CLN - Change string formatting in plotting (#29781)

Author: ohad83

pandas/plotting/_core.py

@@ -736,26 +736,23 @@ def _get_call_args(backend_name, data, args, kwargs):
             ]
         else:
             raise TypeError(
-                (
-                    "Called plot accessor for type {}, expected Series or DataFrame"
-                ).format(type(data).__name__)
+                f"Called plot accessor for type {type(data).__name__}, "
+                "expected Series or DataFrame"
             )
 
         if args and isinstance(data, ABCSeries):
+            positional_args = str(args)[1:-1]
+            keyword_args = ", ".join(
+                f"{name}={value!r}" for (name, default), value in zip(arg_def, args)
+            )
             msg = (
                 "`Series.plot()` should not be called with positional "
                 "arguments, only keyword arguments. The order of "
                 "positional arguments will change in the future. "
-                "Use `Series.plot({})` instead of `Series.plot({})`."
-            )
-            positional_args = str(args)[1:-1]
-            keyword_args = ", ".join(
-                "{}={!r}".format(name, value)
-                for (name, default), value in zip(arg_def, args)
-            )
-            warnings.warn(
-                msg.format(keyword_args, positional_args), FutureWarning, stacklevel=3
+                f"Use `Series.plot({keyword_args})` instead of "
+                f"`Series.plot({positional_args})`."
             )
+            warnings.warn(msg, FutureWarning, stacklevel=3)
 
         pos_args = {name: value for value, (name, _) in zip(args, arg_def)}
         if backend_name == "pandas.plotting._matplotlib":
@@ -782,7 +779,7 @@ def __call__(self, *args, **kwargs):
             return plot_backend.plot(self._parent, x=x, y=y, kind=kind, **kwargs)
 
         if kind not in self._all_kinds:
-            raise ValueError("{} is not a valid plot kind".format(kind))
+            raise ValueError(f"{kind} is not a valid plot kind")
 
         # The original data structured can be transformed before passed to the
         # backend. For example, for DataFrame is common to set the index as the
@@ -796,14 +793,13 @@ def __call__(self, *args, **kwargs):
             if isinstance(data, ABCDataFrame):
                 return plot_backend.plot(data, x=x, y=y, kind=kind, **kwargs)
             else:
-                raise ValueError(
-                    ("plot kind {} can only be used for data frames").format(kind)
-                )
+                raise ValueError(f"plot kind {kind} can only be used for data frames")
         elif kind in self._series_kinds:
             if isinstance(data, ABCDataFrame):
                 if y is None and kwargs.get("subplots") is False:
-                    msg = "{} requires either y column or 'subplots=True'"
-                    raise ValueError(msg.format(kind))
+                    raise ValueError(
+                        f"{kind} requires either y column or 'subplots=True'"
+                    )
                 elif y is not None:
                     if is_integer(y) and not data.columns.holds_integer():
                         y = data.columns[y]
@@ -1639,12 +1635,11 @@ def _find_backend(backend: str):
                 _backends[backend] = module
                 return module
 
-    msg = (
-        "Could not find plotting backend '{name}'. Ensure that you've installed the "
-        "package providing the '{name}' entrypoint, or that the package has a"
+    raise ValueError(
+        f"Could not find plotting backend '{backend}'. Ensure that you've installed "
+        f"the package providing the '{backend}' entrypoint, or that the package has a "
         "top-level `.plot` method."
     )
-    raise ValueError(msg.format(name=backend))
 
 
 def _get_plot_backend(backend=None):

pandas/plotting/_matplotlib/boxplot.py

@@ -74,9 +74,8 @@ def _validate_color_args(self):
                 for key, values in self.color.items():
                     if key not in valid_keys:
                         raise ValueError(
-                            "color dict contains invalid "
-                            "key '{0}' "
-                            "The key must be either {1}".format(key, valid_keys)
+                            f"color dict contains invalid key '{key}'. "
+                            f"The key must be either {valid_keys}"
                         )
         else:
             self.color = None
@@ -217,7 +216,7 @@ def _grouped_plot_by_column(
         result = axes
 
     byline = by[0] if len(by) == 1 else by
-    fig.suptitle("Boxplot grouped by {byline}".format(byline=byline))
+    fig.suptitle(f"Boxplot grouped by {byline}")
     fig.subplots_adjust(bottom=0.15, top=0.9, left=0.1, right=0.9, wspace=0.2)
 
     return result
@@ -268,9 +267,8 @@ def _get_colors():
                         result[key_to_index[key]] = value
                     else:
                         raise ValueError(
-                            "color dict contains invalid "
-                            "key '{0}' "
-                            "The key must be either {1}".format(key, valid_keys)
+                            f"color dict contains invalid key '{key}'. "
+                            f"The key must be either {valid_keys}"
                         )
             else:
                 result.fill(colors)

