diff --git a/pandas/core/arrays/period.py b/pandas/core/arrays/period.py
index fdf4059fad569..f3d51b28ad399 100644
--- a/pandas/core/arrays/period.py
+++ b/pandas/core/arrays/period.py
@@ -596,7 +596,7 @@ def _format_native_types(self, na_rep="NaT", date_format=None, **kwargs):
         if date_format:
             formatter = lambda dt: dt.strftime(date_format)
         else:
-            formatter = lambda dt: "%s" % dt
+            formatter = lambda dt: str(dt)
 
         if self._hasnans:
             mask = self._isnan
diff --git a/pandas/core/common.py b/pandas/core/common.py
index 133e60de5d694..41b6ebbd2f196 100644
--- a/pandas/core/common.py
+++ b/pandas/core/common.py
@@ -451,7 +451,7 @@ def pipe(obj, func, *args, **kwargs):
     if isinstance(func, tuple):
         func, target = func
         if target in kwargs:
-            msg = "%s is both the pipe target and a keyword argument" % target
+            msg = f"{target} is both the pipe target and a keyword argument"
             raise ValueError(msg)
         kwargs[target] = obj
         return func(*args, **kwargs)
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 442994a04caee..ad970cac92724 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -1805,7 +1805,7 @@ def to_records(
             if isinstance(self.index, ABCMultiIndex):
                 for i, n in enumerate(index_names):
                     if n is None:
-                        index_names[i] = "level_%d" % count
+                        index_names[i] = f"level_{count}"
                         count += 1
             elif index_names[0] is None:
                 index_names = ["index"]
@@ -2454,7 +2454,7 @@ def info(
         exceeds_info_cols = len(self.columns) > max_cols
 
         def _verbose_repr():
-            lines.append("Data columns (total %d columns):" % len(self.columns))
+            lines.append(f"Data columns (total {len(self.columns)} columns):")
             space = max(len(pprint_thing(k)) for k in self.columns) + 4
             counts = None
 
@@ -2846,7 +2846,7 @@ def _getitem_bool_array(self, key):
             )
         elif len(key) != len(self.index):
             raise ValueError(
-                "Item wrong length %d instead of %d." % (len(key), len(self.index))
+                f"Item wrong length {len(key)} instead of {len(self.index)}."
             )
 
         # check_bool_indexer will throw exception if Series key cannot
@@ -2957,7 +2957,7 @@ def _setitem_array(self, key, value):
         if com.is_bool_indexer(key):
             if len(key) != len(self.index):
                 raise ValueError(
-                    "Item wrong length %d instead of %d!" % (len(key), len(self.index))
+                    f"Item wrong length {len(key)} instead of {len(self.index)}!"
                 )
             key = check_bool_indexer(self.index, key)
             indexer = key.nonzero()[0]
@@ -4537,8 +4537,8 @@ def _maybe_casted_values(index, labels=None):
         if not drop:
             if isinstance(self.index, ABCMultiIndex):
                 names = [
-                    n if n is not None else ("level_%d" % i)
-                    for (i, n) in enumerate(self.index.names)
+                    (n if n is not None else f"level_{i}")
+                    for i, n in enumerate(self.index.names)
                 ]
                 to_insert = zip(self.index.levels, self.index.codes)
             else:
@@ -4858,8 +4858,7 @@ def sort_values(
             by = [by]
         if is_sequence(ascending) and len(by) != len(ascending):
             raise ValueError(
-                "Length of ascending (%d) != length of by (%d)"
-                % (len(ascending), len(by))
+                f"Length of ascending ({len(ascending)}) != length of by ({len(by)})"
             )
         if len(by) > 1:
             from pandas.core.sorting import lexsort_indexer
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 17784b623c414..e9964167c7c10 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -421,8 +421,7 @@ def _construct_axes_from_arguments(
                 if a in kwargs:
                     if alias in kwargs:
                         raise TypeError(
-                            "arguments are mutually exclusive "
-                            "for [%s,%s]" % (a, alias)
+                            f"arguments are mutually exclusive for [{a},{alias}]"
                         )
                     continue
                 if alias in kwargs:
@@ -754,7 +753,7 @@ def transpose(self, *args, **kwargs):
 
