Tell us what’s happening:
My solution for the mean-variance-std project passes the first two tests. But, it fails to show the error message when a list that is not equal to 9 is passed. My solution works fine in Jupyter Notebook and I cannot figure out why it fails the fCC test. Any help or suggestions would be appreciated. Thanks.
Your code so far
import numpy as np
#a = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8])
def calculate(list):
if len(list) != 9:
return “List must contain nine numbers.”
x = np.array(list).reshape(3, 3)
mean0 = np.mean(x, axis=0).tolist() # collapses rows
mean1 = np.mean(x, axis=1).tolist() # collapses columns
meanN = np.mean(x, None).tolist()
var0 = np.var(x, axis=0).tolist() # collapses rows
var1 = np.var(x, axis=1).tolist() # collapses columns
varN = np.var(x, None).tolist()
std0 = np.std(x, axis=0).tolist() # collapses rows
std1 = np.std(x, axis=1).tolist() # collapses columns
stdN = np.std(x, None).tolist()
max0 = np.max(x, axis=0).tolist() # collapses rows
max1 = np.max(x, axis=1).tolist() # collapses columns
maxN = np.max(x, None).tolist()
min0 = np.min(x, axis=0).tolist() # collapses rows
min1 = np.min(x, axis=1).tolist() # collapses columns
minN = np.min(x, None).tolist()
sum0 = np.sum(x, axis=0).tolist() # collapses rows
sum1 = np.sum(x, axis=1).tolist() # collapses columns
sumN = np.sum(x, None).tolist()
values = [[mean0, mean1, meanN], [var0, var1, varN],
[std0, std1, stdN], [max0, max1, maxN],
[min0, min1, minN], [sum0, sum1, sumN]]
keys = ["mean", "variance", "standard deviation", "max", "min", "sum"]
result = {keys[i]: values[i] for i in range(len(keys))}
return result
Your browser information:
User Agent is: Mozilla/5.0 (X11; Linux x86_64; rv:97.0) Gecko/20100101 Firefox/97.0
Challenge: Mean-Variance-Standard Deviation Calculator
Link to the challenge: