This document discusses different types of operators in Python programming. It defines operators as symbols that represent operations that can be performed on operands or values. The main types of operators covered are: arithmetic operators for mathematical operations, relational operators for comparisons, logical operators for Boolean logic, assignment operators for assigning values, and special operators like identity and membership. Examples are provided to demonstrate the usage of each operator type.
Variables & Data Types In Python | EdurekaEdureka!
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This Edureka PPT on 'Variables and Data Types in Python' will help you establish a foothold on Python by helping you learn basic concepts like variables and data types. Below are the topics covered in this PPT:
Introduction To Python
Applications Of Python
Variable Declaration
Variable Data Types
Type Conversion
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This document provides an overview of cartography and mapmaking. It discusses that cartography is the art and science of mapmaking, and that maps have existed for thousands of years. The key stages of mapmaking are collecting and organizing data, designing the map, and reproducing it. Different types of maps exist for various purposes, using symbols and projections to represent geographic information on a flat surface. Technological advances have moved mapmaking from hand-drawn to digital, but the goals of effective communication and accurate representation remain the same.
Python provides numerous built-in functions that are readily available to us at the Python prompt. Some of the functions like input() and print() are widely used for standard input and output operations respectively.
- Python is a high-level programming language created by Guido van Rossum in 1991.
- It is an interpreted language that is dynamically typed and supports multiple programming paradigms like object-oriented, imperative and functional programming.
- Python code is highly readable and it is commonly used for scripting, web development, data analysis and artificial intelligence projects.
Foreign direct investment (FDI) refers to cross-border investment by a company or individual in business interests located in another country. FDI plays an important role in India's economic development by providing capital, jobs, technology and boosting growth. While India receives around 25% of China's FDI, various sectors like infrastructure, automotive, airlines and textiles have seen increased FDI inflows in recent years due to government reforms. FDI can benefit India through infrastructure development, increased competition and technology advancement.
When Covid-19 outbreak In across the world. Everybody stay at their home, its effects so much in education then the term Digital Literacy or Media literacy is arrived and its try's to fullfill the need of Education.
This document discusses research ethics from an Islamic perspective. It begins by defining ethics and exploring ethics in Islam's history. It then discusses ethics in different aspects of research, including objectives of research ethics, ethics that should be followed at different research stages, and ethical issues like informed consent, privacy, and deception. The document also examines sources of tension in research ethics between principles like beneficence and human dignity. It outlines researchers' responsibilities to participants and the research community, such as protecting safety, reputation and enabling further research. The conclusion emphasizes the importance of awareness and understanding of ethical issues in research.
Modules allow grouping of related functions and code into reusable files. Packages are groups of modules that provide related functionality. There are several ways to import modules and their contents using import and from statements. The document provides examples of creating modules and packages in Python and importing from them.
The document discusses lists in Python, including how to create, access, modify, loop through, slice, sort, and perform other operations on list elements. Lists can contain elements of different data types, are indexed starting at 0, and support methods like append(), insert(), pop(), and more to manipulate the list. Examples are provided to demonstrate common list operations and functions.
This document discusses Python arrays. Some key points:
1) An array is a mutable object that stores a collection of values of the same data type. It stores homogeneous data and its size can be increased or decreased dynamically.
2) The array module provides various methods and classes to easily process arrays. Arrays are more memory and computationally efficient than lists for large amounts of data.
3) Arrays only allow homogeneous data types while lists can contain different data types. Arrays must be declared before use while lists do not require declaration.
The document discusses strings in Python. It describes that strings are immutable sequences of characters that can contain letters, numbers and special characters. It covers built-in string functions like len(), max(), min() for getting the length, maximum and minimum character. It also discusses string slicing, concatenation, formatting, comparison and various string methods for operations like conversion, formatting, searching and stripping whitespace.
All data values in Python are encapsulated in relevant object classes. Everything in Python is an object and every object has an identity, a type, and a value. Like another object-oriented language such as Java or C++, there are several data types which are built into Python. Extension modules which are written in C, Java, or other languages can define additional types.
To determine a variable's type in Python you can use the type() function. The value of some objects can be changed. Objects whose value can be changed are called mutable and objects whose value is unchangeable (once they are created) are called immutable.
1. Inheritance is a mechanism where a new class is derived from an existing class, known as the base or parent class. The derived class inherits properties and methods from the parent class.
