Data Science Average of Rows questions

Question

Regarding the Code challenge in the Data Science course chapter 1 (Data Manipulation) "Average of rows": My code seems to be wrong for the last two hidden test cases, but I can't find the error. Can anyone help me and give me a hint?
Here's the code:

import numpy as np
n, p = [int(x) for x in input().split()]
means = []
for i in range(n):
list = [float(x) for x in input().split()]
means.append(sum(list)/len(list))
arr = np.array(means)
np.around(arr, decimals=2)
print(arr)

Answer 1

For a start, it would be nice to know the assignment.

Answer 2

You forgot to round the output to the second decimal place, as required by the task.

Answer 3

Right, I copied the assignment here: In a matrix, or 2-d array X, the averages (or means) of the elements of rows is called row means.

Task
Given a 2D array, return the rowmeans.

Input Format
First line: two integers separated by spaces, the first indicates the rows of matrix X (n) and the second indicates the columns of X (p)
Next n lines: values of the row in X

Output Format
An numpy 1d array of values rounded to the second decimal.

2 2
1.5 1
2 2.9

Sample Output
[1.25 2.45]

Answer 4

You’re right, thanks :)

Answer 5

import numpy as np

n, p = [int(x) for x in input().split()]

# Initialize matrix
matrix = []

#Entry row elements separated by space
for i in range(n):
matrix.append(input().split())

print(np.array(matrix).astype(np.float16).mean(axis=1).round(2))

#This will work

Answer 6

import numpy as np
n, p = [int(x) for x in input().split()]
my_list = []
for i in range(n):
my_list.append(list(float(x) for x in (input().split())))
my_list_ar = np.array(my_list)
my_list_ar.reshape(n, p)

print(np.around((my_list_ar.mean(axis=1)), decimals=2))