Other than some generic containers like list, Python in its definition can also handle containers with specified data types. Array can be handled in python by module named “array“. They can be useful when we have to manipulate only a specific data type values.
Arrays In Python | Python Array Operations | EdurekaEdureka!
** Python Certification Training: https://www.edureka.co/python **
This Edureka PPT on 'Arrays in Python' will help you establish a strong hold on all the fundamentals in the Python programming language. Below are the topics covered in this PPT:
What is an array?
Is python list same as an array?
How to create arrays in python?
Accessing array elements
Basic array operations
- Finding the length of an array
- Adding Elements
- Removing elements
- Array concatenation
- Slicing
- Looping
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This presentation is all about various built in
datastructures which we have in python.
List
Dictionary
Tuple
Set
and various methods present in each data structure
Other than some generic containers like list, Python in its definition can also handle containers with specified data types. Array can be handled in python by module named “array“. They can be useful when we have to manipulate only a specific data type values.
Arrays In Python | Python Array Operations | EdurekaEdureka!
** Python Certification Training: https://www.edureka.co/python **
This Edureka PPT on 'Arrays in Python' will help you establish a strong hold on all the fundamentals in the Python programming language. Below are the topics covered in this PPT:
What is an array?
Is python list same as an array?
How to create arrays in python?
Accessing array elements
Basic array operations
- Finding the length of an array
- Adding Elements
- Removing elements
- Array concatenation
- Slicing
- Looping
Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
This presentation is all about various built in
datastructures which we have in python.
List
Dictionary
Tuple
Set
and various methods present in each data structure
OOPS concepts are one of the most important concepts in high level languages. Here in this PPT we will learn more about Object oriented approach in python programming which includes details related to classes and objects, inheritance, dat abstraction, polymorphism and many more with examples and code.
Array
Introduction
One-dimensional array
Multidimensional array
Advantage of Array
Write a C program using arrays that produces the multiplication of two matrices.
String literals in python are surrounded by either single quotation marks, or double quotation marks. Strings can be output to screen using the print function. For example: print("hello"). Like many other popular programming languages, strings in Python are arrays of bytes representing unicode characters.
OOPS concepts are one of the most important concepts in high level languages. Here in this PPT we will learn more about Object oriented approach in python programming which includes details related to classes and objects, inheritance, dat abstraction, polymorphism and many more with examples and code.
Array
Introduction
One-dimensional array
Multidimensional array
Advantage of Array
Write a C program using arrays that produces the multiplication of two matrices.
String literals in python are surrounded by either single quotation marks, or double quotation marks. Strings can be output to screen using the print function. For example: print("hello"). Like many other popular programming languages, strings in Python are arrays of bytes representing unicode characters.
C Programming : Arrays, One Dimensional Arrays, Two Dimensional Arrays, Three Dimensional Arrays, Operations on Arrays like Insertion, Deletion, Searching, Sorting, Merging, Traversing, Matrix Manipulation like Addition, Multiplication etc. : Visit us at : www.rozyph.com
Using various data structures: Using Arrays (One Dimensional, Two Dimensional,
Jagged), Array.
ArrayList classes
Using Collections: Collection, HashTable, List, Stack, Queue, HashSet classes.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
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I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
2. What Is Array?
• An array is an mutable object which store a collection of values of
same data type under a single reference.
• An array store only homogeneous data type.
• Python's array is dynamic array.
• In Python we need declaration of array before use it in program.
• 'array' module must be imported for handling array in Python.
3. Advantages Of Array
I. Performance: For huge number of elements array take less memory
spaces and execution time also faster if compare with list.
II. Dynamic: Array's size is not fixed, so we can increase or decrease its
size at run time.
III. array module: Python provide 'array' module which contain
different methods, classes, objects to process array very easily.
4. Array vs. List
Topic Array List
Type of data structure
It is not built - in. We need
import 'array' module
before using array.
It is built - in. There are no
need to import any extra
module or package.
Necessity of declaration
Requires specific function
to declare an array.
