Slider in `scatter_3d` and `scatter` makes some data points go missing

Ejecuta el MWE de Python proporcionado en plot_scatter_3d_mwe y compara el comportamiento de los diagramas de dispersión 2D y 3D animados a través de los frames de umbral. Traza cómo se representan animation_frame y animation_group en la figura generada; se considera terminado cuando las cuatro categorías y sus puntos de datos siguen disponibles en cada posición del deslizador.

Only 2 out of 4 categories are plotted when I use a slider. Other data points do not appear at all. When I slide the slider, different categories are plotted. E.g. in the MWE below, only TP and FP show up when the slider is below 0.9. At 0.9 only TN and FN show up.

This behavior also happens for both 2d and 3d scatter plots. See the MWE below for 3d.

import numpy as np
import pandas as pd
import plotly.express as px

def plot_scatter_3d_mwe():
    # Create a small DataFrame with fake data
    data = {
        'Dim1': np.random.rand(10),
        'Dim2': np.random.rand(10),
        'Dim3': np.random.rand(10),
        'due': [1, 0, 1, 0, 1, 0, 1, 0, 1, 0],
        'serial_number': range(10),
        'predicted_probabilities': [0.9, 0.8, 0.4, 0.2, 0.6, 0.7, 0.1, 0.5, 0.3, 0.95]
    }

    df = pd.DataFrame(data)
    thresholds = np.arange(0, 1.1, 0.1)
    all_frames = []

    for threshold in thresholds:
        # Recalculate predictions based on the threshold
        predicted = (df['predicted_probabilities'] >= threshold).astype(int)
        
        # Create the 4 categories for coloring: TP, TN, FP, FN
        conditions = [
            (df['due'] == 1) & (predicted == 1),  # TP
            (df['due'] == 0) & (predicted == 0),  # TN
            (df['due'] == 0) & (predicted == 1),  # FP
            (df['due'] == 1) & (predicted == 0),  # FN
        ]
        categories = ['TP', 'TN', 'FP', 'FN']
        
        # Assign the categories to a new column
        df['category'] = np.select(conditions, categories, default='Unknown')
        df['threshold'] = threshold  # Add threshold as a column for animation frame
        
        all_frames.append(df.copy())

    # Concatenate all frames for animation
    df_all_frames = pd.concat(all_frames)

    # Plot the scatter 3D with the categories as color and animate over thresholds
    fig = px.scatter_3d(df_all_frames,
                        x='Dim1', y='Dim2', z='Dim3',
                        color='category',
                        animation_frame='threshold',
                        animation_group='serial_number')

    fig.show()

# Call the function
plot_scatter_3d_mwe()