2. There are 5 types of inheritance: single, multilevel, multiple, hierarchical, and hybrid. Multiple inheritance allows a class to inherit from more than one parent class.
3. Overriding allows a subclass to replace or extend a method defined in the parent class, while still calling the parent method using the super() function or parent class name. This allows the subclass to provide a specific implementation of a method.
The document discusses various Python flow control statements including if/else, for loops, while loops, break and continue. It provides examples of using if/else statements for decision making and checking conditions. It also demonstrates how to use for and while loops for iteration, including using the range function. It explains how break and continue can be used to terminate or skip iterations. Finally, it briefly mentions pass, for, while loops with else blocks, and nested loops.
Exception handling in Python allows programmers to handle errors and exceptions that occur during runtime. The try/except block handles exceptions, with code in the try block executing normally and code in the except block executing if an exception occurs. Finally blocks ensure code is always executed after a try/except block. Programmers can define custom exceptions and raise exceptions using the raise statement.
The document discusses data structures and lists in Python. It begins by defining data structures as a way to organize and store data for efficient access and modification. It then covers the different types of data structures, including primitive structures like integers and strings, and non-primitive structures like lists, tuples, and dictionaries. A large portion of the document focuses on lists in Python, describing how to perform common list manipulations like adding and removing elements using various methods. These methods include append(), insert(), remove(), pop(), and clear(). The document also discusses accessing list elements and other list operations such as sorting, counting, and reversing.
This document discusses Python variables and data types. It defines what a Python variable is and explains variable naming rules. The main Python data types are numbers, strings, lists, tuples, dictionaries, booleans, and sets. Numbers can be integer, float or complex values. Strings are sequences of characters. Lists are mutable sequences that can hold elements of different data types. Tuples are immutable sequences. Dictionaries contain key-value pairs with unique keys. Booleans represent True and False values. Sets are unordered collections of unique elements. Examples are provided to demonstrate how to declare variables and use each of the different data types in Python.
A class is a code template for creating objects. Objects have member variables and have behaviour associated with them. In python a class is created by the keyword class.
An object is created using the constructor of the class. This object will then be called the instance of the class.
This document discusses values, data types, and the five standard data types in Python. It defines that values are the fundamental things like numbers and strings that programs manipulate. Data type refers to the type and size of data that variables can hold. The five main data types in Python are numbers, strings, lists, tuples, and dictionaries. Numbers include integers, floating point values, and complex numbers. Lists and tuples are ordered sequences that can hold heterogeneous data, but lists are mutable while tuples are immutable. Strings are ordered sequences of characters. Dictionaries are unordered collections of key-value pairs.
The document discusses various concepts related to functions in Python including defining functions, passing arguments, default arguments, arbitrary argument lists, lambda expressions, function annotations, and documentation strings. Functions provide modularity and code reusability. Arguments can be passed by value or reference and default values are evaluated once. Keyword, arbitrary and unpacked arguments allow flexible calling. Lambda expressions define small anonymous functions. Annotations provide type metadata and docstrings document functions.
Functions allow programmers to organize code into reusable blocks. There are built-in functions and user-defined functions. Functions make code easier to develop, test and reuse. Variables inside functions can be local, global or nonlocal. Parameters pass data into functions, while functions can return values. Libraries contain pre-defined functions for tasks like mathematics and string manipulation.
This document provides an introduction to the Python programming language. It discusses Python's design philosophy emphasizing readability. It also covers printing messages, reading input, variables and data types, operators, and basic syntax like comments and identifiers. Arithmetic, relational, logical and bitwise operators are explained along with examples.
NumPy is a Python library that provides multidimensional array and matrix objects to perform scientific computing. It contains efficient functions for operations on arrays like arithmetic, aggregation, copying, indexing, slicing, and reshaping. NumPy arrays have advantages over native Python sequences like fixed size and efficient mathematical operations. Common NumPy operations include elementwise arithmetic, aggregation functions, copying and transposing arrays, changing array shapes, and indexing/slicing arrays.
The Input Statement in Core Python .pptxKavitha713564
The document discusses different ways to accept input from the user in Python programs. It explains the input(), raw_input(), and int() functions for accepting input as a string, integer, or other data type. It also covers using command line arguments with the sys module to access arguments passed when running a Python program from the terminal. The getopt and argparse modules provide additional functionality for parsing command line arguments in a program.
