optuna.visualization.plot_parallel_coordinate(study, params=None, *, target=None, target_name='Objective Value')[source]

Plot the high-dimensional parameter relationships in a study.

Note that, if a parameter contains missing values, a trial with missing values is not plotted.


The following code snippet shows how to plot the high-dimensional parameter relationships.

import optuna

def objective(trial):
    x = trial.suggest_float("x", -100, 100)
    y = trial.suggest_categorical("y", [-1, 0, 1])
    return x ** 2 + y

sampler = optuna.samplers.TPESampler(seed=10)
study = optuna.create_study(sampler=sampler)
study.optimize(objective, n_trials=10)

fig = optuna.visualization.plot_parallel_coordinate(study, params=["x", "y"])
  • study (Study) – A Study object whose trials are plotted for their target values.

  • params (list[str] | None) – Parameter list to visualize. The default is all parameters.

  • target (Callable[[FrozenTrial], float] | None) –

    A function to specify the value to display. If it is None and study is being used for single-objective optimization, the objective values are plotted.


    Specify this argument if study is being used for multi-objective optimization.

  • target_name (str) – Target’s name to display on the axis label and the legend.


A plotly.graph_objects.Figure object.

Return type:



The colormap is reversed when the target argument isn’t None or direction of Study is minimize.