         # we must have unique axes
         if len(axes) != len(set(axes)):
-            raise ValueError("Must specify %s unique axes" % self._AXIS_LEN)
+            raise ValueError(f"Must specify {self._AXIS_LEN} unique axes")
 
         new_axes = self._construct_axes_dict_from(
             self, [self._get_axis(x) for x in axes_names]
@@ -2096,7 +2095,7 @@ def __repr__(self) -> str:
         # string representation based upon iterating over self
         # (since, by definition, `PandasContainers` are iterable)
         prepr = "[%s]" % ",".join(map(pprint_thing, self))
-        return "%s(%s)" % (self.__class__.__name__, prepr)
+        return f"{self.__class__.__name__}({prepr})"
 
     def _repr_latex_(self):
         """
@@ -6357,7 +6356,7 @@ def fillna(
             elif isinstance(value, ABCDataFrame) and self.ndim == 2:
                 new_data = self.where(self.notna(), value)
             else:
-                raise ValueError("invalid fill value with a %s" % type(value))
+                raise ValueError(f"invalid fill value with a {type(value)}")
 
         if inplace:
             self._update_inplace(new_data)
@@ -6794,9 +6793,8 @@ def replace(
                 if is_list_like(value):
                     if len(to_replace) != len(value):
                         raise ValueError(
-                            "Replacement lists must match "
-                            "in length. Expecting %d got %d "
-                            % (len(to_replace), len(value))
+                            f"Replacement lists must match in length. "
+                            f"Expecting {len(to_replace)} got {len(value)} "
                         )
 
                     new_data = self._data.replace_list(
@@ -8871,7 +8869,7 @@ def align(
                 fill_axis=fill_axis,
             )
         else:  # pragma: no cover
-            raise TypeError("unsupported type: %s" % type(other))
+            raise TypeError(f"unsupported type: {type(other)}")
 
     def _align_frame(
         self,
@@ -9515,9 +9513,9 @@ def tshift(self, periods=1, freq=None, axis=0):
                 new_data = self._data.copy()
                 new_data.axes[block_axis] = index.shift(periods)
             else:
-                msg = "Given freq %s does not match PeriodIndex freq %s" % (
-                    freq.rule_code,
-                    orig_freq.rule_code,
+                msg = (
+                    f"Given freq {freq.rule_code} does not match"
+                    f" PeriodIndex freq {orig_freq.rule_code}"
                 )
                 raise ValueError(msg)
         else:
@@ -9665,7 +9663,7 @@ def truncate(self, before=None, after=None, axis=None, copy=True):
 
         if before is not None and after is not None:
             if before > after:
-                raise ValueError("Truncate: %s must be after %s" % (after, before))
+                raise ValueError(f"Truncate: {after} must be after {before}")
 
         slicer = [slice(None, None)] * self._AXIS_LEN
         slicer[axis] = slice(before, after)
@@ -9711,7 +9709,7 @@ def _tz_convert(ax, tz):
                 if len(ax) > 0:
                     ax_name = self._get_axis_name(axis)
                     raise TypeError(
-                        "%s is not a valid DatetimeIndex or PeriodIndex" % ax_name
+                        f"{ax_name} is not a valid DatetimeIndex or PeriodIndex"
                     )
                 else:
                     ax = DatetimeIndex([], tz=tz)
@@ -9875,7 +9873,7 @@ def _tz_localize(ax, tz, ambiguous, nonexistent):
                 if len(ax) > 0:
                     ax_name = self._get_axis_name(axis)
                     raise TypeError(
-                        "%s is not a valid DatetimeIndex or PeriodIndex" % ax_name
+                        f"{ax_name} is not a valid DatetimeIndex or PeriodIndex"
                     )
                 else:
                     ax = DatetimeIndex([], tz=tz)
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index a8c7100b3846a..88f26a4df65ef 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -963,14 +963,14 @@ def __repr__(self):
         data = self._format_data()
         attrs = self._format_attrs()
         space = self._format_space()
-
-        prepr = (",%s" % space).join("%s=%s" % (k, v) for k, v in attrs)
+        attrs_str = [f"{k}={v}" for k, v in attrs]
+        prepr = f",{space}".join(attrs_str)
 