Modules allow grouping of related functions and code into reusable files. Packages are groups of modules that provide related functionality. There are several ways to import modules and their contents using import and from statements. The document provides examples of creating modules and packages in Python and importing from them.
The document discusses lists in Python, including how to create, access, modify, loop through, slice, sort, and perform other operations on list elements. Lists can contain elements of different data types, are indexed starting at 0, and support methods like append(), insert(), pop(), and more to manipulate the list. Examples are provided to demonstrate common list operations and functions.
This document discusses Python arrays. Some key points:
1) An array is a mutable object that stores a collection of values of the same data type. It stores homogeneous data and its size can be increased or decreased dynamically.
2) The array module provides various methods and classes to easily process arrays. Arrays are more memory and computationally efficient than lists for large amounts of data.
3) Arrays only allow homogeneous data types while lists can contain different data types. Arrays must be declared before use while lists do not require declaration.
The document discusses strings in Python. It describes that strings are immutable sequences of characters that can contain letters, numbers and special characters. It covers built-in string functions like len(), max(), min() for getting the length, maximum and minimum character. It also discusses string slicing, concatenation, formatting, comparison and various string methods for operations like conversion, formatting, searching and stripping whitespace.
All data values in Python are encapsulated in relevant object classes. Everything in Python is an object and every object has an identity, a type, and a value. Like another object-oriented language such as Java or C++, there are several data types which are built into Python. Extension modules which are written in C, Java, or other languages can define additional types.
To determine a variable's type in Python you can use the type() function. The value of some objects can be changed. Objects whose value can be changed are called mutable and objects whose value is unchangeable (once they are created) are called immutable.
1. Inheritance is a mechanism where a new class is derived from an existing class, known as the base or parent class. The derived class inherits properties and methods from the parent class.
2. There are 5 types of inheritance: single, multilevel, multiple, hierarchical, and hybrid. Multiple inheritance allows a class to inherit from more than one parent class.
3. Overriding allows a subclass to replace or extend a method defined in the parent class, while still calling the parent method using the super() function or parent class name. This allows the subclass to provide a specific implementation of a method.
The document discusses various Python flow control statements including if/else, for loops, while loops, break and continue. It provides examples of using if/else statements for decision making and checking conditions. It also demonstrates how to use for and while loops for iteration, including using the range function. It explains how break and continue can be used to terminate or skip iterations. Finally, it briefly mentions pass, for, while loops with else blocks, and nested loops.
Exception handling in Python allows programmers to handle errors and exceptions that occur during runtime. The try/except block handles exceptions, with code in the try block executing normally and code in the except block executing if an exception occurs. Finally blocks ensure code is always executed after a try/except block. Programmers can define custom exceptions and raise exceptions using the raise statement.
The document discusses data structures and lists in Python. It begins by defining data structures as a way to organize and store data for efficient access and modification. It then covers the different types of data structures, including primitive structures like integers and strings, and non-primitive structures like lists, tuples, and dictionaries. A large portion of the document focuses on lists in Python, describing how to perform common list manipulations like adding and removing elements using various methods. These methods include append(), insert(), remove(), pop(), and clear(). The document also discusses accessing list elements and other list operations such as sorting, counting, and reversing.
This document discusses Python variables and data types. It defines what a Python variable is and explains variable naming rules. The main Python data types are numbers, strings, lists, tuples, dictionaries, booleans, and sets. Numbers can be integer, float or complex values. Strings are sequences of characters. Lists are mutable sequences that can hold elements of different data types. Tuples are immutable sequences. Dictionaries contain key-value pairs with unique keys. Booleans represent True and False values. Sets are unordered collections of unique elements. Examples are provided to demonstrate how to declare variables and use each of the different data types in Python.
A class is a code template for creating objects. Objects have member variables and have behaviour associated with them. In python a class is created by the keyword class.
An object is created using the constructor of the class. This object will then be called the instance of the class.
This document discusses values, data types, and the five standard data types in Python. It defines that values are the fundamental things like numbers and strings that programs manipulate. Data type refers to the type and size of data that variables can hold. The five main data types in Python are numbers, strings, lists, tuples, and dictionaries. Numbers include integers, floating point values, and complex numbers. Lists and tuples are ordered sequences that can hold heterogeneous data, but lists are mutable while tuples are immutable. Strings are ordered sequences of characters. Dictionaries are unordered collections of key-value pairs.
