Use one$\_$sample$\_$mean to define a function simulate$\_$sample$\_$mean. The arguments are the name of the table, the label of the column containing the variable, the sample$\_$size, and the number of simulations $($repetitions$).$

The function should sample with replacement from the table and calculate the mean of each sample. It should save the sample means in an array called means. The remaining code in the function displays an empirical histogram of the sample means.

Note: We round all values to $2$ decimal places in the provided code because we are working with salaries. containing the variable, the sample$\_$size, and the number of simulations $($ repetitions $).$

The function should sample with replacement from the table and calculate the mean of each sample. It should save the sample means in an array called means $.$ The remaining code in the function displays an empirical histogram of the sample means.

Note: We round all values to $2$ decimal places in the provided code because we are working with salaries.

$```$

$"""$Empirical distribution of random sample means"""

def simulate$\_$sample$\_$mean$($table$,$ label, sample$\_$size, repetitions$)$:

means $=$ make$\_$array$()$

for i in np$.$arange$($repetitions$)$:

new$\_$sample$\_$mean $=...$

means $=...$

sample$\_$means $=$ Table$().$with$\_$column$(\text{'}$Sample Means', means$)$

$```$