         # no data provided, just attributes
         if data is None:
             data = ""
 
-        res = "%s(%s%s)" % (klass, data, prepr)
+        res = f"{klass}({data}{prepr})"
 
         return res
 
@@ -1124,13 +1124,13 @@ def _summary(self, name=None):
             tail = self[-1]
             if hasattr(tail, "format") and not isinstance(tail, str):
                 tail = tail.format()
-            index_summary = ", %s to %s" % (pprint_thing(head), pprint_thing(tail))
+            index_summary = f", {head} to {tail}"
         else:
             index_summary = ""
 
         if name is None:
             name = type(self).__name__
-        return "%s: %s entries%s" % (name, len(self), index_summary)
+        return f"{name}: {len(self)} entries{index_summary}"
 
     def summary(self, name=None):
         """
@@ -1304,7 +1304,7 @@ def _set_names(self, values, level=None):
         if not is_list_like(values):
             raise ValueError("Names must be a list-like")
         if len(values) != 1:
-            raise ValueError("Length of new names must be 1, got %d" % len(values))
+            raise ValueError(f"Length of new names must be 1, got {len(values)}")
 
         # GH 20527
         # All items in 'name' need to be hashable:
@@ -1475,8 +1475,8 @@ def _validate_index_level(self, level):
         if isinstance(level, int):
             if level < 0 and level != -1:
                 raise IndexError(
-                    "Too many levels: Index has only 1 level,"
-                    " %d is not a valid level number" % (level,)
+                    f"Too many levels: Index has only 1 level,"
+                    f" {level} is not a valid level number"
                 )
             elif level > 0:
                 raise IndexError(
@@ -4565,7 +4565,7 @@ def shift(self, periods=1, freq=None):
                        '2012-03-01'],
                       dtype='datetime64[ns]', freq='MS')
         """
-        raise NotImplementedError("Not supported for type %s" % type(self).__name__)
+        raise NotImplementedError(f"Not supported for type {type(self).__name__}")
 
     def argsort(self, *args, **kwargs):
         """
@@ -5072,8 +5072,8 @@ def get_slice_bound(self, label, side, kind):
 
         if side not in ("left", "right"):
             raise ValueError(
-                "Invalid value for side kwarg,"
-                " must be either 'left' or 'right': %s" % (side,)
+                f"Invalid value for side kwarg, must be either"
+                f" 'left' or 'right': {side}"
             )
 
         original_label = label
@@ -5627,7 +5627,7 @@ def _trim_front(strings):
 
 def _validate_join_method(method):
     if method not in ["left", "right", "inner", "outer"]:
-        raise ValueError("do not recognize join method %s" % method)
+        raise ValueError(f"do not recognize join method {method}")
 
 
 def default_index(n):
diff --git a/pandas/core/indexes/category.py b/pandas/core/indexes/category.py
index 819f8ac53197a..e0ffc726bc3a1 100644
--- a/pandas/core/indexes/category.py
+++ b/pandas/core/indexes/category.py
@@ -357,7 +357,7 @@ def _format_attrs(self):
         ]
         if self.name is not None:
             attrs.append(("name", ibase.default_pprint(self.name)))
-        attrs.append(("dtype", "'%s'" % self.dtype.name))
+        attrs.append(("dtype", f"'{self.dtype.name}'"))
         max_seq_items = get_option("display.max_seq_items") or len(self)
         if len(self) > max_seq_items:
             attrs.append(("length", len(self)))
diff --git a/pandas/core/indexes/datetimelike.py b/pandas/core/indexes/datetimelike.py
index ceb23f61ae15a..b8670b765ca90 100644
--- a/pandas/core/indexes/datetimelike.py
+++ b/pandas/core/indexes/datetimelike.py
@@ -36,7 +36,6 @@
 from pandas.core.indexes.base import Index, _index_shared_docs
 from pandas.core.tools.timedeltas import to_timedelta
 