The document discusses various concepts related to functions in Python including defining functions, passing arguments, default arguments, arbitrary argument lists, lambda expressions, function annotations, and documentation strings. Functions provide modularity and code reusability. Arguments can be passed by value or reference and default values are evaluated once. Keyword, arbitrary and unpacked arguments allow flexible calling. Lambda expressions define small anonymous functions. Annotations provide type metadata and docstrings document functions.
Functions allow programmers to organize code into reusable blocks. There are built-in functions and user-defined functions. Functions make code easier to develop, test and reuse. Variables inside functions can be local, global or nonlocal. Parameters pass data into functions, while functions can return values. Libraries contain pre-defined functions for tasks like mathematics and string manipulation.
This document provides an introduction to the Python programming language. It discusses Python's design philosophy emphasizing readability. It also covers printing messages, reading input, variables and data types, operators, and basic syntax like comments and identifiers. Arithmetic, relational, logical and bitwise operators are explained along with examples.
NumPy is a Python library that provides multidimensional array and matrix objects to perform scientific computing. It contains efficient functions for operations on arrays like arithmetic, aggregation, copying, indexing, slicing, and reshaping. NumPy arrays have advantages over native Python sequences like fixed size and efficient mathematical operations. Common NumPy operations include elementwise arithmetic, aggregation functions, copying and transposing arrays, changing array shapes, and indexing/slicing arrays.
The Input Statement in Core Python .pptxKavitha713564
The document discusses different ways to accept input from the user in Python programs. It explains the input(), raw_input(), and int() functions for accepting input as a string, integer, or other data type. It also covers using command line arguments with the sys module to access arguments passed when running a Python program from the terminal. The getopt and argparse modules provide additional functionality for parsing command line arguments in a program.
The document discusses Python input and output functions. It describes how the input() function allows user input and converts the input to a string by default. The print() function outputs data to the screen and allows formatting of output. The document also discusses importing modules to reuse code and functions from other files.
Functions allow programmers to organize code into reusable blocks to perform related actions. There are three types of functions: built-in functions, modules, and user-defined functions. Built-in functions like int(), float(), str(), and abs() are predefined to perform common tasks. Modules like the math module provide additional mathematical functions like ceil(), floor(), pow(), sqrt(), and trigonometric functions. User-defined functions are created by programmers to customize functionality.
Python is a high-level, general-purpose programming language that was created by Guido van Rossum in 1985. It is an interpreted, interactive, object-oriented language with features like dynamic typing and memory management. This document provides an overview of Python 3 and its basic syntax, data types, operators, decision making structures like if/else statements, and loops. It covers topics like variables, numbers, strings, lists, tuples, dictionaries, and type conversion between data types.
Python 3000 (Python 3.0) is an upcoming major release that will break backwards compatibility to fix early design mistakes and issues. It introduces many changes like Unicode as the default string type, a reworked I/O library, print as a function, and removal of some old features like classic classes. The document provides details on the changes and recommends projects support both Python 2.6 and 3.0 during the transition period.
The Ring programming language version 1.8 book - Part 94 of 202Mahmoud Samir Fayed
This document provides code examples for common GUI tasks in Ring using the Qt library:
1. It shows how to close a window and display another by connecting a button's click event to call the close() method on the first window and show() on the second.
2. It demonstrates how to create a modal window in Ring/Qt by setting the window modality to true and parent to the main window.
3. Methods like setWindowFlags() and removing the maximize flag can disable resizing and maximize buttons on a window.
The document discusses various C++ libraries including file streams, fstream, assert, math, and ctype libraries. It provides an overview of each library, describing what they are used for and giving examples of common functions. The fstream library is used for reading and writing files and defines ofstream, ifstream, and fstream classes. The assert library contains macros for testing assumptions, math contains mathematical functions, and ctype has functions for testing character properties.
The document summarizes Guido van Rossum's talk about Python 3000 (also known as Python 3.0) at PyCon in 2007. Some key points:
- Python 3.0 will be an incompatible major release that fixes early design mistakes in Python.
- Major changes include print becoming a function, dictionary views replacing key methods, default integer division rounding to a float, and strings becoming Unicode by default.
- The timeline targets completion of PEPs by April 2007 and a 3.0 final release in June 2008.
- Automatic tools can help convert most 2.x code to 3.x, but not cases depending on implementation details. Developers are encouraged to write portable code and add tests.
