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

Python
1

Tell us what’s happening:

Describe your issue in detail here.

Your code so far

import numpy as np

def calculate(list):
while True:
try:
array = np.array(list)
matrix = np.reshape(array, (3, 3))
mean_ax_1 =
mean_ax_2 =
mean_flat = np.mean(list)
var_ax_1 =
var_ax_2 =
var_flat = np.var(list)
st_dv_ax_1 =
st_dv_ax_2 =
st_dv_flat = np.std(list)
max_ax_1 =
max_ax_2 =
max_flat = np.max(list)
min_ax_1 =
min_ax_2 =
min_flat = np.min(list)
sum_ax_1 =
sum_ax_2 =
sum_flat = np.sum(list)

  for i in range(matrix[0].size):
    mean_ax_1.append(matrix[:, i].mean())
    var_ax_1.append(matrix[:, i].var())
    st_dv_ax_1.append(matrix[:, i].std())
    max_ax_1.append(matrix[:,i].max())
    min_ax_1.append(matrix[:, i].min())
    sum_ax_1.append(matrix[:, i].sum())

  for i in range(matrix[:,0].size):
    mean_ax_2.append(matrix[i].mean())
    var_ax_2.append(matrix[i].var())
    st_dv_ax_2.append(matrix[i].std())
    max_ax_2.append(matrix[i].max())
    min_ax_2.append(matrix[i].min())
    sum_ax_2.append(matrix[i].sum())

  calculations = {
    'mean': [mean_ax_1, mean_ax_2, mean_flat],
    'variance': [var_ax_1, var_ax_2, var_flat],
    'standard deviation': [st_dv_ax_1, st_dv_ax_2, st_dv_flat],
    'max': [max_ax_1, max_ax_2, max_flat],
    'min': [min_ax_1, min_ax_2, min_flat],
    'sum': [sum_ax_1, sum_ax_2, sum_flat]
  }

  return calculations
  break

except ValueError:
  return "List must contain nine numbers."

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Challenge Information:

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

2

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