[FIXED] Set up Numpy random seed to 150 to make sure you get the same results

Issue

I am trying to add Numpy Random seed to 150 to get the same results.

I tried

simulations = np.random.seed(simulations)

But got me a float error

# Generate sales samples 
simulations = 10000
sales_sims = np.random.normal(sales_mean, sales_std, simulations)

print(sales_sims)
print("mean:", np.mean(sales_sims))
print("std:", np.std(sales_sims))

My question: How to set up Numpy random seed to my 10,000 simulations

Solution

Here’s a guide on setting the random state for numpy. What does numpy.random.seed(0) do?

np.random.seed(150) #set seed
sales_mean = 0 # replace with desired value
sales_std = 1 # replace with desired value

#Generate sales samples 
simulations = 10000
sales_sims = np.random.normal(sales_mean, sales_std, simulations)
print(sales_sims)
print("mean:", np.mean(sales_sims))
print("std:", np.std(sales_sims))

Answered By - M. Small