Data Analysis with Python Projects - Mean-Variance-Standard Deviation Calculator

Tell us what’s happening:
Describe your issue in detail here.

Your code so far

import numpy as np

def calculate(list):
  if np.size(list) == 9:
     m = np.reshape(list,(3,3))
     calculations = dict({
    'mean':[np.mean(m,axis=0),np.mean(m,axis=1),np.mean(m)],
    'variance':[np.var(m,axis=0),np.var(m,axis=1),np.var(m)],
    'standard deviation':[np.std(m,axis=0),np.std(m,axis=1),np.std(m)],
    'max':[np.max(m,axis=0),np.max(m,axis=1),np.max(m)],
    'min':[np.min(m,axis=0),np.min(m,axis=1),np.min(m)],
    'sum':[np.sum(m,axis=0),np.sum(m,axis=1),np.sum(m)]
    })
     return calculations
  
  else:
    print('ValueError')

The test is failed, I add dtype =np.float64 but I have the same result.

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Challenge: Data Analysis with Python Projects - Mean-Variance-Standard Deviation Calculator

Link to the challenge:

can you please give the link to your repl?

The link is.

boilerplate-mean-variance-standard-deviation-calculator - Python Repl - Replit

The code can run, but test_module.py shows “”"
FAILED (failures=1, errors=2) “”“”