-import pandas.io.formats.printing as printing
 from pandas.tseries.frequencies import to_offset
 
 _index_doc_kwargs = dict(ibase._index_doc_kwargs)
@@ -496,7 +495,7 @@ def _format_attrs(self):
             if attrib == "freq":
                 freq = self.freqstr
                 if freq is not None:
-                    freq = "'%s'" % freq
+                    freq = f"{freq!r}"
                 attrs.append(("freq", freq))
         return attrs
 
@@ -686,17 +685,13 @@ def _summary(self, name=None):
         """
         formatter = self._formatter_func
         if len(self) > 0:
-            index_summary = ", %s to %s" % (formatter(self[0]), formatter(self[-1]))
+            index_summary = f", {formatter(self[0])} to {formatter(self[-1])}"
         else:
             index_summary = ""
 
         if name is None:
             name = type(self).__name__
-        result = "%s: %s entries%s" % (
-            printing.pprint_thing(name),
-            len(self),
-            index_summary,
-        )
+        result = f"{name}: {len(self)} entries{index_summary}"
         if self.freq:
             result += "\nFreq: %s" % self.freqstr
 
diff --git a/pandas/core/indexes/datetimes.py b/pandas/core/indexes/datetimes.py
index 41f5eb90d51b0..4a95f0a2ab7e9 100644
--- a/pandas/core/indexes/datetimes.py
+++ b/pandas/core/indexes/datetimes.py
@@ -491,7 +491,7 @@ def _formatter_func(self):
         from pandas.io.formats.format import _get_format_datetime64
 
         formatter = _get_format_datetime64(is_dates_only=self._is_dates_only)
-        return lambda x: "'%s'" % formatter(x, tz=self.tz)
+        return lambda x: f"'{formatter(x, tz=self.tz)}'"
 
     # --------------------------------------------------------------------
     # Set Operation Methods
diff --git a/pandas/core/indexes/frozen.py b/pandas/core/indexes/frozen.py
index 08c86b81b59c0..1b33269d404d6 100644
--- a/pandas/core/indexes/frozen.py
+++ b/pandas/core/indexes/frozen.py
@@ -109,7 +109,7 @@ def __str__(self) -> str:
         return pprint_thing(self, quote_strings=True, escape_chars=("\t", "\r", "\n"))
 
     def __repr__(self) -> str:
-        return "%s(%s)" % (self.__class__.__name__, str(self))
+        return f"{self.__class__.__name__}({str(self)})"
 
     __setitem__ = __setslice__ = __delitem__ = __delslice__ = _disabled
     pop = append = extend = remove = sort = insert = _disabled
@@ -153,7 +153,7 @@ def __repr__(self) -> str:
         Return a string representation for this object.
         """
         prepr = pprint_thing(self, escape_chars=("\t", "\r", "\n"), quote_strings=True)
-        return "%s(%s, dtype='%s')" % (type(self).__name__, prepr, self.dtype)
+        return f"{type(self).__name__}({prepr}, dtype='{self.dtype}')"
 
