Python Program to Find Largest Number in a List
Last Updated :
28 Aug, 2023
Given a list of numbers, the task is to write a Python program to find the largest number in given list.
Examples:
Input : list1 = [10, 20, 4]
Output : 20
Find Largest Number in a List with Native Example
Sort the list in ascending order and print the last element in the list.
Python3
list1 = [ 10 , 20 , 4 , 45 , 99 ]
list1.sort()
print ( "Largest element is:" , list1[ - 1 ])
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Output
Largest element is: 99
Time Complexity: O(nlogn)
Auxiliary Space: O(1)
Find Largest Number in a List Using max() method
Here list1 is a list with some element and we will use max() function, this will return maximum from the array.
Python3
list1 = [ 10 , 20 , 4 , 45 , 99 ]
print ( "Largest element is:" , max (list1))
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Output
Largest element is: 99
Time complexity : O(n)
Auxiliary Space : O(1)
Find the max list element on inputs provided by user
Python3
list1 = []
num = int ( input ( "Enter number of elements in list: " ))
for i in range ( 1 , num + 1 ):
ele = int ( input ( "Enter elements: " ))
list1.append(ele)
print ( "Largest element is:" , max (list1))
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Output:
Enter number of elements in list: 4
Enter elements: 12
Enter elements: 19
Enter elements: 1
Enter elements: 99
Largest element is: 99
Time complexity : O(n)
Auxiliary Space : O(1)
Find Largest Number in a List Without using built-in functions
Python3
def myMax(list1):
max = list1[ 0 ]
for x in list1:
if x > max :
max = x
return max
list1 = [ 10 , 20 , 4 , 45 , 99 ]
print ( "Largest element is:" , myMax(list1))
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Output
Largest element is: 99
Time complexity : O(n)
Auxiliary Space : O(1)
Find Largest Number in a List Using the lambda function
Python lambda which is also know as inline function, here we will use max inside the lambda.
Python3
lst = [ 20 , 10 , 20 , 4 , 100 ]
print ( max (lst, key = lambda value: int (value)) )
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Time complexity : O(n)
Auxiliary Space: O(n), where n is the length of the list.
Find Largest Number in a List Using reduce function
Using reduce() function we will get the maximum element from the array.
Python3
from functools import reduce
lst = [ 20 , 10 , 20 , 4 , 100 ]
largest_elem = reduce ( max , lst)
print (largest_elem)
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Time Complexity: O(n)
Auxiliary Space: O(1)
Find Largest Number in a List Using recursion
Python3
def FindLargest(itr, ele, list1):
if itr = = len (list1):
print ( "Largest element in the list is: " , ele)
return
if ele < list1[itr]:
ele = list1[itr]
FindLargest(itr + 1 , ele, list1)
return
list1 = [ 2 , 1 , 7 , 9 , 5 , 4 ]
FindLargest( 0 , list1[ 0 ], list1)
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Output
Largest element in the list is: 9
Time Complexity: O(n)
Auxiliary Space: O(n)
Find Largest Number in a List Using heapq.nlargest()
Here’s how you can use heapq.nlargest() function to find the largest number in a list:
Algorithm:
- Import the heapq module.
- Create a list of numbers.
- Use the heapq.nlargest() function to find the largest element. The nlargest() function takes two arguments – the first argument is the number of largest elements to be returned, and the second argument is the list of numbers.
- Retrieve the largest element from the list of largest elements returned by heapq.nlargest() function.
- Print the largest element.
Python3
import heapq
list1 = [ 10 , 20 , 4 , 45 , 99 ]
largest_element = heapq.nlargest( 1 , list1)[ 0 ]
print ( "Largest element is:" , largest_element)
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Output
Largest element is: 99
Time complexity: O(nlogk), where n is the length of the list and k is the number of largest elements to be returned. In this case, k is 1, so the time complexity is O(nlog1) = O(n).
Auxiliary Space: O(k), where k is the number of largest elements to be returned. In this case, k is 1, so the auxiliary space is O(1).
Find Largest Number in a List Using np.max() method
- Initialize the test list.
- Use np.array() method to convert the list to numpy array.
- Use np.max() method on numpy array which gives the max element in the list.
Python3
import numpy as np
list1 = [ 2 , 7 , 5 , 64 , 14 ]
arr = np.array(list1)
num = arr. max ()
print (num)
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Output:
64
Time Complexity: O(n) where n is the length of the list.
Auxiliary Space: O(n) where n is the length of the list. because numpy array of length n is created.
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