iterator object by using zip

name=['Ravi','Raju','Alex']
id=[1,2,3]
MATH=[30,40,50]
my_data=zip(name,id,MATH) # zip object 
print(list(my_data))

[('Ravi', 1, 30), ('Raju', 2, 40), ('Alex', 3, 50)]

print(set(my_data))

{('Alex', 3, 50), ('Ravi', 1, 30), ('Raju', 2, 40)}

print(tuple(my_data))

(('Ravi', 1, 30), ('Raju', 2, 40), ('Alex', 3, 50))

zip with different number of elements

name=['Ravi','Raju','Alex']
id=[1,2] 
MATH=[30,40,50]
my_data=zip(name,id,MATH)
print(list(my_data))

[('Ravi', 1, 30), ('Raju', 2, 40)]

name=['Ravi','Raju','Alex']
id=[1,2,3] 
MATH=[30,40,50]
my_data=zip(name,id,MATH)
name,id,mark=zip(*my_data)
print(name)
print(id)
print(mark)

('Ravi', 'Raju', 'Alex')
(1, 2, 3)
(30, 40, 50)

Example 1: Zipping Three or More Iterables

How to zip three or more iterables and handle uneven lengths?

names = ["Alice", "Bob", "Charlie"]
ages = [25, 30, 35]
cities = ["New York", "Los Angeles", "Chicago"]

# Zipping three lists together
zipped_data = zip(names, ages, cities)

# Display the zipped output
for item in zipped_data:
    print(item)

Output:

('Alice', 25, 'New York')
('Bob', 30, 'Los Angeles')
('Charlie', 35, 'Chicago')

Example 2: Unzipping to Multiple Lists

We can include an example that demonstrates unzipping back into individual lists, especially useful for reorganizing data.

zipped_data = [('Alice', 25, 'New York'), ('Bob', 30, 'Los Angeles'), ('Charlie', 35, 'Chicago')]

# Unzipping
names, ages, cities = zip(*zipped_data)

print("Names:", names)
print("Ages:", ages)
print("Cities:", cities)

Output:

Names: ('Alice', 'Bob', 'Charlie')
Ages: (25, 30, 35)
Cities: ('New York', 'Los Angeles', 'Chicago')

Example 3: Using Zip with Dictionaries

Demonstrating how to use zip() with dictionaries can expand its applicability in real-world tasks.

keys = ["name", "age", "city"]
values = ["Alice", 25, "New York"]

# Creating a dictionary using zip
person = dict(zip(keys, values))

print(person)

Output:

{'name': 'Alice', 'age': 25, 'city': 'New York'}

Example 4: Handling Uneven Length Iterables with zip_longest

When working with iterables of unequal lengths, the itertools.zip_longest function provides a way to fill missing values with a default.

from itertools import zip_longest

names = ["Alice", "Bob"]
ages = [25, 30, 35]

# Using zip_longest
zipped_data = zip_longest(names, ages, fillvalue="N/A")

# Display the zipped output
for item in zipped_data:
    print(item)

Output:

('Alice', 25)
('Bob', 30)
('N/A', 35)

Use Cases of zip() and unzip()

• Data Grouping: Combine related data into tuples for easier manipulation.
• Parallel Iteration: Iterate over multiple iterables simultaneously.
• Data Rearrangement: Unzip data for separate processing of grouped information.
• Dictionary Construction: Quickly create dictionaries from two related lists.
• Handling Missing Data: Use zip_longest to manage uneven lists.

Advanced Example: Parallel Iteration and Conditional Filtering

We can demonstrate how to use zip() for parallel iteration with conditional filtering:

names = ["Alice", "Bob", "Charlie"]
ages = [25, 30, 35]
cities = ["New York", "Los Angeles", "Chicago"]

# Parallel iteration with filtering
filtered_data = [(name, age, city) for name, age, city in zip(names, ages, cities) if age > 28]

print("Filtered Data:", filtered_data)

Output:

Filtered Data: [('Bob', 30, 'Los Angeles'), ('Charlie', 35, 'Chicago')]

Subhendu Mohapatra

Author & Instructor at plus2net

I write and maintain practical tutorials on Python, PHP, SQL, JavaScript, HTML, jQuery, and web development at plus2net. The tutorials focus on clear explanations, working examples, and code that readers can test and adapt while learning.

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