pandas/plotting/_matplotlib/converter.py

@@ -125,7 +125,7 @@ def time2num(d):
     if isinstance(d, str):
         parsed = tools.to_datetime(d)
         if not isinstance(parsed, datetime):
-            raise ValueError("Could not parse time {d}".format(d=d))
+            raise ValueError(f"Could not parse time {d}")
         return _to_ordinalf(parsed.time())
     if isinstance(d, pydt.time):
         return _to_ordinalf(d)
@@ -244,7 +244,7 @@ def get_datevalue(date, freq):
         return date
     elif date is None:
         return None
-    raise ValueError("Unrecognizable date '{date}'".format(date=date))
+    raise ValueError(f"Unrecognizable date '{date}'")
 
 
 def _dt_to_float_ordinal(dt):
@@ -421,12 +421,10 @@ def __call__(self):
 
         if estimate > self.MAXTICKS * 2:
             raise RuntimeError(
-                (
-                    "MillisecondLocator estimated to generate "
-                    "{estimate:d} ticks from {dmin} to {dmax}: "
-                    "exceeds Locator.MAXTICKS"
-                    "* 2 ({arg:d}) "
-                ).format(estimate=estimate, dmin=dmin, dmax=dmax, arg=self.MAXTICKS * 2)
+                "MillisecondLocator estimated to generate "
+                f"{estimate:d} ticks from {dmin} to {dmax}: "
+                "exceeds Locator.MAXTICKS"
+                f"* 2 ({self.MAXTICKS * 2:d}) "
             )
 
         interval = self._get_interval()
@@ -582,7 +580,7 @@ def _daily_finder(vmin, vmax, freq):
         elif freq == FreqGroup.FR_HR:
             periodsperday = 24
         else:  # pragma: no cover
-            raise ValueError("unexpected frequency: {freq}".format(freq=freq))
+            raise ValueError(f"unexpected frequency: {freq}")
         periodsperyear = 365 * periodsperday
         periodspermonth = 28 * periodsperday
 
@@ -941,8 +939,7 @@ def get_finder(freq):
     elif (freq >= FreqGroup.FR_BUS) or fgroup == FreqGroup.FR_WK:
         return _daily_finder
     else:  # pragma: no cover
-        errmsg = "Unsupported frequency: {freq}".format(freq=freq)
-        raise NotImplementedError(errmsg)
+        raise NotImplementedError(f"Unsupported frequency: {freq}")
 
 
 class TimeSeries_DateLocator(Locator):
@@ -1119,11 +1116,11 @@ def format_timedelta_ticks(x, pos, n_decimals):
         h, m = divmod(m, 60)
         d, h = divmod(h, 24)
         decimals = int(ns * 10 ** (n_decimals - 9))
-        s = r"{:02d}:{:02d}:{:02d}".format(int(h), int(m), int(s))
+        s = f"{int(h):02d}:{int(m):02d}:{int(s):02d}"
         if n_decimals > 0:
-            s += ".{{:0{:0d}d}}".format(n_decimals).format(decimals)
+            s += f".{decimals:0{n_decimals}d}"
         if d != 0:
-            s = "{:d} days ".format(int(d)) + s
+            s = f"{int(d):d} days {s}"
         return s
 
     def __call__(self, x, pos=0):

pandas/plotting/_matplotlib/core.py

@@ -349,8 +349,7 @@ def _setup_subplots(self):
         if input_log - valid_log:
             invalid_log = next(iter((input_log - valid_log)))
             raise ValueError(
-                "Boolean, None and 'sym' are valid options,"
-                " '{}' is given.".format(invalid_log)
+                f"Boolean, None and 'sym' are valid options, '{invalid_log}' is given."
             )
 
         if self.logx is True or self.loglog is True:
@@ -501,14 +500,13 @@ def _adorn_subplots(self):
             if self.subplots:
                 if is_list_like(self.title):
                     if len(self.title) != self.nseries:
-                        msg = (
+                        raise ValueError(
                             "The length of `title` must equal the number "
                             "of columns if using `title` of type `list` "
                             "and `subplots=True`.\n"
-                            "length of title = {}\n"
-                            "number of columns = {}"
-                        ).format(len(self.title), self.nseries)
-                        raise ValueError(msg)
+                            f"length of title = {len(self.title)}\n"
+                            f"number of columns = {self.nseries}"
+                        )
 
                     for (ax, title) in zip(self.axes, self.title):
                         ax.set_title(title)
@@ -813,11 +811,10 @@ def match_labels(data, e):
                     or (err_shape[1] != 2)
                     or (err_shape[2] != len(self.data))
                 ):
-                    msg = (
+                    raise ValueError(
                         "Asymmetrical error bars should be provided "
-                        + "with the shape (%u, 2, %u)" % (self.nseries, len(self.data))
+                        f"with the shape ({self.nseries}, 2, {len(self.data)})"
                     )
-                    raise ValueError(msg)
 
