Generating random dataframes using unique elements from an existing dataframe using pandas

I am trying to do some data manipulations using pandas. I have an excel file with two columns x,y . The number of elements in x corresponds to number of connections(n_arrows) it makes with an element in column y. The number of unique elements in column x corresponds to the number of unique points(n_nodes). What i want to do is to generate a random data frame(10^4 times) with the unique elements in column x and elements in column y? The code i was trying to work on is attached. Any suggestion will be appreciated

import pandas as pd
import numpy as np
df = pd.read_csv('/home/amit/Desktop/playing_with_pandas.csv')
num_nodes = df.drop_duplicates(subset='x', keep="last")
n_arrows = [32]             #32 rows corresponds to 32 
n_nodes = [10]
n_arrows_random = np.random.randn(df.x)