TypeError: unsupported operand type(s) for -: ‘dict’ and ‘dict’
Hello, I’ve done my code… but it seems like the test package cannot directly compare dict to dict, which they use
diff = abs(first - second)
I 've tried to change my return from dict to str , but instead now it say 'TypeError: unsupported operand type(s) for -: ‘str’ and 'dict
what can I do in this kind of situation ?
import numpy as np
def calculate(lst):
lst = np.array(lst)
if np.shape(lst) != (9,):
raise ValueError ('List must contain nine numbers.')
input = np.reshape (lst,(3,3))
calculations = {}
mean_ax1 = np.mean(input, axis=0)
mean_ax2 = np.mean(input, axis=1)
mean_all = np.mean(input)
calculations['mean']= [mean_ax1.tolist(), mean_ax2.tolist(), mean_all.tolist()]
var_ax1 = np.var(input, axis=0)
var_ax2 = np.var(input, axis=1)
var_all = np.var(input)
calculations['variance']= [var_ax1.tolist(), var_ax2.tolist(), var_all.tolist()]
std_ax1 = np.std(input, axis=0)
std_ax2 = np.std(input, axis=1)
std_all = np.std(input)
calculations['standart deviation']= [std_ax1.tolist(), std_ax2.tolist(), std_all.tolist()]
max_ax1 = np.max(input, axis=0)
max_ax2 = np.max(input, axis=1)
max_all = np.max(input)
calculations['max']= [max_ax1.tolist(), max_ax2.tolist(), max_all.tolist()]
min_ax1 = np.min(input, axis=0)
min_ax2 = np.min(input, axis=1)
min_all = np.min(input)
calculations['min']= [min_ax1.tolist(), min_ax2.tolist(), min_all.tolist()]
sum_ax1 = np.sum(input, axis=0)
sum_ax2 = np.sum(input, axis=1)
sum_all = np.sum(input)
calculations['sum']= [sum_ax1.tolist(), sum_ax2.tolist(), sum_all.tolist()]
return calculations
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