Dynamic subplot using Figures in Matplotlib

Here is a basis for the interactive part.

I remove all axes from the figure at each new selection and add the newly selected ones on a relevant GridSpec.

Still axes are not redrawn every time thanks to @lru_cache.

Edit: Added shared x axes

from functools import lru_cache

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.gridspec import GridSpec
from matplotlib.ticker import FuncFormatter, NullFormatter

plt.ion()

NULL_FORMATTER = NullFormatter()
FUNC_FORMATTER = FuncFormatter(lambda x, pos: f"{x:,.0f}")


def main():

    # Emulate data and user selection
    np.random.seed(0)
    datas = generate_data(num_datas=10)
    states = generate_states(list(datas.keys()), num_states=6, max_key_per_state=5)

    fig = plt.figure(figsize=(6, 8))

    @lru_cache
    def get_data_ax(data_id):
        """Create a new ax on fig with corresponding data plotted"""
        # thanks to @lru_cache, axes are not redrawn each time
        print(f"Drawing ax for {data_id}")
        ax = fig.add_subplot()
        ax = plot_data(*datas[data_id], y_label=data_id, ax=ax)
        return ax

    for data_state in states:
        axes = [get_data_ax(data_id) for data_id in data_state]
        update_figure_with_axes(fig, axes)
        plt.pause(1)


def plot_data(x, y, *, y_label, ax=None, marker_sym=None, color_idx=0):
    if ax is None:
        # fig, ax = plt.subplots()  # New figure
        # ax = plt.gca()  # Current axis
        ax = plt.gcf().add_subplot()  # New axis on current figure
    ax.plot(x, y)
    ax.set_ylabel(y_label)
    # Use `marker_sym` and `color_idx`
    return ax


def update_figure_with_axes(fig, axes):
    """Every ax in `axes` should have already been plotted on `fig`"""

    # Remove all previous axes, add relevant ones later
    for ax in fig.axes:
        fig.delaxes(ax)

    # Create a GridSpec for the axes to be plot,
    # with at least 3 rows so plots are not too stretched
    gs = GridSpec(max(3, len(axes)), 1, hspace=0.4)

    # Add each ax one by one
    for ax, sgs in zip(axes, gs):
        ax.set_subplotspec(sgs)  # Place ax at the right location
        ax.xaxis.set_major_formatter(NULL_FORMATTER)  # Remove x ticks labels
        fig.add_subplot(ax)

    # Add back the x ticks labels for the bottom ax
    axes[-1].xaxis.set_major_formatter(FUNC_FORMATTER)

    # Share all axes with the bottom ax
    axes[-1].get_shared_x_axes().join(*axes)
    axes[-1].autoscale()


def generate_data(num_datas):
    """
    Generate `num_datas` random data, with 100 to 200 points,
    starting somewhere in between 100 and 150 on the x axis.
    """
    return {
        f"data{data_idx:02d}": (
            np.arange(
                start := np.random.randint(100, 150),
                start + (num_points := np.random.randint(100, 200)),
            ),  # x
            np.random.randn(num_points),  # y
        )
        for data_idx in range(1, num_datas + 1)
    }


def generate_states(keys, num_states, max_key_per_state):
    """Generate `num_states` draws of `keys`, in between 1 and `max_key_per_state`"""
    return tuple(
        np.random.choice(
            keys,
            replace=False,
            size=np.random.randint(1, max_key_per_state + 1),
        )
        for _ in range(num_states)
    )


if __name__ == "__main__":
    main()