CODEWITHSUNDEEP
pythonarrayslistnumpymultidimensional-array
zmorris
zmorris

Reputation: 35

Find Element In Two-Dimensional Python Array

What I am trying to do is take a user input for as many rows as they wish, and make it into an array. After that i want to find where the highest number is in the array, an (x,y) coordinate of the number type of thing. I have created the initial array in different way but for example I have:

  import numpy as np
  m = []
  rows = eval(input("How many rows in the list:"))
  for row in range(rows):
      m.append([])
      value = eval(input("Enter a row:"))
      m[row].append(value)
  m = np.array(m)
  print(m)
  M = np.amax(m)
  print(M)
  index = np.where(M)
  print(index)

The printing is just so i can see what it is doing. As a final i just want to see the last line in this example:

   Enter the number of rows in the list:3          
   Enter a row: 1,5,6        
   Enter a row: 2,6,7     
   Enter a row: 5,26,12     
   The location of the largest element is at (1, 2)

Extra info: I don't care if it uses numpy of not. and i wouldn't be against using separate functions, when i think about it it might be a good idea; one to create an array and a separate to locate the largest number.

Thanks in advance.

PS. As the comment says, eval shouldn't usually be used because of security risks. The only reason I am using it is because this is a quick assignment for school.

Upvotes: 1

Views: 7261

Answers (2)

Prajwal
Prajwal

Reputation: 4000

This is an implementation without using numpy. It is not that efficient, but works fine.

rows = eval(input("How many rows in the list:"))
m = []
for row in range(rows):
  value = eval(input("Enter a row:"))
  m.append(value)

large = m[0][0]
x = 0
y = 0

for i in range(0, rows):
  for j in range(0, len(m[i])):
    if(large < m[i][j]):
     large = m[i][j]
     y = i
     x = j
print(x, y, large)

Upvotes: 1

Vivek Kalyanarangan
Vivek Kalyanarangan

Reputation: 9081

This gives the (row,column) index of the max - 

import numpy as np

m = np.array([[1,5,6],[2,6,7],[5,26,12]]) # input minified
print(m)

print np.unravel_index(m.argmax(), m.shape) # main code you need

Upvotes: 1

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