Jack Downson

Jack Downson

1566450470

Python Zip Example | Python Zip() Function Tutorial

The zip() function is used to map the same indexes of more than one iterable. Mapping these indexes will generate a zip object.

How zip function works?

The zip function pairs the first elements of each iterator together then pairs the second elements together and so on.

If the iterables in the zip function are not the same length, then the smallest length iterable decides the length of the generated output.

Syntax:

zip(iterable0, iterable1, interable2, …)

Iterables can be Python lists, dictionary, strings, or any iterable object.

In the syntax above, the iterable0, iterable1, etc. are the iterator objects that we need to join using the zip function.

Example:

Consider the following snippet, where we have three iterables and the zip function joins them together.

x = ("Joey", "Monica", "Ross")
 
y = ("Chandler", "Pheobe")
 
z = ("David", "Rachel", "Courtney")
 
result = zip(x, y, z)
 
print(result)
 
print(tuple(result))

Output:

(('Joey', 'Chandler', 'David'), ('Monica', 'Pheobe', 'Rachel'))

In the above example, we defined three iterators of different lengths. The first elements of all of them are joined together, similarly, the second elements of all of them are joined together.

But there is no third element in the iterator y, therefore, the third elements of remaining iterators are not included in the output object.

This is why we said before that the length of the output is determined by the length of the smallest iterator which is 2 in this case.

The tuple() function converts the zip object to a tuple.

If no parameters are passed to the function, an empty iterable will be generated. For example, the result of print(tuple(zip())) will be ():

Convert two lists to a dictionary

To convert two lists to a dictionary using the zip function, you will join the lists using the zip function as we did, then you can convert them to a dictionary.

Suppose we have two lists as follows:

coin = ('Bitcoin', 'Ether', 'Ripple', 'Litecoin')
 
code = ('BTC', 'ETH', 'XRP', 'LTC')

So we will zip the list and then use the dict() function to convert it to a dictionary:

dict(zip(coin, code))

The output will be:

{'Bitcoin': 'BTC', 'Ether': 'ETH', 'Ripple': 'XRP', 'Litecoin': 'LTC'}

Zip function on three/multiple lists

You can pass multiple iterables to the zip function of same or different types. In the following example, we defined three lists (all are of the same length) but the data type of the items in each list is different.

Example:

list_a = ['Bitcoin', 'Ethereum', 'Ripple', 'Litecoin', 'Bitcoin-cash']
 
list_b = ['BTC', 'ETH', 'XRP', 'LTC', 'BCH']
 
list_c = ['11605', '271', '0.335', '102', '347']
 
result = zip(list_a, list_b, list_c)
 
print(tuple(result))

Output:

(('Bitcoin', 'BTC', '11605'), ('Ethereum', 'ETH', '271'), ('Ripple', 'XRP', '0.335'), ('Litecoin', 'LTC', '102'), ('Bitcoin-cash', 'BCH', '347'))

Similarly, we can join more than three iterables using the zip() function the same way.

Zip different length lists

When the arguments in the zip() function are different in length, the output object length will equal the length of the shortest input list.

Consider the following example to get a clearer view:

Example:

list_a = [1, 2, 3, 4, 5]
 
list_b = ['one', 'two', 'three']
 
result = zip(list_a, list_b)
 
print(tuple(result))

Output:

((1, 'one'), (2, 'two'), (3, 'three'))

In this example, list_a has 5 elements and list_b has 3 elements. The iterator will stop when it reaches the third element. Therefore, we have 3 tuples in the output tuple.

 

Zip function asterisk (Unzip)

The asterisk in a zip() function converts the elements of the iterable into separate elements. For example: if a = [a1, a2, a3] then zip(*a) equals to ((‘a’, ‘a’, ‘a’), (‘1’, ‘2’, ‘3’)).

In other words, we can say the asterisk in the zip function unzips the given iterable. That’s why the elements in list “a” are unzipped or extracted.

Consider the following example:

Example:

a = ['a1', 'a2', 'a3']
 
r = zip(*a)
 
print(tuple(r))

Output:

(('a', 'a', 'a'), ('1', '2', '3'))

Zip a matrix

A matrix is a multidimensional array of mn*, where m represents the number of rows and n represents the number of columns.

In Python, we can use the zip function to find the transpose of the matrix. The first step is to unzip the matrix using the * operator and finally zip it again as in the following example:

mat = [[1,2,3], [4,5,6]]
 
trans_mat = zip(*mat)
 
print(tuple(trans_mat))

Output:

((1, 4), (2, 5), (3, 6))

In this example, the matrix is a 2*3 matrix meaning that it has 2 rows and 3 columns. On taking the transpose of the matrix, there will be 3 rows and 2 columns.

