Generate random numbers from a distribution given by a list of numbers in python

Let's say I have a list of (float) numbers:

list_numbers = [0.27,0.26,0.64,0.61,0.81,0.83,0.78,0.79,0.05,0.12,0.07,0.06,0.38,0.35,0.04,0.03,0.46,0.01,0.18,0.15,0.36,0.36,0.26,0.26,0.93,0.12,0.31,0.28,1.03,1.03,0.85,0.47,0.77]

In my case, this is obtained from a pandas dataframe column, meaning that they are not bounded between any pair of values a priori.

The idea now is to obtain a new list of randomly-generated numbers, which follow the same distribution, meaning that, for a sufficiently large sample, both lists should have fairly similar histograms.

I tried using np.random.choice, but as I do not want to generate one of the values in the original list but rather new values which are or not in it, but follow the same distribution, it does not work...