This article covers ‘for’ loops and how they are used with tuples. Even if the tuples are immutable, the accessibility of the tuples is similar to that of the list.
For Loop With Tuples
This article covers ‘for’ loops and how they are used with tuples. Even if the tuples are immutable, the accessibility of the tuples is similar to that of the list. Traverse through a tuple with a for loop.
Python
Python
Python
tuples=()
tuples=(1,'user@gmail.com',5.2,'User',True)
for i in tuples:
print(i)
Output
1
user@gmail.com
5.2
User
TrueUse enumerate with tuple to get index and value.
Python
Python
Python
for i,j in enumerate(tuples):
print(i,j)
Output
0 1
1 user@gmail.com
2 5.2
3 User
4 TrueTo get this output without enumerating, we have to change codes as follows.
Python
Python
Python
size=len(tuples)
# i will be used as index pointer here,
for i in range(size):
print(i,tuples[i])
Output
0 1
1 user@gmail.com
2 5.2
3 User
4 TrueNested Tuples
Let’s create a pseudo-dataset within a nested structure, a tuple. If we print it directly, it will not show up in table format.
Python
Python
Python
ntuple=(
('id','sal','name','email','married'),
(1,5.2,'User1','user1@gmail.com',True),
(2,4.8,'User2','user2@gmail.com',True),
(3,6.3,'User3','user3@gmail.com',True)
)
print(ntuple)
Output
(('id', 'sal', 'name', 'email', 'married'), (1, 5.2, 'User1', 'user1@gmail.com', True), (2, 4.8, 'User2', 'user2@gmail.com', True), (3, 6.3, 'User3', 'user3@gmail.com', True))Let’s print the nested tuple in table format.
Python
Python
Python
for i in ntuple:
for j in i:
print(j,end=' \t ')
print()
Output
id sal name email married
1 5.2 User1 user1@gmail.com True
2 4.8 User2 user2@gmail.com True
3 6.3 User3 user3@gmail.com True Tuple Unpacking
We will use the same tuple to demonstrate the tuple unpacking.
Python
Python
Python
ntuple=(
('id','sal','name','email','married'),
(1,5.2,'User1','user1@gmail.com',True),
(2,4.8,'User2','user2@gmail.com',True),
(3,6.3,'User3','user3@gmail.com',True)
)
print(ntuple)
Output
(('id', 'sal', 'name', 'email', 'married'), (1, 5.2, 'User1', 'user1@gmail.com', True), (2, 4.8, 'User2', 'user2@gmail.com', True), (3, 6.3, 'User3', 'user3@gmail.com', True))Let’s try to unpack a tuple without any special method. Let’s use for loop to unpack tuple.
Python
Python
Python
for i in ntuple:
j,k,l,m,n=i
print(j,k,l,m,n)
Output
id sal name email married
1 5.2 User1 user1@gmail.com True
2 4.8 User2 user2@gmail.com True
3 6.3 User3 user3@gmail.com True Python
Python
Python
i,*j=ntuple
print(i,j,sep='\n')
Output
('id', 'sal', 'name', 'email', 'married')
[(1, 5.2, 'User1', 'user1@gmail.com', True), (2, 4.8, 'User2', 'user2@gmail.com', True), (3, 6.3, 'User3', 'user3@gmail.com', True)]This is how a tuple is unpacked without a for loop.
Python
Python
Python
i,j,*k=ntuple
print(i,j,k,sep='\n')
Output
('id', 'sal', 'name', 'email', 'married')
(1, 5.2, 'User1', 'user1@gmail.com', True)
[(2, 4.8, 'User2', 'user2@gmail.com', True), (3, 6.3, 'User3', 'user3@gmail.com', True)]Practice Your codes here
ntuple=(
(‘id’,’sal’,’name’,’email’,’married’),
(1,5.2,’User1′,’user1@gmail.com’,True),
(2,4.8,’User2′,’user2@gmail.com’,True),
(3,6.3,’User3′,’user3@gmail.com’,True)
)
print(ntuple)
i,j,*k=ntuple
print(i,j,k,sep=’\n’)
ANCOVA: Analysis of Covariance with python
ANCOVA is an extension of ANOVA (Analysis of Variance) that combines blocks of regression analysis and ANOVA. Which makes it Analysis of Covariance.
Learn Python The Fun Way
What if we learn topics in a desirable way!! What if we learn to write Python codes from gamers data !!
Meet the most efficient and intelligent AI assistant : NotebookLM
Start using NotebookLM today and embark on a smarter, more efficient learning journey!
Break the ice
This can be a super guide for you to start and excel in your data science career.
ANOVA (Analysis of Variance ) part 1
A method to find a statistical relationship between two variables in a dataset where one variable is used to group data.
Basic plots with Seaborn
Seaborn library has matplotlib at its core for data point visualizations. This library gives highly statistical informative graphics functionality to Seaborn.
Matplotlib in python
The Matplotlib library helps you create static and dynamic visualisations. Dynamic visualizations that are animated and interactive. This library makes it easy to plot data and create graphs.
Plotly with Python and R
This library is named Plotly after the company of the same name. Plotly provides visualization libraries for Python, R, MATLAB, Perl, Julia, Arduino, and REST.
Numpy Array
Numpy array have functions for matrices ,linear algebra ,Fourier Transform. Numpy arrays provide 50x more speed than a python list.
NumPy: Python’s Mathematical Backbone
Numpy has created a vast ecosystem spanning numerous fields of science.
Introduction to Pandas: A Guide
Pandas is a easy to use data analysis and manipulation tool. Pandas provides functionality for categorical,ordinal, and time series data . Panda provides fast and powerful calculations for data analysis.
Pandas Dataframe in brief
In this tutorial, you will learn How to Access The Data in Various Ways From the dataframe.
Exploring the World of Sets in Python
Understand one of the important data types in Python. Each item in a set is distinct. Sets can store multiple items of various types of data.
A Beginner’s Guide to Immutable Tuples
Tuples are a sequence of Python objects. A tuple is created by separating items with a comma. They are put inside the parenthesis “”(“” , “”)””.
Points You Earned
0 distinction_points
python_points 0
0 Solver points
Leave a Reply
You must be logged in to post a comment.