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what is the solution n, p = [int(x) for x in input().split()]
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]
4 odpowiedzi
+ 2
n, p = [int(x) for x in input().split()]
import numpy as np
arr=np.ones((n,p))
for i in range(n):
arr[i,:]=np.array(input().split())
mean =arr.mean(axis=1).round(2)
print(mean)
0
#Try this in Python :
lens = list(map(lambda x : int(x), input().split(" ")))
avg = []
for i in range(lens[0]) :
avg.append(round(sum(list(map(lambda x : float(x), input().split(" ")))) / lens[1], 2))
print(avg)
0
n, p = [int(x) for x in input().split()]
import numpy as np
lijst = [[0]*p for _ in range(n)]
#print (n)
#print (p)
#print (lijst)
for i in range(n):
lijst[i] = [float(j) for j in input().strip().split(" ")]
#print(lijst)
npArray = np.array(lijst)
#print(npArray)
#npArray = npArray.astype(np.float64)
gemiddeldRij = npArray.mean(axis=1).round(2)
print(gemiddeldRij)
- 1
n, p = [int(x) for x in input().split()]
import numpy as np
list1 = []
for i in range(n):
list1.append(input().split())
#print(list1)
L1_array = np.array(list1)
#print(list1_array)
L1_array = L1_array.astype(np.float)
mean = L1_array.mean(axis=1).round(2)
print(mean)