Python – Iterate Over list Using For Loop

Use for item in list syntax to iterate over a list in Python. By using this for loop syntax you can iterate any sequence objects (stringlisttuplesetrange, or dictionary(dict)). A list contains a collection of values so, we can iterate each value present in the list using Python for loop or while loop.

In this article, you will learn different ways to iterate through a python list.

Quick Examples to Iterate Over a List in Python using For Loop

Following are some of the quick examples of how to iterate over a list in Python using for loop and while loop.


courses = ["java", "python", "pandas"]

# Example 1: Iterate over the list using for loop
for x in courses:
    print(x)

# Example 2: Using range() to iterate over a list
for x in range(len(courses)):
    print(courses[x])

# Example 3: Using enumerate() to iterate over a list
for index , item in enumerate(courses):
    print(index, item)

# Example 4: Use list comprehension to iterate over a list
print([list((i, courses[i])) for i in range(len(courses))])

#Example 5: Using while loop iterate over a list
i = 0
while i < len(courses):
    print(courses[i])
    i += 1

# Example 6: Using  Python NumPy module 
a = np.arange(4)
for x in np.nditer(a):
    print(x)

# Example 7: Using lambda function to iterate over a list
list1 = [3,5,7,9,11]
new_list= list(map(lambda x:x+3 , list1))
print(new_list)

Below I have explained these examples in detail by executing the code and sharing the output.

Table of contents

Iterate over a list by using,

  1. The for loop
  2. The range() function
  3. The enumerate() function
  4. A list comprehension
  5. A while loop
  6. Python NumPy module
  7. The lambda function.

1. Use For Loop to Iterate Over a Python List

The easiest method to iterate the list in python programming is by using it with for loop. Below I have created a list called courses and iterated over using for loop.


# Iterate over the list using for loop
courses = ["java", "python", "pandas"]
for x in courses:
    print(x)

Yields below output.


java
python
pandas

2. Use range() Function To Iterate Over A Python list

The range() method returns a sequence of integers. The range() function starts from 0 and increments by 1(by default) and ends before an end number (n-1).

Use len(courses) to get the size of the list and use the size with range() function to get the list of values starting from 0 by incrementing 1 until the size of the list. To retrieve the value from the list use courses[x] within the body of for loop.


# Using range() to iterate over a list
courses = ['java','python','pandas','sparks']
for x in range(len(courses)):
    print(courses[x])

Yields below output.


java
python
pandas
sparks

3. Python For Loop With enumerate() To Iterate List

The enumerate() method can be used for any iterable objects such as list, range e.tc. Using enumerate() method we can access an index of iterable objects and return enumerate objects.

3.1 Syntax of enumerate()

Following is the syntax of enumerate() function that I will be using rest of the article.


enumerate(iterable_object,start=0)
  • The enumerate() method can be used for any iterable objects such as list, and range.
  • Using enumerate() method we can access an index of iterable objects.
  • enumerate() method has two parameters: iterable objects( such as list, tuple) and start parameter.
  • enumerate() method starts with 0 (by default). Use start parm to define the custom start position.
  • It returns enumerate object.

The below example shows the type of the enumerate object.


# Using type() to get enumerate type
courses = ["java","python","pandas"]
courses_index = enumerate(courses)
print(courses_index)
print(type(courses_index))


# Outputs
<enumerate object at 0x7fe3c12c83c0>
<class 'enumerate'>

3.2 Convert enumerate to List

The enumerate() method combines indices to iterable objects and returns them as an enumerated object. This enumerated object can be easily converted to a list using a list(). This is the easiest way of accessing both items and their indices at once. You need to understand this as it will give you insight into how enumerate provides you with an index.


# Convert enumerate object to list object
courses = ["java","python","pandas"]
courses_index = enumerate(courses)
print(list(courses_index))

# Outputs
[(0, 'java'), (1, 'python'), (2, 'pandas')]

As you see, the values in the list are now inside a tuple where the first value in the tuple is an index and the second is a value from a list.

3.3 Use enumerate() To Iterate Over a List

In Python when you use enumerate() to iterate the list, it returns an index and item for each element in a enumerate


# Using enumerate() to iterate over a list
courses=['java','python','pandas','sparks']
for index , item in enumerate(courses):
    print(index,item)

# Outputs
0 java
1 python
2 pandas
3 sparks

3.4 Start Loop Indexing with Non-Zero Value

You can change the start parameter to change the indexing. By default, it is 0. Now start loop indexing with a non-zero value(start=1).


