily_rule(self):
             if days % 7 == 0:
                 # Weekly
                 day = int_to_weekday[self.rep_stamp.weekday()]
-                return _maybe_add_count("W-{day}".format(day=day), days / 7)
+                return _maybe_add_count(f"W-{day}", days / 7)
             else:
                 return _maybe_add_count("D", days)
 
@@ -485,7 +484,7 @@ def _get_wom_rule(self):
         week = week_of_months[0] + 1
         wd = int_to_weekday[weekdays[0]]
 
-        return "WOM-{week}{weekday}".format(week=week, weekday=wd)
+        return f"WOM-{week}{wd}"
 
 
 class _TimedeltaFrequencyInferer(_FrequencyInferer):
@@ -495,7 +494,7 @@ def _infer_daily_rule(self):
             if days % 7 == 0:
                 # Weekly
                 wd = int_to_weekday[self.rep_stamp.weekday()]
-                alias = "W-{weekday}".format(weekday=wd)
+                alias = f"W-{wd}"
                 return _maybe_add_count(alias, days / 7)
             else:
                 return _maybe_add_count("D", days)
@@ -509,6 +508,6 @@ def _maybe_add_count(base, count):
     if count != 1:
         assert count == int(count)
         count = int(count)
-        return "{count}{base}".format(count=count, base=base)
+        return f"{count}{base}"
     else:
         return base