import numpy as np
import matplotlib.pyplot as plt
from sklearn.datasets import make_classification
from sklearn.model_selection import ValidationCurveDisplay, validation_curve
from sklearn.linear_model import LogisticRegression

X, y = make_classification(n_samples=1_000, random_state=0)
logistic_regression = LogisticRegression()

# put categorical values in param space
param_name, param_range = "class_weight", [{0:0.9, 1:1.1}, 'balanced']
train_scores, test_scores = validation_curve(
     logistic_regression, X, y, param_name=param_name, param_range=param_range
 )
display = ValidationCurveDisplay(
     param_name=param_name, param_range=param_range,
     train_scores=train_scores, test_scores=test_scores, score_name="Score"
 )
display.plot()
plt.show()

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In [1], line 19
     12 train_scores, test_scores = validation_curve(
     13      logistic_regression, X, y, param_name=param_name, param_range=param_range
     14  )
     15 display = ValidationCurveDisplay(
     16      param_name=param_name, param_range=param_range,
     17      train_scores=train_scores, test_scores=test_scores, score_name="Score"
     18  )
---> 19 display.plot()
     20 plt.show()

File ~/work/miniconda/envs/GC_overhaul_nb/lib/python3.10/site-packages/sklearn/model_selection/_plot.py:691, in ValidationCurveDisplay.plot(self, ax, negate_score, score_name, score_type, std_display_style, line_kw, fill_between_kw, errorbar_kw)
    630 def plot(
    631     self,
    632     ax=None,
   (...)
    640     errorbar_kw=None,
    641 ):
    642     """Plot visualization.
    643 
    644     Parameters
   (...)
    689         Object that stores computed values.
    690     """
--> 691     self._plot_curve(
    692         self.param_range,
    693         ax=ax,
    694         negate_score=negate_score,
    695         score_name=score_name,
    696         score_type=score_type,
    697         log_scale="deprecated",
    698         std_display_style=std_display_style,
    699         line_kw=line_kw,
    700         fill_between_kw=fill_between_kw,
    701         errorbar_kw=errorbar_kw,
    702     )
    703     self.ax_.set_xlabel(f"{self.param_name}")
    704     return self

File ~/work/miniconda/envs/GC_overhaul_nb/lib/python3.10/site-packages/sklearn/model_selection/_plot.py:64, in _BaseCurveDisplay._plot_curve(self, x_data, ax, negate_score, score_name, score_type, log_scale, std_display_style, line_kw, fill_between_kw, errorbar_kw)
     61 self.lines_ = []
     62 for line_label, score in scores.items():
     63     self.lines_.append(
---> 64         *ax.plot(
     65             x_data,
     66             score.mean(axis=1),
     67             label=line_label,
     68             **line_kw,
     69         )
     70     )
     71 self.errorbar_ = None
     72 self.fill_between_ = None  # overwritten below by fill_between

File ~/work/miniconda/envs/GC_overhaul_nb/lib/python3.10/site-packages/matplotlib/axes/_axes.py:1723, in Axes.plot(self, scalex, scaley, data, *args, **kwargs)
   1721 lines = [*self._get_lines(self, *args, data=data, **kwargs)]
   1722 for line in lines:
-> 1723     self.add_line(line)
   1724 if scalex:
   1725     self._request_autoscale_view("x")

File ~/work/miniconda/envs/GC_overhaul_nb/lib/python3.10/site-packages/matplotlib/axes/_base.py:2309, in _AxesBase.add_line(self, line)
   2306 if line.get_clip_path() is None:
   2307     line.set_clip_path(self.patch)
-> 2309 self._update_line_limits(line)
   2310 if not line.get_label():
   2311     line.set_label(f'_child{len(self._children)}')

File ~/work/miniconda/envs/GC_overhaul_nb/lib/python3.10/site-packages/matplotlib/axes/_base.py:2332, in _AxesBase._update_line_limits(self, line)
   2328 def _update_line_limits(self, line):
   2329     """
   2330     Figures out the data limit of the given line, updating self.dataLim.
   2331     """
-> 2332     path = line.get_path()
   2333     if path.vertices.size == 0:
   2334         return

File ~/work/miniconda/envs/GC_overhaul_nb/lib/python3.10/site-packages/matplotlib/lines.py:1032, in Line2D.get_path(self)
   1030 """Return the `~matplotlib.path.Path` associated with this line."""
   1031 if self._invalidy or self._invalidx:
-> 1032     self.recache()
   1033 return self._path

File ~/work/miniconda/envs/GC_overhaul_nb/lib/python3.10/site-packages/matplotlib/lines.py:669, in Line2D.recache(self, always)
    667 if always or self._invalidx:
    668     xconv = self.convert_xunits(self._xorig)
--> 669     x = _to_unmasked_float_array(xconv).ravel()
    670 else:
    671     x = self._x

File ~/work/miniconda/envs/GC_overhaul_nb/lib/python3.10/site-packages/matplotlib/cbook/__init__.py:1369, in _to_unmasked_float_array(x)
   1367     return np.ma.asarray(x, float).filled(np.nan)
   1368 else:
-> 1369     return np.asarray(x, float)

TypeError: float() argument must be a string or a real number, not 'dict'