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):