3D Plot:: How to set legend and colorbar orientation and position?

If I remember correctly you can use update_traces to set the colorbar properties. Something like:

fig.update_traces(
    colorbar_orientation='h',
    colorbar_y=0
)

You might need to play around with the position itself to not get any overlaps.

You're talking about two different things here: legend and colorbar, where the former is an attribute of the figure layout, and the latter is an attribute of the figure data or traces. To obtain what you're aiming for here, just include this:

fig.update_layout(legend = dict(orientation="h", x = -0.25, y = -0.10))
fig.update_traces(colorbar = dict(orientation='h', y = -0.25, x = 0.5))

Plot 1

That is, if you'd like to keep the "small" legend at all. If not, just use:

fig.update_layout(showlegend = False)

Plot 2

Complete code:

import numpy as np
import plotly.graph_objects as go 
from scipy.interpolate import griddata
import plotly.io as pio

import pandas as pd

df = pd.DataFrame({'hidden_layer_sizes': {0: 25,
  1: 25,  2: 25,  3: 25,  4: 25,  5: 50,  6: 50,  7: 50,  8: 50,  9: 50,  10: 75,
  11: 75,  12: 75,  13: 75,  14: 75,  15: 100,  16: 100,  17: 100,  18: 100,  19: 100,  20: 125,
  21: 125,  22: 125,  23: 125,  24: 125,  25: 150,  26: 150,  27: 150,  28: 150,  29: 150}, 
'max_iter': {0: 100,  1: 200,  2: 300,  3: 400,  4: 500,  5: 100,  6: 200,  7: 300,  8: 400,  9: 500,  
10: 100,  11: 200,  12: 300,  13: 400,  14: 500,  15: 100, 16: 200,  17: 300,  18: 400,  19: 500,  
20: 100,  21: 200,  22: 300,  23: 400,  24: 500,  25: 100,  26: 200,  27: 300,  28: 400,  29: 500}, 
'Score': {0: 0.9270832984321359,  1: 0.9172223807360554,  2: 0.9202868292420568,  3: 0.9187318693456508,
  4: 0.9263589700182026,  5: 0.9325454241272417,  6: 0.9351742112383672,  7: 0.934706441722599,
  8: 0.9350294733755595,  9: 0.9334167352798914,  10: 0.9355533396303661,  11: 0.9327821227628682,
  12: 0.9333376163633981,  13: 0.9322875868305249,  14: 0.9345524934883098,  15: 0.9341786678949748,
  16: 0.9306931295155753,  17: 0.9332227354795629,  18: 0.9312008571438402,  19: 0.9335295484755572,
  20: 0.9333167395841182,  21: 0.9315595511169302,  22: 0.9301811416101524,  23: 0.9314818362895073,
  24: 0.9308551601915486,  25: 0.9296559215457606,  26: 0.9284091216867709,  27: 0.9318823563281231,
  28: 0.9295666150206443,  29: 0.9291284919738931},
 'Time': {0: 119.91294360160828,  1: 256.4710912704468,  2: 266.6792154312134,  3: 326.7445312023163,
  4: 256.8881601810455,  5: 183.77022705078124,  6: 359.7090343952179,  7: 383.6012378692627,
  8: 416.3133870601654,  9: 425.7837643623352,  10: 225.39801173210145,  11: 516.9914848804474,
  12: 562.7134436607361,  13: 585.6752841472626,  14: 560.5802517414093,  15: 267.22873797416685,
  16: 646.1253435134888,  17: 811.1979314804078,  18: 780.6058969974517,  19: 789.9369702339172,
  20: 394.0711458206177,  21: 890.7988158226013,  22: 1065.5482338428496,  23: 996.5119229316712,
  24: 1096.0208141803741,  25: 524.0947244644165,  26: 1182.684538602829,  27: 1348.3343998908997,
  28: 1356.0255290508271,  29: 1053.8607951164245}})


xi = np.linspace(min(df["hidden_layer_sizes"]), max(df["hidden_layer_sizes"]), num=100)
yi = np.linspace(min(df["max_iter"]), max(df["max_iter"]), num=100)

x_grid, y_grid = np.meshgrid(xi,yi)
z_grid = griddata((df["hidden_layer_sizes"],df["max_iter"]),df["Score"],(x_grid,y_grid),method="cubic")

fig = go.Figure(go.Surface(x=x_grid, y=y_grid, z=z_grid, showlegend=True))
fig.update_layout(title="Test",
                  width=600, height=600, template="none",
                  # legend=dict(orientation="h")
                 )

fig.update_layout(legend = dict(orientation="h", x = -0.25, y = -0.10))
fig.update_traces(colorbar = dict(orientation='h', y = -0.25, x = 0.5))
fig.update_layout(showlegend = False)

fig.show()