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

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 2

#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 3

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 4

Please help. Thank you.

Answer 5

Josiah Mathieu and what am I missing?

Answer 6

I solved it. Thank you.

Answer 7

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

Answer 8

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

Answer 9

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 10

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 11

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

Answer 12

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 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))))

Answer 14

Your code works for the given sample, but it has one issue — you’ve hardcoded 2 as the number of columns:
arr.reshape(r, 2)
That will only work if the number of columns is always 2, which is not guaranteed by the problem statement.
Instead, you should calculate the number of columns from the total length of the list and r.

Here’s the corrected version:

python
Copy
Edit
import numpy as np

r = int(input())
lst = [float(x) for x in input().split()]
arr = np.array(lst)

# Calculate columns automatically
c = len(lst) // r

print(np.round(arr.reshape(r, c), decimals=2))
Why this works:

len(lst) // r ensures the columns are computed based on input size.

.reshape(r, c) creates the correct 2D shape.

np.round(..., 2) rounds to 2 decimal places as required.