Python: simple mapping of dataframe styler

Question

I am stuck on figuring out how to map a pre-existing df of styling options to a df of integers:

import numpy as np
import pandas as pd

# Create a 9 x 3 array of integers
random_state = np.random.RandomState(seed=44)
myArray = random_state.randint(0,9, (9,3))

Which gives the output:

[[4 3 1]
 [3 0 4]
 [3 8 7]
 [7 6 3]
 [7 3 3]
 [6 5 4]
 [5 1 8]
 [7 4 5]
 [3 0 4]]

Then create a random 2D list of 'color: option' to be mapped onto myArray with the styler:

styleList    = []
colorOptions = ['color: lime','color: red','color: yellow']

for i in arr:
  inner = []
  for j in i:
    inner.append(np.random.choice(colorOptions))
  styleList.append(inner)

for i in styleList: print(i)

Check the output:

['color: yellow', 'color: lime'  , 'color: red']
['color: red'   , 'color: lime'  , 'color: red']
['color: yellow', 'color: yellow', 'color: yellow']
['color: yellow', 'color: red'   , 'color: lime']
['color: yellow', 'color: red'   , 'color: yellow']
['color: red'   , 'color: lime'  , 'color: yellow']
['color: red'   , 'color: yellow', 'color: red']
['color: yellow', 'color: yellow', 'color: yellow']
['color: lime'  , 'color: red'   , 'color: red']

Convert both of these to dataframes:

df      = pd.DataFrame(data=myArray,   index=None, columns=['col1', 'col2', 'col3'])
dfStyle = pd.DataFrame(data=styleList, index=None, columns=['col1', 'col2', 'col3'])

Since I already have the dataframe dfStyle with the styling options, how can I simply map its values to the integer values in df (and without having to generate dfStyle within a separate function)?

I'll avoid cluttering this space with my various attempts using df.style.apply(), df.style.applymap() and even functions that attempt to simply return dfStyle, but this seemingly straightforward task has thrown me in circles.

Desired result is a styled df:

df[0][0] should be the number 4 displayed with the color yellow

df[0][1] should be the number 3 displayed with the color lime

df[0][2] should be the number 1 displayed with the color red

etc.

Thanks for any help.

••• UPDATE •••

I figured out how to properly map the style as I wanted by using:

def color(row):
  dfs = dfStyle.copy()
  x = [dfs.iloc[row.name][j] for i,j in zip(row, dfStyle)]
  return x

df.style.apply(color, axis=1)

which results in the desired:

Answer 1

As posted at the end of my question, I managed to arrive at my desired solution with:

def color(row):
  dfs = dfStyle.copy()
  x = [dfs.iloc[row.name][j] for i,j in zip(row, dfStyle)]
  return x

df.style.apply(color, axis=1)

Although this is indeed the solution I was after, it seems like a rather convoluted and unnecessarily complicated way of getting there.

I would still be grateful to know of a simple and intuitive way to achieve the same.