[Python] graph_objects.Surface axis tic spacing inconsistent on x and y

Given hemi.csv data of:

244,1000,1500,2000,2500,3000,3500,5000
0,14,18,-42,-72,-84,-86,-94,-119
12.5,277,231,185,139,144,150,161,158
25.1,416,394,370,348,361,374,404,396
37.6,483,587,633,653,566,585,633,621
49.8,504,612,733,756,668,691,748,734
62.4,504,612,733,756,786,749,809,794
74.9,504,612,733,756,786,814,854,838
100,504,612,733,756,786,814,880,864


I have plotly code of:

import pandas as pd
import plotly.graph_objects as go

# Open DataFrame
df = pd.read_csv('hemi.csv', header=0, index_col=0)
# Extracting data for the surface plot
x_data = df.columns.tolist()
y_data = df.index.tolist()
z_data = df.values

# Creating the surface plot
fig = go.Figure(data=[go.Surface(z=z_data, x=x_data, y=y_data)])

# Updating layout for axis titles and tick labels
fig.update_layout(
scene = dict(
xaxis = dict(title = 'RPM',
tickmode = 'array',
tickvals = x_data,
ticktext = df.columns),
yaxis = dict(title = 'TPS',
tickmode = 'array',
tickvals = y_data,
ticktext = df.index),
zaxis = dict(title = 'torque Nm')
)
)

fig.show()


I get yaxis 'TPS' spaced as expected with tic spacing of the index values. However the xaxis 'RPM' tic spacing is uniform, ie not proportional to the columns values as desired. Ie, 3500,5000 is the same width as 3000,3500.



In MPL plot_trisurf the tics appear to be uniform, and the plot locations are scaled:

import matplotlib.pyplot as plt
from matplotlib import cm
import pandas as pd
# Get the data (csv file is hosted on the web)
data = pd.read_csv('413.csv', header=0, index_col=0)

# Transform it to a long format
df=data.unstack().reset_index()
df.columns=["X","Y","Z"]

fig = plt.figure()
ax = fig.add_subplot(projection='3d')
ax.plot_trisurf(df['Y'],
df['X'],
df['Z'],
cmap=cm.jet,
linewidth=0.2)
plt.show()




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