Data Science - Reshape

Question

Task
Given a list of numbers and the number of rows (r), reshape the list into a 2-dimensional array. Note that r divides the length of the list evenly.
Input Format
First line: an integer (r) indicating the number of rows of the 2-dimensional array
Next line: numbers separated by the space
Output Format
An numpy 2d array of values rounded to the second decimal.
Sample Input
2
1.2 0 0.5 -1
Sample Output
[[ 1.2 0. ]
[ 0.5 -1. ]]
import numpy as np
r = int(input())
lst = [float(x) for x in input().split()]
arr = np.array(lst)
print(np.round(arr.reshape(r, 2), decimals=2))

Answer 1

The note that r DIVIDES THE LENGTH of the list evenly tells you that the 2D array will always have enough elements to fill r rows evenly (no empty spots).
Therefore you have to have the number of columns in which r rows creates an acceptable 2D array.

Answer 2

try
r = int(input())
lst = [float(x) for x in input().split()]
arr = np.array(lst)
arr_new=arr.reshape(r,-1) #-1 stands for any value that numpy founds suitable.
print(arr_new)

Answer 3

#library import
import numpy as np
#input and create list
row = int(input())
lst = [round(float(x), 2) for x in input().split()]
#number of columns
column = len(lst)//row
#reshape numpy array
arr = np.array(lst)
arr_2d = arr.reshape(row, column)
print(arr_2d)

Answer 4

hack with `.reshape(r,-1)` works but it didn't explained in the course :)

Answer 5

This is 15 code project (in data science course)
I Think that I don't understand this:
"Note that r divides the length of the list evenly."
of the task.
The 2 first tests are o.k. but the next 3 tests are wrong.

Answer 6

Please help. Thank you.

Answer 7

Josiah Mathieu and what am I missing?

Answer 8

I solved it. Thank you.

Answer 9

Can somebody explain why reshape(r,2) doesn`t work?

Answer 10

The inputs of Next line(lst) are not divisible by 2 in all the tests

Answer 11

import numpy as np
r = int(input())
lst = [float(x) for x in input().split()]
arr = np.array(lst)
p=np.array(lst)+np.array(arr)
k=p.size//r
print((p/2).reshape(r,k))

Answer 12

import numpy as np
r = int(input())
lst = [float(x) for x in input().split()]
arr = np.array(lst)
arr=arr.reshape(r,-1)
print(arr)

Answer 13

import numpy as np
r = int(input())
lst = [float(x) for x in input().split()]
arr = np.array(lst)
print(np.reshape(arr, (r, int(len(lst) / r))))