CLN changed .format to f-string for test_converter.py, test_datetimel… (#30248)

Author: jlamborn324

pandas/tests/plotting/test_converter.py

@@ -268,7 +268,7 @@ def _assert_less(ts1, ts2):
  val1 = self.dtc.convert(ts1, None, None)
  val2 = self.dtc.convert(ts2, None, None)
  if not val1 < val2:
- raise AssertionError("{0} is not less than {1}.".format(val1, val2))
+ raise AssertionError(f"{val1} is not less than {val2}.")
 
  # Matplotlib's time representation using floats cannot distinguish
  # intervals smaller than ~10 microsecond in the common range of years.

pandas/tests/plotting/test_datetimelike.py

@@ -1352,7 +1352,7 @@ def test_plot_outofbounds_datetime(self):
 
  def test_format_timedelta_ticks_narrow(self):
 
- expected_labels = ["00:00:00.0000000{:0>2d}".format(i) for i in np.arange(10)]
+ expected_labels = [f"00:00:00.0000000{i:0>2d}" for i in np.arange(10)]
 
  rng = timedelta_range("0", periods=10, freq="ns")
  df = DataFrame(np.random.randn(len(rng), 3), rng)

pandas/tests/plotting/test_series.py

@@ -330,7 +330,7 @@ def test_pie_series(self):
  ax = _check_plot_works(
  series.plot.pie, colors=color_args, autopct="%.2f", fontsize=7
  )
- pcts = ["{0:.2f}".format(s * 100) for s in series.values / float(series.sum())]
+ pcts = [f"{s*100:.2f}" for s in series.values / float(series.sum())]
  expected_texts = list(chain.from_iterable(zip(series.index, pcts)))
  self._check_text_labels(ax.texts, expected_texts)
  for t in ax.texts:
@@ -865,15 +865,15 @@ def test_time_series_plot_color_with_empty_kwargs(self):
 
  def test_xticklabels(self):
  # GH11529
- s = Series(np.arange(10), index=["P{i:02d}".format(i=i) for i in range(10)])
+ s = Series(np.arange(10), index=[f"P{i:02d}" for i in range(10)])
  _, ax = self.plt.subplots()
  ax = s.plot(xticks=[0, 3, 5, 9], ax=ax)
- exp = ["P{i:02d}".format(i=i) for i in [0, 3, 5, 9]]
+ exp = [f"P{i:02d}" for i in [0, 3, 5, 9]]
  self._check_text_labels(ax.get_xticklabels(), exp)
 
  def test_xtick_barPlot(self):
  # GH28172
- s = pd.Series(range(10), index=["P{i:02d}".format(i=i) for i in range(10)])
+ s = pd.Series(range(10), index=[f"P{i:02d}" for i in range(10)])
  ax = s.plot.bar(xticks=range(0, 11, 2))
  exp = np.array(list(range(0, 11, 2)))
  tm.assert_numpy_array_equal(exp, ax.get_xticks())