Python-04| Fundamental data types vs immutabilityMohd Sajjad
Fundamental data types like integers, floats, booleans and strings are immutable in Python. Immutable means the object cannot be changed once created. For integers from 0 to 256, Python reuses the same integer objects to save memory. It also reuses the two boolean objects for True and False. For strings, a new object is created each time due to the large number of possible string values. Floats and complexes are also immutable and do not reuse objects. Immutability helps improve performance and memory usage in Python.
After the end of lesson you will be able to learn Python basics-What Python is? Its releases. Where we can use Python? Python Features. Tokens, comments variables etc... In out next PPT you will learn how to input and get output in Python
Secure your folder with password/without any softwareMohd Sajjad
@ECHO OFF
if EXIST "Control Panel.{21EC2020-3AEA-1069-A2DD-08002B30309D}" goto UNLOCK
if NOT EXIST folder_name goto MDfolder_name
:CONFIRM
echo Are you sure to lock this folder? (Y/N)
set/p "cho=>"
if %cho%==Y goto LOCK
if %cho%==y goto LOCK
if %cho%==n goto END
if %cho%==N goto END
echo Invalid choice.
goto CONFIRM
:LOCK
ren folder_name "Control Panel.{21EC2020-3AEA-1069-A2DD-08002B30309D}"
attrib +h +s "Control Panel.{21EC2020-3AEA-1069-A2DD-08002B30309D}"
echo Folder locked
goto End
:UNLOCK
echo Enter password to Unlock Your Secure Folder
set/p "pass=>" folder_password
if NOT %pass%== folder_password goto FAIL
attrib -h -s "Control Panel.{21EC2020-3AEA-1069-A2DD-08002B30309D}"
ren "Control Panel.{21EC2020-3AEA-1069-A2DD-08002B30309D}" folder_name
echo Folder Unlocked successfully
goto End
:FAIL
echo Invalid password
goto end
:MDfolder_name
md folder_name
echo folder_name created successfully
goto End
:End
SNMP is an Internet standard protocol used for managing network devices running TCP/IP, using a manager-agent model where a manager monitors and controls agents running on devices. It uses three components - SNMP itself, SMI which standardizes object attributes, and MIB which defines the set of objects supported by each network device for SNMP management. There are three versions, with v1 having poor security and v2 improving on performance, security and confidentiality over v1.
pulse ppt.pptx Types of pulse , characteristics of pulse , Alteration of pulsesushreesangita003
what is pulse ?
Purpose
physiology and Regulation of pulse
Characteristics of pulse
factors affecting pulse
Sites of pulse
Alteration of pulse
for BSC Nursing 1st semester
for Gnm Nursing 1st year
Students .
vitalsign
CBSE - Grade 8 - Science - Chemistry - Metals and Non Metals - WorksheetSritoma Majumder
Introduction
All the materials around us are made up of elements. These elements can be broadly divided into two major groups:
Metals
Non-Metals
Each group has its own unique physical and chemical properties. Let's understand them one by one.
Physical Properties
1. Appearance
Metals: Shiny (lustrous). Example: gold, silver, copper.
Non-metals: Dull appearance (except iodine, which is shiny).
2. Hardness
Metals: Generally hard. Example: iron.
Non-metals: Usually soft (except diamond, a form of carbon, which is very hard).
3. State
Metals: Mostly solids at room temperature (except mercury, which is a liquid).
Non-metals: Can be solids, liquids, or gases. Example: oxygen (gas), bromine (liquid), sulphur (solid).
4. Malleability
Metals: Can be hammered into thin sheets (malleable).
Non-metals: Not malleable. They break when hammered (brittle).
5. Ductility
Metals: Can be drawn into wires (ductile).
Non-metals: Not ductile.
6. Conductivity
Metals: Good conductors of heat and electricity.
Non-metals: Poor conductors (except graphite, which is a good conductor).
7. Sonorous Nature
Metals: Produce a ringing sound when struck.
Non-metals: Do not produce sound.
Chemical Properties
1. Reaction with Oxygen
Metals react with oxygen to form metal oxides.
These metal oxides are usually basic.
Non-metals react with oxygen to form non-metallic oxides.
These oxides are usually acidic.
2. Reaction with Water
Metals:
Some react vigorously (e.g., sodium).
Some react slowly (e.g., iron).
Some do not react at all (e.g., gold, silver).
Non-metals: Generally do not react with water.
3. Reaction with Acids
Metals react with acids to produce salt and hydrogen gas.
Non-metals: Do not react with acids.
