```
import numpy as np
from numpy.core.fromnumeric import var
def calculate(list):
try:
#Make the list into an NumPy Array
list = np.array(list)
#Reshape the Array into a 3D Array
new_ar = list.reshape(3,3)
#Get the mean
mean_column = np.mean(new_ar, axis = 0).tolist()
mean_row = np.mean(new_ar, axis =1).tolist()
flat = np.mean(list)
#Get the variance
variance_column = np.var(new_ar, axis=0).tolist()
variance_row = np.var(new_ar, axis=1).tolist()
flat_var = np.var(list)
#Get the Standard Deviation
std_dev_col= np.std(new_ar, axis = 0).tolist()
std_dev_row= np.std(new_ar, axis = 1).tolist()
std_flat = np.std(list)
#Get Maximum , Minumum and Sum
max_col = np.max(new_ar, axis=0).tolist()
max_row = np.max(new_ar,axis = 1).tolist()
max_flat = np.max(list)
min_col = np.min(new_ar, axis=0).tolist()
min_row = np.min(new_ar,axis = 1).tolist()
min_flat = np.min(list)
sum_col = np.sum(new_ar, axis=0).tolist()
sum_row = np.sum(new_ar,axis = 1).tolist()
sum_flat = np.sum(list)
# Create a Dictionary and Join it all together
answer = dict()
answer['mean'] = [mean_column, mean_row, flat]
answer['variance'] = [variance_column, variance_row, flat_var]
answer['standard deviation'] = [std_dev_col, std_dev_row, std_flat]
answer['max'] = [max_col, max_row, max_flat]
answer['min'] = [min_col, min_row, min_flat]
answer['sum'] = [sum_col, sum_row, sum_flat]
return answer
except ValueError:
print("List must contain nine numbers.")
```

Here’s the Error

I don’t know what to is the expected output on the ValueError part