             # broadcast errors to each data series
             if len(err) == 1:
@@ -827,7 +824,7 @@ def match_labels(data, e):
             err = np.tile([err], (self.nseries, len(self.data)))
 
         else:
-            msg = "No valid {label} detected".format(label=label)
+            msg = f"No valid {label} detected"
             raise ValueError(msg)
 
         return err
@@ -1178,7 +1175,7 @@ def _get_stacked_values(cls, ax, stacking_id, values, label):
         raise ValueError(
             "When stacked is True, each column must be either "
             "all positive or negative."
-            "{0} contains both positive and negative values".format(label)
+            f"{label} contains both positive and negative values"
         )
 
     @classmethod
@@ -1473,7 +1470,7 @@ class PiePlot(MPLPlot):
     def __init__(self, data, kind=None, **kwargs):
         data = data.fillna(value=0)
         if (data < 0).any().any():
-            raise ValueError("{0} doesn't allow negative values".format(kind))
+            raise ValueError(f"{kind} doesn't allow negative values")
         MPLPlot.__init__(self, data, kind=kind, **kwargs)
 
     def _args_adjust(self):

pandas/plotting/_matplotlib/misc.py

@@ -395,7 +395,7 @@ def lag_plot(series, lag=1, ax=None, **kwds):
     if ax is None:
         ax = plt.gca()
     ax.set_xlabel("y(t)")
-    ax.set_ylabel("y(t + {lag})".format(lag=lag))
+    ax.set_ylabel(f"y(t + {lag})")
     ax.scatter(y1, y2, **kwds)
     return ax
 

pandas/plotting/_matplotlib/style.py

@@ -20,7 +20,7 @@ def _get_standard_colors(
             cmap = colormap
             colormap = cm.get_cmap(colormap)
             if colormap is None:
-                raise ValueError("Colormap {0} is not recognized".format(cmap))
+                raise ValueError(f"Colormap {cmap} is not recognized")
         colors = [colormap(num) for num in np.linspace(0, 1, num=num_colors)]
     elif color is not None:
         if colormap is not None:

pandas/plotting/_matplotlib/timeseries.py

@@ -307,7 +307,8 @@ def _maybe_convert_index(ax, data):
 
 
 def _format_coord(freq, t, y):
-    return "t = {0}  y = {1:8f}".format(Period(ordinal=int(t), freq=freq), y)
+    time_period = Period(ordinal=int(t), freq=freq)
+    return f"t = {time_period}  y = {y:8f}"
 
 
 def format_dateaxis(subplot, freq, index):

pandas/plotting/_matplotlib/tools.py

@@ -60,10 +60,7 @@ def _get_layout(nplots, layout=None, layout_type="box"):
 
         if nrows * ncols < nplots:
             raise ValueError(
-                "Layout of {nrows}x{ncols} must be larger "
-                "than required size {nplots}".format(
-                    nrows=nrows, ncols=ncols, nplots=nplots
-                )
+                f"Layout of {nrows}x{ncols} must be larger than required size {nplots}"
             )
 
         return layout
@@ -203,8 +200,8 @@ def _subplots(
                 return fig, ax
             else:
                 raise ValueError(
-                    "The number of passed axes must be {0}, the "
-                    "same as the output plot".format(naxes)
+                    f"The number of passed axes must be {naxes}, the "
+                    "same as the output plot"
                 )
 
         fig = ax.get_figure()

pandas/plotting/_misc.py

@@ -446,9 +446,7 @@ def __init__(self, deprecated=False):
     def __getitem__(self, key):
         key = self._get_canonical_key(key)
         if key not in self:
-            raise ValueError(
-                "{key} is not a valid pandas plotting option".format(key=key)
-            )
+            raise ValueError(f"{key} is not a valid pandas plotting option")
         return super().__getitem__(key)
 
     def __setitem__(self, key, value):
@@ -458,7 +456,7 @@ def __setitem__(self, key, value):
     def __delitem__(self, key):
         key = self._get_canonical_key(key)
         if key in self._DEFAULT_KEYS:
-            raise ValueError("Cannot remove default parameter {key}".format(key=key))
+            raise ValueError(f"Cannot remove default parameter {key}")
         return super().__delitem__(key)
 
     def __contains__(self, key):