[FIXED] Add "nan" to numpy histogram python

Issue

I am using random library to generate 5000 data points from a Gaussian distribution and then using the data to compute histogram with 10 bins, see code below.

s = np.random.normal(mu, sigma, 5000)
arrHist = np.histogram(s, 10)
print(arrHist)

Output is:

(array([   9,   48,  282,  800, 1436, 1424,  742,  216,   40,    3]), 
 array([1.52017489, 1.61690575, 1.71363661, 1.81036747, 1.90709834,
       2.0038292 , 2.10056006, 2.19729092, 2.29402179, 2.39075265,
       2.48748351]))

As you can see there are different array lengths and therefore I want to add np.nan to the shorter array, so that array lengths are the same. I know it is possible to use np.append to append values to the end of an array, but how can I do it when there are two arrays in arrHist?

I am new with python, therefore is any help appreciated. Thanks in advance.

Solution

Try this:

result=[]
max_len=max([len(x) for x in arrHist])
for x in arrHist:
    if len(x)!=max_len:
        x=x.astype('float')
        x=np.pad(x, (0,max_len-len(x)), 'constant', constant_values=(np.nan, ))
    result.append(x)
         

Answered By - NicolasPeruchot