In this tutorial, we’ll get to see the way to Loop with List Python essentially an ordered arrangement which enables us to store and manipulate the info in it also.

So, now lets see the various methods to do our tasks.

## The various methods –> Loop with List Python

### Iterating with range() method

Python’s range() method are often utilized in combination with a for loop to traverse and also loop over a list in Python. This method basically returns a sequence of integers i.e. it builds/generates a sequence of integers from the provided start index up to the top index as laid out in the argument list.

Syntax:

``````range (start, stop[, step])
``````

Example:

``````n = [100, 510, 705, 823, 938, 145, 312]
for x in range(len(n)):
print(n[x])``````

Output:

``````100
510
705
823
938
145
312``````

### Using a for Loop

Python for loop is often used to loop through lists directly.

Syntax:

``````for var_name in input_list_name:
``````

Example:

``````n = [100, 510, 705, 823, 938, 145, 312]
for x in n:
print(x)``````

Output:

``````100
510
705
823
938
145
312``````

## Using List Comprehension

Python List Comprehension is an indifferent way of generating an inventory of elements that possess a selected property or specification i.e. it can identify whether the input may be a list, string, tuple, etc.

Syntax:

``[expression/statement for item in input_list]``

Example:

``````n = [100, 510, 705, 823, 938, 145, 312]
[print(x) for x in n]``````

Output:

``````100
510
705
823
938
145
312``````

## Using while Loop — loop with list python

``````while x < len(n):
print(n[x])
x = x+1``````

Output:

``````100
510
705
823
938
145
312``````

## Using NumPy

Python NumPy Arrays also can be wont to iterate an inventory efficiently. Also, the numpy.arange() function creates a consistent sequence of integers.

Syntax :

``numpy.arange(start, stop, step)``

The numpy.nditer(numpy_array)also may be a function that gives us with an iterator to traverse through the NumPy array.

Example:

``````import numpy as np
n = np.arange(5)
for x in np.nditer(n):
print(x)``````

Output:

``````0
1
2
3
4
5``````

## The enumerate() method

The Python enumerate() function is in use to iterate the list in an optimized manner thus. Also, the enumerate() function adds a counter to the list or the other iterable and returns it as an enumerate object by the function. Thus, it reduces the overhead of keeping a count of the weather while the iteration operation.

Syntax:

``enumerate(iterable, start_index)``

Example:

``````n = [100, 510, 705, 823, 938, 145, 312]
for x, result in enumerate(n):
print (x,":",result)``````

Output:

``````0 : 100
1 : 510
2 : 705
3 : 823
4 : 938
5 : 145
6 : 312``````

## Using Lambda function

These are generally anonymous functions, i.e. without any name.

Syntax:

``lambda parameters: expression``

Also, the lambda function along side a Python map() function is often used to iterate lists very easily. Thus, Python map() method accepts a function as a parameter and returns a list.

The input function to the map() method thus, gets called with every element of the iterable and it returns a replacement list with all the weather returned from the function, respectively.

Example:

``````n = [100, 510, 705, 823, 938, 145, 312]
result = list(map(lambda x:x, n))
print(result)``````

Output:

``````0 : 100
1 : 510
2 : 705
3 : 823
4 : 938
5 : 145
6 : 312``````

The input_list (lst) is provided because the second argument to the map() function. So, the map() function will pass every element of lst to the lambda x:x function and return the weather .

## SUMMING UP —> Loop with List Python

In this post, thus, we have gone through the various methods in our task to loop with list Python. We have also discussed this in detailed steps and procedures with all technicalities. Thus, we are now well accomplished and ready to work out our way through various such tasks.

By and through this article, thus, I suppose I have made myself pretty clear. But, in case, you still have some doubts lingering. Then, please do write to me in the comments section and I am as always, ever-ready to help you. And, also solve your many queries and problems.

Until then bidding you Good-Bye !!! Ok, wait ….. before you go, you may check out my various other posts. Also, for the simple reason, that is, to enhance your knowledge on various other topics of importance. Also, where ??? Here……