4. Reaction with Bases
Some non-metals react with bases to form salts, but this is rare.
Metals generally do not react with bases directly (except amphoteric metals like aluminum and zinc).
Displacement Reaction
More reactive metals can displace less reactive metals from their salt solutions.
Uses of Metals
Iron: Making machines, tools, and buildings.
Aluminum: Used in aircraft, utensils.
Copper: Electrical wires.
Gold and Silver: Jewelry.
Zinc: Coating iron to prevent rusting (galvanization).
Uses of Non-Metals
Oxygen: Breathing.
Nitrogen: Fertilizers.
Chlorine: Water purification.
Carbon: Fuel (coal), steel-making (coke).
Iodine: Medicines.
Alloys
An alloy is a mixture of metals or a metal with a non-metal.
Alloys have improved properties like strength, resistance to rusting.
Real GitHub Copilot Exam Dumps for SuccessMark Soia
Download updated GitHub Copilot exam dumps to boost your certification success. Get real exam questions and verified answers for guaranteed performance
Link your Lead Opportunities into Spreadsheet using odoo CRMCeline George
In Odoo 17 CRM, linking leads and opportunities to a spreadsheet can be done by exporting data or using Odoo’s built-in spreadsheet integration. To export, navigate to the CRM app, filter and select the relevant records, and then export the data in formats like CSV or XLSX, which can be opened in external spreadsheet tools such as Excel or Google Sheets.
Understanding P–N Junction Semiconductors: A Beginner’s GuideGS Virdi
Dive into the fundamentals of P–N junctions, the heart of every diode and semiconductor device. In this concise presentation, Dr. G.S. Virdi (Former Chief Scientist, CSIR-CEERI Pilani) covers:
What Is a P–N Junction? Learn how P-type and N-type materials join to create a diode.
Depletion Region & Biasing: See how forward and reverse bias shape the voltage–current behavior.
V–I Characteristics: Understand the curve that defines diode operation.
Real-World Uses: Discover common applications in rectifiers, signal clipping, and more.
Ideal for electronics students, hobbyists, and engineers seeking a clear, practical introduction to P–N junction semiconductors.
What makes space feel generous, and how architecture address this generosity in terms of atmosphere, metrics, and the implications of its scale? This edition of #Untagged explores these and other questions in its presentation of the 2024 edition of the Master in Collective Housing. The Master of Architecture in Collective Housing, MCH, is a postgraduate full-time international professional program of advanced architecture design in collective housing presented by Universidad Politécnica of Madrid (UPM) and Swiss Federal Institute of Technology (ETH).
Yearbook MCH 2024. Master in Advanced Studies in Collective Housing UPM - ETH
Odoo Inventory Rules and Routes v17 - Odoo SlidesCeline George
Odoo's inventory management system is highly flexible and powerful, allowing businesses to efficiently manage their stock operations through the use of Rules and Routes.
Geography Sem II Unit 1C Correlation of Geography with other school subjectsProfDrShaikhImran
The correlation of school subjects refers to the interconnectedness and mutual reinforcement between different academic disciplines. This concept highlights how knowledge and skills in one subject can support, enhance, or overlap with learning in another. Recognizing these correlations helps in creating a more holistic and meaningful educational experience.
GDGLSPGCOER - Git and GitHub Workshop.pptxazeenhodekar
This presentation covers the fundamentals of Git and version control in a practical, beginner-friendly way. Learn key commands, the Git data model, commit workflows, and how to collaborate effectively using Git — all explained with visuals, examples, and relatable humor.
How to Manage Opening & Closing Controls in Odoo 17 POSCeline George
In Odoo 17 Point of Sale, the opening and closing controls are key for cash management. At the start of a shift, cashiers log in and enter the starting cash amount, marking the beginning of financial tracking. Throughout the shift, every transaction is recorded, creating an audit trail.
K12 Tableau Tuesday - Algebra Equity and Access in Atlanta Public Schoolsdogden2
Algebra 1 is often described as a “gateway” class, a pivotal moment that can shape the rest of a student’s K–12 education. Early access is key: successfully completing Algebra 1 in middle school allows students to complete advanced math and science coursework in high school, which research shows lead to higher wages and lower rates of unemployment in adulthood.
Learn how The Atlanta Public Schools is using their data to create a more equitable enrollment in middle school Algebra classes.