Similarly, if we have 1 row and 3 columns in a matrix as:

[[1, 2, 3]]

On taking the transpose, we should have 3 rows and 1 column. Consider the following snippet:

Example:

mat = [[1,2,3]]
 
trans_mat = zip(*mat)
 
print(tuple(trans_mat))

Output:

((1,), (2,), (3,))

Iterate through two lists in parallel

We can also iterate through two lists simultaneously using the zip function. This is demonstrated in the following line of code:

Example:

list_1 = ['Numpy', 'asyncio', 'cmath', 'enum', 'ftplib']
 
list_2 = ['C', 'C++', 'Java', 'Python']
 
for i, j in zip(list_1, list_2):
 
    print(i, j)

Output:

Numpy C
 
asyncio C++
 
cmath Java
 
enum Python

In the above example, we have two different lists. The for loop uses two iterative variables to iterate through the lists that are zipped together to work in parallel.

 

Zip a list of floats

The zip function also works on floating-point numbers. The floating-point numbers contain decimal point like 10.3, 14.44, etc.

In this section, we will create an example where zip function iterates through a list of floats:

>>> float_list1 = [12.3, 10.99, 3.33, 2.97]
 
>>> float_list2 = [78.13, 0.89, 4.6, 0.7]
 
>>> float_zip = zip(float_list1, float_list2)
 
>>> print(tuple(float_zip))

Output:

((12.3, 78.13), (10.99, 0.89), (3.33, 4.6), (2.97, 0.7))

Pass a single iterable

If one iterable is passed in the arguments of zip() function, there would be one item in each tuple. This is demonstrated below:

Example:

list_1 = ['C', 'C++', 'Python', 'Java']
 
list_zip = zip(list_1)
 
print(tuple(list_zip))

Output

(('C',), ('C++',), ('Python',), ('Java',))

Output to a file

To save the output from the zip function into a file. Consider the following example:

The first step is to open a file (we will use the append mode so nothing of existing content will be deleted). Use the following line:

f = open("zipOutput.txt", "a+")

If the file doesn’t exist, it will be created.

Now let’s create two lists to zip together.

list_1 = ['C', 'C++', 'Python', 'Java']
 
list_2 = ['Solidity', 'Android', 'Php', 'Kotlin']

Finally, use the for loop to iterate through lists in zip function and write the result in the file (after converting a tuple to string):

for i in zip(list_1, list_2):
 
    f.write(str(i))

Now close the file and check the saved data.

f.close()

The following will be the contents of the file:

Also, there is a shorter code instead of using the for loop. We can convert the zip object to a tuple then to a string and write the string to the file:

f.write(str(tuple(zip(list_1,list_2))))

It will lead to the same result.

Working with zip function in Python is pretty neat and easy. The idea is about merging iterables together which comes handy in many cases. I hope you find the tutorial useful.

Keep coming back.

Further reading:

Building a Blockchain with Python - Full

Web Scraping with Python

What is TensorFrames? TensorFlow + Apache Spark

How to Make a Discord Bot in Python

WebScraping With Python, Beautiful Soup, and Urllib3

How to Build an E-commerce Website with Django and Python

Seaborn Heatmap Tutorial (Python Data Visualization)

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Python Zip Example | Python Zip() Function Tutorial
Ray  Patel

Ray Patel

1619510796

Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Ray  Patel

Ray Patel

1619518440

top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

#python #python hacks tricks #python learning tips #python programming tricks #python tips #python tips and tricks #python tips and tricks advanced #python tips and tricks for beginners #python tips tricks and techniques #python tutorial #tips and tricks in python #tips to learn python #top 30 python tips and tricks for beginners

Shardul Bhatt

Shardul Bhatt

1626775355

Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas. 

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities. 

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly. 

5 Reasons to Utilize Python for Programming Web Apps 

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks 

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions. 

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events. 

Simple to read and compose 

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building. 

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties. 

Utilized by the best 

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player. 

Massive community support 

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions. 

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking. 

Progressive applications 

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.

Summary

Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential. 

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

#python development services #python development company #python app development #python development #python in web development #python software development

Art  Lind

Art Lind

1602968400

Python Tricks Every Developer Should Know

Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?

In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.

Let’s get started

Swapping value in Python

Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead

>>> FirstName = "kalebu"
>>> LastName = "Jordan"
>>> FirstName, LastName = LastName, FirstName 
>>> print(FirstName, LastName)
('Jordan', 'kalebu')

#python #python-programming #python3 #python-tutorials #learn-python #python-tips #python-skills #python-development

Art  Lind

Art Lind

1602666000

How to Remove all Duplicate Files on your Drive via Python

Today you’re going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates.

Intro

In many situations you may find yourself having duplicates files on your disk and but when it comes to tracking and checking them manually it can tedious.

Heres a solution

Instead of tracking throughout your disk to see if there is a duplicate, you can automate the process using coding, by writing a program to recursively track through the disk and remove all the found duplicates and that’s what this article is about.

But How do we do it?

If we were to read the whole file and then compare it to the rest of the files recursively through the given directory it will take a very long time, then how do we do it?

The answer is hashing, with hashing can generate a given string of letters and numbers which act as the identity of a given file and if we find any other file with the same identity we gonna delete it.

There’s a variety of hashing algorithms out there such as

  • md5
  • sha1
  • sha224, sha256, sha384 and sha512

#python-programming #python-tutorials #learn-python #python-project #python3 #python #python-skills #python-tips