No requirement of specific
function to declare a list.
Data type
Support only
homogeneous type.
Always support different
types of data in a list.
5. Array vs. List
Topic Array List
Handling large data
Store data very compact
way, so array more
efficient to handle large
data.
It is not so much efficient
to handle large data.
Numerical operations
Arryas are efficient for
various types of numerical
operations.
Lists can not handle
numerical operations
directly.
6. 'array' Module
• If you working with array you need to import 'array' module.
• According to Python documentation “This module defines an object
type which can compactly represent an array of basic values:
characters, integers, floating point numbers.”
• Import array module as following way:
>>> import array
7. Declaring Array
• The syntax of array declaration is:
• 'array_name' is an identifier, which store reference of array object.
• 'array.array( )' first array represent 'array' module and second array
represent array class which resides in 'array' module.
• 'type_code' represent the data type of array's elements.
• '[ elements ]' represent list of values which we want to store in array.
array_name = array.array( type_code, [ elements ] )
8. List Of 'type_code'
type_code Data type Minimum size in
bytes
'b' Signed integer 1
'B' Unsigned integer 1
'i' Signed integer 2
'I' Unsigned integer 2
'l' Signed integer 4
'L' Unsigned integer 4
9. List Of 'type_code'
type_code Data type Minimum size in
bytes
'f' Floating point 4
'd' Double precision
floating point
8
'u' Unicode character 2
10. Array Declaration Example
>>> import array
>>> my_array = array.array( 'i', [ 5, 7, 11, 14 ] )
>>> for i in my_array:
print( i )
5
7
11
14
11. Programming Example
• A program to create an array to store the characters of word
'Welcome' and display all characters.
>>> import array
>>> my_array = array.array( 'u', [ 'W', 'e', 'l', 'c', 'o', 'm', 'e' ] )
>>> for i in my_array:
print( i )
W m
e e
l
c
o
12. Different Ways Of Importing Array Module
• Import array module with an alias or alternate name as below:
• Here 'arr' is an alias name of imported module.
• For example:
>>> import array as arr
>>> my_array = arr.array( 'i', [ 5, 7, 11, 14 ] )
>>> import array as arr
13. Different Ways Of Importing Array Module
• Second way of importing 'array' module is below:
• Here '*' means all. That means we import all things such as classes,
objects, variables etc. of array module in our program.
• For example:
>>> from array import *
>>> my_array = array( 'i', [ 5, 7, 11, 14 ] )
>>> from array import *
14. Indexing On Arrays
• An index represent position value of an element in an array.
• Array index always start from 0.
• For example:
>>> from array import *
>>> x = array( 'i', [ 5, 7, 11, 14 ] )
>>> print( x[ 2 ] )
11
5 7 11 14
x[ 0 ] x[ 1 ] x[ 2 ] x[ 3 ]
15. Accessing Array Using Index
- By for loop
from array import *
a = array( 'i', [ 34, 56,-12, 44 ] )
n = len( a )
for i in range( n ):
print( a[ i ], 't', end = ' ' )
34 56 -12 44
16. Accessing Array Using Index
- By while loop
from array import *
a = array( 'i', [ 34, 56,-12, 44 ] )
n = len( a )
i = 0
while i < n:
print( a[ i ], 't', end = ' ' )
i += 1
34 56 -12 44
17. Slicing On Array
• By slicing operation we can retrive a piece of array out of an array.
• The syntax of slicing is:
• For example:
array_name[ start: stop: stride ]
>>> x = array( 'i', [ 10, 20, 30, 40, 50, 60, 70, 80, 90 ] )
>>> print( x[ 1: 4 ] )
array('i', [20, 30, 40])
>>> print( x[ 1: : 2 ] )
array('i', [20, 40, 60, 80])
19. Programming Example
• A program to calculate sum of a range of elements in an array.
from array import *
x = array( 'i', [ 10, 20, 30, 40, 50, 60, 70, 80, 90 ] )
sum = 0
for i in x[ 2: 5 ]:
sum = sum + i
print( sum )