K12 Tableau Tuesday - Algebra Equity and Access in Atlanta Public Schoolsdogden2
Python-02| Input, Output & Import
2. Python 2.7 offers two functions
a) raw_input()
b) input()
Python 3.x (latest release) the raw_input() has been
renamed as input() and the old input() function (of
release 2.x) has been removed.
3. The raw_input() is used as:
variable = raw_input(<statement>)
For example:
name = raw_input(‘What is your name’)
The data you type will be save to variable ‘name’
The raw_input() always returns a string type. In above example the python
interpreter returns the value of age(i.e., 18) in string type.
See the next slide to clear this concept.
4. Python through an error, as Python cannot add integer to a
string.
It received 12 through raw_input() as a string.
We required to use typecasting functions with
raw_input()/input() [of python 3.x]
5. •Python offers two function int() and float() to convert the value in
integer and float type.
•bool() can also be used to get data in true/false
6. Python will through an error if you entered string type using raw_input() inside
int() or float()
7. This input() function works only in Python 2.x.
It does not supported by Python 3.x although Python uses
input() but actually it is raw_input() renamed as input().
The input() returns value accordingly i.e., whatever type we
provide the same will be considered.
It doesn’t require type casting.
On some installation it doesn’t work properly and raise error thus it should be
avoided and raw_input() should be used.
8. In Python 3.x, this input() has been removed and uses
raw_input() which has been renamed as input().
Input() function in Python 3.x should require typecasting
as it also generate data in string type by default.
9. To take input from user we took two input function and two lines. What
if we want this process in one single line? See next slide for answer
This is multiple input in one line. What if I want to use only one input()
function to take multiple inputs?
10. For this we use split() function
a, b = input(“Enter first and last name”).split()
Note in Python code,
both a and b would be
of string.
We can convert them
to int using
a, b = [int(a), int(b)]
We can also use list
comprehension, will discuss in
next slide
11. a, b = [int(x) for x in input(“Enter two number:”).split()]
split() is a function/method used to split the input() function
into multiple values.
The method split() returns a list of all the words in the string.
split() is opposite of concatenation which combines strings
into one.
List of multiple values
12. Note in the output window, user enter 3 values separated by spaces.
By default i.e., if no separator is defined in split() , space will be used
by default.
13. Input(“Enter two number”)
10 20
This will considered as one string but split() divide this string
into two with respect to space between them
10 | 20
14. Separated by
comma
Python will through error if not
separated by comma
Separation can be done using any of the other argument
split(“:”), split(“s”), split(“5”), split(“#”)
16. Python uses print() function to produce output.
print “Hello”
print 5
print ‘hello’
print (“Hello world”)
print (5)
print (“sum of 2 & 3 is”, 2+3)
Example of Python 2.x
Example of Python 3.x
17. print() :- without argument print() function prints a
blank line.
Line separator
19. What is the difference between
print(“Hello”+ “World”) and
print(“Hello” , “World”)
No Space
with Space
First argument Second argument
print() function insert spaces between items automatically.
20. If we don’t want a space as separator between
arguments then we can use sep attribute
Space is added automatically
between the arguments. This is by
default, we can change it and will
show you on next slide.
By default sep = ‘ ’
21. It appends a newline automatically
In Python 2.x, it appends a newline unless the
statement ends in a comma.
a, b = 10, 20 a, b = 10, 20
print “a=”, a print “a=”, a,
print “b=”, b print “b=”, b
a = 10 a = 10 b = 20
b = 20
Notice first print
statement ends
with a comma
output
23. As we have seen that print() automatically appends a
new line and a space between different object, this is by
default
The actual syntax of the print() function is
print(*objects, sep=‘ ’, end = ‘n’, file=sys.stdout, flush=false)
24. %i ➔ int type
%d ➔ int type
%f ➔ float type
%s ➔ str type
Syntax
Print(“formatted string” %(variable list))
25. {} ➔ replacement operator
It is used to format our output to make it look
attractive.
This can be done by using the str.format() method.
{} specify the order in which it is printed.
27. The backslash ( ) character is used to escape
characters
What if want to print n......use double
backslash
Printing single quote ( ‘ )
Printing double quote ( “ )
Printing backslash using double backslash
29. When our program grows bigger, it is a good idea to break
it into different modules.
Module is a group of functions, variables, classes etc.
A library is a collection of modules.
Python module have a filename and end with the
extension .py
Definitions inside a module can be imported to another
module or the interactive interpreter in Python. We use
the import keyword to do this.