Python visual on the Service doesn't render as in PBI Desktop

I'm trying to post a 3D scatter plot on the Service but I am getting the error. If I remove the ax formatting I get it, but it's not what I expect.

Does anyone know any alternative?

Below is the error message, a screenshot of how it beautifully looks on Desktop and what I could get on the Service.

To replicate it I am providing the M code to generate the data and the Python viz (ax formatting lines commented with #).

Script Runtime Error

fig.add_axes(ax)

[S-ecccd5b8-55de-460e-b32a-be84188e4e5c]NotImplementedError: It is not currently possible to manually set the aspect on 3D axes

Please try again later or contact support. If you contact support, please provide these details.

On Desktop On Service, removing the ax formatting

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("lZTBasMwDIZfJXiXFEqQbSm1r2kvg1IGG3Rb6KHQwQppC2XvT52uW5eAZ/8Ho0T580myZbWtWuy3h6J8XE3UVK33u6/Pn5enbns8fuyK9UtRLpvn3vUa1ltY72HNT93pXGm1mbZKKDi8rmbByIxcML2HKro9PRD5pnZ3sZPrNzHeBsMykrvGEVFMLoTJMfpdLFm5QHJNoB7kG5BvQL5N8odtMN76//vAgtkwWC2DfAH5kuTXXElfqDf8e7o3xlXva27i+u/TBfQg34J8m+QPu0GPL+64HYZ4BtNhsFwB+QLy/zZIVjqYXhP6AxrBoBFMOkJ8vmVcGIsmZNGSGY3AaARJR4jP9IwhZFJbGp/oOXKMzjH65gI=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Column1 = _t, Column2 = _t, Column3 = _t, Column4 = _t, Column5 = _t, Column6 = _t, Column7 = _t]),
    #"Promoted Headers" = Table.PromoteHeaders(Source, [PromoteAllScalars=true]),
    #"Changed Type" = Table.TransformColumnTypes(#"Promoted Headers",{{"Z", type number}, {"Y", type number}, {"X", type number}, {"Planned WT (LBS)", type number}, {"Width (IN)", type number}, {"Diam (IN)", type number}})
in
    #"Changed Type"

# The following code to create a dataframe and remove duplicated rows is always executed and acts as a preamble for your script: 

# dataset = pandas.DataFrame(Diam (IN), X, Y, Z, Width (IN), Railcar)
# dataset = dataset.drop_duplicates()

# Paste or type your script code here:

df = dataset

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.path import Path
import numpy as np

def plot_cylinder(x, y, z, r, h, cylinder_color):

    if y == 0:
        y = r
    elif y > 0:
        y = y + r + 5

    
    def data_for_cylinder_along_z(center_x,center_y,radius,height_z):
        z = np.linspace(0, height_z, 50)
        theta = np.linspace(0, 2*np.pi, 50)
        theta_grid, z_grid=np.meshgrid(theta, z + h)
        x_grid = radius*np.cos(theta_grid) + center_x
        y_grid = radius*np.sin(theta_grid) + center_y
        return x_grid,y_grid,z_grid
    
    Xc,Yc,Zc = data_for_cylinder_along_z(x+r, y, r, z)
    ax.plot_surface(Xc,Yc,Zc, 
                    alpha=0.95,
                    color= cylinder_color,
                    #cmap='Set1',
                    rstride=3, 
                    cstride=3
                   )


fig = plt.figure(figsize=(7,4))
ax = Axes3D(fig)
fig.add_axes(ax)

#ax.set_xlim3d(0, 600)
#ax.set_ylim3d(0, 108)
#ax.set_zlim3d(0, 154)

#ax.set_zticks(np.arange(0, 154, step=10))
#ax.zaxis.set_tick_params(labelsize=5)

#ax.set_yticks(np.arange(0, 108, step=25))
#ax.yaxis.set_tick_params(labelsize=5)

#ax.set_xticks(np.arange(0, 600, step=25))
#ax.xaxis.set_tick_params(labelsize=5)

#ax.set_aspect('equal', adjustable='box')

for i, row in df.iterrows():
    
    plot_cylinder(
        int(row['X']), 
        int(row['Z']),
        int(row['Width (IN)']),
        int(row['Diam (IN)']) / 2,
        int(row['Y']),
        row['Color.1']
    )

ax.view_init(30, -40)

plt.show()