     @deprecate_kwarg(old_arg_name="v", new_arg_name="value")
     def searchsorted(self, value, side="left", sorter=None):
diff --git a/pandas/core/indexes/multi.py b/pandas/core/indexes/multi.py
index f3a735511c96b..86398613798be 100644
--- a/pandas/core/indexes/multi.py
+++ b/pandas/core/indexes/multi.py
@@ -1329,21 +1329,20 @@ def _get_level_number(self, level) -> int:
         count = self.names.count(level)
         if (count > 1) and not is_integer(level):
             raise ValueError(
-                "The name %s occurs multiple times, use a level number" % level
+                f"The name {level} occurs multiple times, use a level number"
             )
         try:
             level = self.names.index(level)
         except ValueError:
             if not is_integer(level):
-                raise KeyError("Level %s not found" % str(level))
+                raise KeyError(f"Level {level} not found")
             elif level < 0:
                 level += self.nlevels
                 if level < 0:
                     orig_level = level - self.nlevels
                     raise IndexError(
-                        "Too many levels: Index has only %d "
-                        "levels, %d is not a valid level number"
-                        % (self.nlevels, orig_level)
+                        f"Too many levels: Index has only {self.nlevels} levels,"
+                        f" {orig_level} is not a valid level number"
                     )
             # Note: levels are zero-based
             elif level >= self.nlevels:
@@ -2286,8 +2285,8 @@ def reorder_levels(self, order):
         order = [self._get_level_number(i) for i in order]
         if len(order) != self.nlevels:
             raise AssertionError(
-                "Length of order must be same as "
-                "number of levels (%d), got %d" % (self.nlevels, len(order))
+                f"Length of order must be same as number of levels ({self.nlevels}),"
+                f" got {len(order)}"
             )
         new_levels = [self.levels[i] for i in order]
         new_codes = [self.codes[i] for i in order]
@@ -2599,8 +2598,8 @@ def slice_locs(self, start=None, end=None, step=None, kind=None):
     def _partial_tup_index(self, tup, side="left"):
         if len(tup) > self.lexsort_depth:
             raise UnsortedIndexError(
-                "Key length (%d) was greater than MultiIndex"
-                " lexsort depth (%d)" % (len(tup), self.lexsort_depth)
+                f"Key length ({len(tup)}) was greater than MultiIndex lexsort depth"
+                f" ({self.lexsort_depth})"
             )
 
         n = len(tup)
@@ -2611,7 +2610,7 @@ def _partial_tup_index(self, tup, side="left"):
 
             if lab not in lev:
                 if not lev.is_type_compatible(lib.infer_dtype([lab], skipna=False)):
-                    raise TypeError("Level type mismatch: %s" % lab)
+                    raise TypeError(f"Level type mismatch: {lab}")
 
                 # short circuit
                 loc = lev.searchsorted(lab, side=side)
diff --git a/pandas/core/series.py b/pandas/core/series.py
index d771aefb55844..3f69dd53491c1 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -1008,7 +1008,7 @@ def _unpickle_series_compat(self, state):
             self.name = name
 
         else:
-            raise Exception("cannot unpickle legacy formats -> [%s]" % state)
+            raise Exception(f"cannot unpickle legacy formats -> [{state}]")
 
     # indexers
     @property
@@ -1303,7 +1303,7 @@ def _set_labels(self, key, value):
         indexer = self.index.get_indexer(key)
         mask = indexer == -1
         if mask.any():
-            raise ValueError("%s not contained in the index" % str(key[mask]))
+            raise ValueError(f"{key[mask]} not contained in the index")
         self._set_values(indexer, value)
 
     def _set_values(self, key, value):
@@ -2591,7 +2591,7 @@ def dot(self, other):
             rvals = np.asarray(other)
             if lvals.shape[0] != rvals.shape[0]:
                 raise Exception(
-                    "Dot product shape mismatch, %s vs %s" % (lvals.shape, rvals.shape)
+                    f"Dot product shape mismatch, {lvals.shape} vs {rvals.shape}"
                 )
 
         if isinstance(other, ABCDataFrame):
@@ -2603,7 +2603,7 @@ def dot(self, other):
         elif isinstance(rvals, np.ndarray):
             return np.dot(lvals, rvals)
         else:  # pragma: no cover
-            raise TypeError("unsupported type: %s" % type(other))
+            raise TypeError(f"unsupported type: {type(other)}")
 
