Finding the boolean from a table of random integers compared to a list

Question

Inputs are:

1. A Panda Dataframe with 500 columns and 10 lines, which contains a series of random integers comprised between 0 and 10000 (included)

2. A list of 10 random integers comprised between 0 and 10000

The output I am looking for is:

A Panda Dataframe with 500 columns and 10 lines, which gives the Boolean true or false depending if the element from the x-th line is above (true) or below (false) the number which is the x-th element of the list

I was able to solve this in excel using the following functions:

1. =RANDARRAY(10,1,0,10000,TRUE)
2. =IF(RANDARRAY(10,500,0,10000,TRUE)>A1,TRUE,FALSE)

Is there an elegant way of producing this solution in python? I am still a beginner learning more about python.

Thank you for the help

Update: Using MSS's solution, this is my final code. Could you please tell me if there are any mistakes in my code?

import numpy as np
import pandas as pd
import random

df = pd.DataFrame(np.random.randint(0,10000,size=(10, 500)))
df.head

list = random.sample(range(10000), 10)
print(list)

a = df.to_numpy()
b = np.array(list) 
res = pd.DataFrame(a > b[:,None], index= df.index, columns=df.columns)
print(res)

Thank you for the help

Answer 1

You can do it in this way using numpy.

a = df.to_numpy() # Dataframe of shape (10,500)
b = np.array(your_list) # your_list contains 10 random numbers >=1 and <=10000
res = pd.DataFrame(a > b[:,None], index= df.index, columns=df.columns)

Lets explain using a smaller dataframe having 3 lines and 5 columns and a list having 3 numbers. All numbers are random between 1-9.

inter = np.array([[1,2,3,5],[4,5,6,1],[7,8,9,5]])
df = pd.DataFrame(inter)
your_list = [3,6,7]

The output obtained after applying above code is:

    0       1       2       3
0   False   False   False   True
1   False   False   False   False
2   False   True    True    False

Hence solution is correct.