# Start loop indexing with non zero value
courses=['java','python','pandas','sparks']
for index , item in enumerate(courses,start=1):
    print(index,item)

# Outputs
1 java
2 python
3 pandas
4 sparks

4. Using a List Comprehension to Iterate Over a List

List comprehension allows a lesser syntax if you want to create a new list based on an already existing list. Using list comprehension we can manipulate lists, more efficiently compared to functions and Python for loops.

4.1 Syntax of the List Comprehension


# Syntax of the list comprehension
[expression for item in list]
  • list – Is a collection of elements.
  • item – Elements are present in the sequence which is iterable.
  • expression – Combination of operators and operands.

Let us take a simple example for a better understanding


# Using list comprehension manipulate list
list = [20,10,40,50]
products = [x*2 for x in list]
print(products)

# Outputs
[40, 20, 80, 100]

According to the above example in the list comprehension, List represents iterable object x represents item and x*2 represents expression.

4.2 Use A List Comprehension To Iterate Over List


# Use list comprehension to iterate over a list
courses=['java','python','pandas','sparks']
print([list((i, courses[i])) for i in range(len(courses))])

# Outputs
[[0, 'java'], [1, 'python'], [2, 'pandas'], [3, 'sparks']]

We got 4 lists as an output, containing the index and its corresponding value in courses.

5. Use A While Loop To Iterate Over the List

The while loop in Python is used to iterate over a block of code as long as the test condition is true. It is used when we don’t know the number of times the code block will execute.

5.1 Syntax Of The While Loop


while(condition) :
    body of the loop

The process of the while loop, initially condition will be checked if only the test condition is True, the body of the code will execute. This process continues until the test condition is False.

Everything in Python is an object, every object in Python has a boolean value. The boolean value of 0 or None is False and the boolean value of non-zero value is True.

We can exit from the while loop using the break statement.

Use continue statement inside of the while loop to skip the current block of code.

Python supports nested while loops as-well.

Let’s take an example for better understanding,


# Using while loop print 'hello'
i=1
while i <= 5:
    print("hello")
    i=i+1

#Outputs
hello
hello
hello
hello
hello

5.2 Iterate Over A Python List Using While Loop

Using a while loop we can iterate over a Python list. In the following example, I have taken courses as a list, it has been iterated with the help of len(courses) using the while loop. Then it is processed based on the condition until the condition reach False.


# Using while loop iterate over a list
courses = ["java","python","pandas","sparks"]
i = 0
while i < len(courses):
    print(courses[i])
    i += 1

#Outputs
java
python
pandas
sparks

6. Using Python NumPy Module With For Loop

Iterating means going through elements one by one. As we deal with multi-dimensional arrays in NumPy, we can do this using the basic for loop of python. If we iterate on a 1-D array it will go through each element one by one.

Arrays support the iterator protocol and can be iterated over like Python lists

6.1 Single Array Iteration

The most basic task that can be done with the nditer(iterator object) is to visit every element of an array. Each element is provided one by one using the standard Python iterator interface.


# Using  Python NumPy module 
a = np.arange(7)
for x in np.nditer(a):
    print(x)

#outputs
0
1
2
3
4
5
6
 

From the above example np.arange(7) creates a sequence of integers from 0 to 6.

7. Python For Loop Iterate a List Using Lambda Function

Python lambda function is an anonymous function.

Syntax


lambda arguments: expression

The lambda function along with a Python map() function can be used to iterate a list easily.

Python map() method allows a lambda function as a parameter and returns a list. The function is called with all the items in the list and returned a new list, which contains all items respectively returned from that function.


# Using lambda function to iterate over a list
list1 = [3,5,7,9,11]
new_list= list(map(lambda x:x+3 , list1))
print(new_list)

#Outputs
[6, 8, 10, 12, 14]

Conclusion

In this article, you have learned multiple ways to iterate over a Python list by using for loop, range(), enumerate(), list comprehension, and while loop. You have also learned the basic idea of NumPy and lambda function while iterating items in the list.

Happy learning !!

References

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