     def __matmul__(self, other):
         """
@@ -3083,8 +3083,7 @@ def _try_kind_sort(arr):
         if is_list_like(ascending):
             if len(ascending) != 1:
                 raise ValueError(
-                    "Length of ascending (%d) must be 1 "
-                    "for Series" % (len(ascending))
+                    f"Length of ascending ({len(ascending)}) must be 1 for Series"
                 )
             ascending = ascending[0]
 
diff --git a/pandas/core/util/hashing.py b/pandas/core/util/hashing.py
index 23c370638b572..fa3582755a202 100644
--- a/pandas/core/util/hashing.py
+++ b/pandas/core/util/hashing.py
@@ -133,7 +133,7 @@ def hash_pandas_object(
 
         h = Series(h, index=obj.index, dtype="uint64", copy=False)
     else:
-        raise TypeError("Unexpected type for hashing %s" % type(obj))
+        raise TypeError(f"Unexpected type for hashing {type(obj)}")
     return h
 
 
diff --git a/pandas/io/clipboard/__init__.py b/pandas/io/clipboard/__init__.py
index 40452b41998df..4f690a57893d1 100644
--- a/pandas/io/clipboard/__init__.py
+++ b/pandas/io/clipboard/__init__.py
@@ -87,7 +87,7 @@ class PyperclipException(RuntimeError):
 
 class PyperclipWindowsException(PyperclipException):
     def __init__(self, message):
-        message += " (%s)" % ctypes.WinError()
+        message += f" ({ctypes.WinError()})"
         super().__init__(message)
 
 
@@ -599,9 +599,9 @@ def set_clipboard(clipboard):
     }
 
     if clipboard not in clipboard_types:
+        allowed_clipboard_types = [repr(_) for _ in clipboard_types.keys()]
         raise ValueError(
-            "Argument must be one of %s"
-            % (", ".join([repr(_) for _ in clipboard_types.keys()]))
+            f"Argument must be one of {', '.join(allowed_clipboard_types)}"
         )
 
     # Sets pyperclip's copy() and paste() functions:
diff --git a/pandas/io/sas/sas_xport.py b/pandas/io/sas/sas_xport.py
index 2f2dbdbc76215..9aa8ed1dfeb5d 100644
--- a/pandas/io/sas/sas_xport.py
+++ b/pandas/io/sas/sas_xport.py
@@ -482,7 +482,7 @@ def read(self, nrows=None):
 
         df = pd.DataFrame(index=range(read_lines))
         for j, x in enumerate(self.columns):
-            vec = data["s%d" % j]
+            vec = data["s" + str(j)]
             ntype = self.fields[j]["ntype"]
             if ntype == "numeric":
                 vec = _handle_truncated_float_vec(vec, self.fields[j]["field_length"])
diff --git a/pandas/io/stata.py b/pandas/io/stata.py
index d51c9170c488b..d4d378573b54e 100644
--- a/pandas/io/stata.py
+++ b/pandas/io/stata.py
@@ -2640,7 +2640,7 @@ def _dtype_to_stata_type_117(dtype, column, force_strl):
     elif dtype == np.int8:
         return 65530
     else:  # pragma : no cover
-        raise NotImplementedError("Data type %s not supported." % dtype)
+        raise NotImplementedError(f"Data type {dtype} not supported.")
 
 
 def _pad_bytes_new(name, length):
diff --git a/pandas/plotting/_matplotlib/converter.py b/pandas/plotting/_matplotlib/converter.py
index 946ce8bcec97f..4b0ba2bd423df 100644
--- a/pandas/plotting/_matplotlib/converter.py
+++ b/pandas/plotting/_matplotlib/converter.py
@@ -429,7 +429,8 @@ def __call__(self):
                 ).format(estimate=estimate, dmin=dmin, dmax=dmax, arg=self.MAXTICKS * 2)
             )
 
-        freq = "%dL" % self._get_interval()
+        interval = self._get_interval()
+        freq = f"{interval}L"
         tz = self.tz.tzname(None)
         st = _from_ordinal(dates.date2num(dmin))  # strip tz
         ed = _from_ordinal(dates.date2num(dmax))
diff --git a/pandas/tests/frame/test_query_eval.py b/pandas/tests/frame/test_query_eval.py
index 04d27f4c12c59..cd1bee356ed8e 100644
--- a/pandas/tests/frame/test_query_eval.py
+++ b/pandas/tests/frame/test_query_eval.py
@@ -991,7 +991,7 @@ def test_query_lex_compare_strings(self, parser, engine):
         ops = {"<": operator.lt, ">": operator.gt, "<=": operator.le, ">=": operator.ge}
 
         for op, func in ops.items():
-            res = df.query('X %s "d"' % op, engine=engine, parser=parser)
+            res = df.query(f'X {op} "d"', engine=engine, parser=parser)
             expected = df[func(df.X, "d")]
             tm.assert_frame_equal(res, expected)
 
diff --git a/pandas/tests/internals/test_internals.py b/pandas/tests/internals/test_internals.py
index fa7a98c617677..dbd84f15d143c 100644
--- a/pandas/tests/internals/test_internals.py
+++ b/pandas/tests/internals/test_internals.py
@@ -134,7 +134,7 @@ def create_block(typestr, placement, item_shape=None, num_offset=0):
         arr = values.sp_values.view()
         arr += num_offset - 1
     else:
-        raise ValueError('Unsupported typestr: "%s"' % typestr)
+        raise ValueError(f'Unsupported typestr: "{typestr}"')
 
     return make_block(values, placement=placement, ndim=len(shape))
 
diff --git a/pandas/tests/io/formats/test_style.py b/pandas/tests/io/formats/test_style.py
index e5af74bdd4d33..61a3934187bd3 100644
--- a/pandas/tests/io/formats/test_style.py
+++ b/pandas/tests/io/formats/test_style.py
@@ -390,7 +390,7 @@ def test_applymap_subset_multiindex_code(self):
 
         def color_negative_red(val):
             color = "red" if val < 0 else "black"
-            return "color: %s" % color
+            return f"color: {color}"
 
         df.loc[pct_subset]
         df.style.applymap(color_negative_red, subset=pct_subset)
diff --git a/pandas/tests/util/test_validate_kwargs.py b/pandas/tests/util/test_validate_kwargs.py
index ec9f3948403de..b6241def4e5d6 100644
--- a/pandas/tests/util/test_validate_kwargs.py
+++ b/pandas/tests/util/test_validate_kwargs.py
@@ -60,9 +60,9 @@ def test_validation():
 @pytest.mark.parametrize("name", ["inplace", "copy"])
 @pytest.mark.parametrize("value", [1, "True", [1, 2, 3], 5.0])
 def test_validate_bool_kwarg_fail(name, value):
-    msg = 'For argument "%s" expected type bool, received type %s' % (
-        name,
-        type(value).__name__,
+    msg = (
+        f'For argument "{name}" expected type bool,'
+        f" received type {type(value).__name__}"
     )
 
     with pytest.raises(ValueError, match=msg):
diff --git a/pandas/util/_test_decorators.py b/pandas/util/_test_decorators.py
index b516c3d78a11e..b9c165140aaad 100644
--- a/pandas/util/_test_decorators.py
+++ b/pandas/util/_test_decorators.py
@@ -199,7 +199,7 @@ def skip_if_no(package: str, min_version: Optional[str] = None) -> Callable:
 
 def skip_if_np_lt(ver_str, reason=None, *args, **kwds):
     if reason is None:
-        reason = "NumPy %s or greater required" % ver_str
+        reason = f"NumPy {ver_str} or greater required"
     return pytest.mark.skipif(
         _np_version < LooseVersion(ver_str), reason=reason, *args, **kwds
     )