explain variable assignment with suitable example

Leon Lovett

Python Variables – A Guide to Variable Assignment and Naming

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In Python, variables are essential elements that allow developers to store and manipulate data. When writing Python code, understanding variable assignment and naming conventions is crucial for effective programming.

Python variables provide a way to assign a name to a value and use that name to reference the value later in the code. Variables can be used to store various types of data, including numbers, strings, and lists.

In this article, we will explore the basics of Python variables, including variable assignment and naming conventions. We will also dive into the different variable types available in Python and how to use them effectively.

Key Takeaways

Python variables are used to store and manipulate data in code.
Variable assignment allows developers to assign a name to a value and reference it later.
Proper variable naming conventions are essential for effective programming.
Python supports different variable types, including integers, floats, strings, and lists.

Variable Assignment in Python

Python variables are created when a value is assigned to them using the equals sign (=) operator. For example, the following code snippet assigns the integer value 5 to the variable x :

From this point forward, whenever x is referenced in the code, it will have the value 5.

Variables can also be assigned using other variables or expressions. For example, the following code snippet assigns the value of x plus 2 to the variable y :

It is important to note that variables in Python are dynamically typed, meaning that their type can change as the program runs. For example, the following code snippet assigns a string value to the variable x , then later reassigns it to an integer value:

x = "hello" x = 7

Common Mistakes in Variable Assignment

One common mistake is trying to reference a variable before it has been assigned a value. This will result in a NameError being raised. For example:

print(variable_name) NameError: name ‘variable_name’ is not defined

Another common mistake is assigning a value to the wrong variable name. For example, the following code snippet assigns the value 5 to the variable y instead of x :

y = 5 print(x) NameError: name ‘x’ is not defined

To avoid these mistakes, it is important to carefully review code and double-check variable names and values.

Using Variables in Python

Variables are used extensively in Python code for a variety of purposes, from storing user input to performing complex calculations. The following code snippet demonstrates the basic usage of variables in a simple addition program:

number1 = input("Enter the first number: ") number2 = input("Enter the second number: ") sum = float(number1) + float(number2) print("The sum of", number1, "and", number2, "is", sum)

This program prompts the user to enter two numbers, converts them to floats using the float() function, adds them together, and prints the result using the print() function.

Variables can also be used in more complex operations, such as string concatenation and list manipulation. The following code snippet demonstrates how variables can be used to combine two strings:

greeting = "Hello" name = "Alice" message = greeting + ", " + name + "!" print(message)

This program defines two variables containing a greeting and a name, concatenates them using the plus (+) operator, and prints the result.

Variable Naming Conventions in Python

In Python, proper variable naming conventions are crucial for writing clear and maintainable code. Consistently following naming conventions makes code more readable and easier to understand, especially when working on large projects with many collaborators. Here are some commonly accepted conventions:

It’s recommended to use lowercase or snake case for variable names as they are easier to read and more commonly used in Python. Camel case is common in other programming languages, but can make Python code harder to read.

Variable names should be descriptive and meaningful. Avoid using abbreviations or single letters, unless they are commonly understood, like “i” for an iterative variable in a loop. Using descriptive names will make your code easier to understand and maintain by you and others.

Lastly, it’s a good practice to avoid naming variables with reserved words in Python such as “and”, “or”, and “not”. Using reserved words can cause errors in your code, making it hard to debug.

Scope of Variables in Python

Variables in Python have a scope, which dictates where they can be accessed and used within a code block. Understanding variable scope is important for writing efficient and effective code.

Local Variables in Python

A local variable is created within a particular code block, such as a function. It can only be accessed within that block and is destroyed when the block is exited. Local variables can be defined using the same Python variable assignment syntax as any other variable.

Example: def my_function(): x = 10 print(“Value inside function:”, x) my_function() print(“Value outside function:”, x) Output: Value inside function: 10 NameError: name ‘x’ is not defined

In the above example, the variable ‘x’ is a local variable that is defined within the function ‘my_function()’. It cannot be accessed outside of that function, which is why the second print statement results in an error.

Global Variables in Python

A global variable is a variable that can be accessed from anywhere within a program. These variables are typically defined outside of any code block, at the top level of the program. They can be accessed and modified from any code block within the program.

Example: x = 10 def my_function(): print(“Value inside function:”, x) my_function() print(“Value outside function:”, x) Output: Value inside function: 10 Value outside function: 10

In the above example, the variable ‘x’ is a global variable that is defined outside of any function. It can be accessed from within the ‘my_function()’ as well as from outside it.

When defining a function, it is possible to access and modify a global variable from within the function using the ‘global’ keyword.

Example: x = 10 def my_function(): global x x = 20 my_function() print(x) Output: 20

In the above example, the ‘global’ keyword is used to indicate that the variable ‘x’ inside the function is the same as the global variable ‘x’. The function modifies the global variable, causing the final print statement to output ’20’ instead of ’10’.

One of the most fundamental concepts in programming is the use of variables. In Python, variables allow us to store and manipulate data efficiently. Here are some practical examples of how to use variables in Python:

Mathematical Calculations

Variables are often used to perform mathematical calculations in Python. For instance, we can assign numbers to variables and then perform operations on those variables. Here’s an example:

x = 5 y = 10 z = x + y print(z) # Output: 15

In this code, we have assigned the value 5 to the variable x and the value 10 to the variable y. We then create a new variable z by adding x and y together. Finally, we print the value of z, which is 15.

String Manipulation

Variables can also be used to manipulate strings in Python. Here is an example:

first_name = “John” last_name = “Doe” full_name = first_name + ” ” + last_name print(full_name) # Output: John Doe

In this code, we have assigned the strings “John” and “Doe” to the variables first_name and last_name respectively. We then create a new variable full_name by combining the values of first_name and last_name with a space in between. Finally, we print the value of full_name, which is “John Doe”.

Working with Data Structures

Variables are also essential when working with data structures such as lists and dictionaries in Python. Here’s an example:

numbers = [1, 2, 3, 4, 5] sum = 0 for num in numbers: sum += num print(sum) # Output: 15

In this code, we have assigned a list of numbers to the variable numbers. We then create a new variable sum and initialize it to 0. We use a for loop to iterate over each number in the list, adding it to the sum variable. Finally, we print the value of sum, which is 15.

As you can see, variables are an essential tool in Python programming. By using them effectively, you can manipulate data and perform complex operations with ease.

Variable Types in Python

Python is a dynamically typed language, which means that variables can be assigned values of different types without explicit type declaration. Python supports a wide range of variable types, each with its own unique characteristics and uses.

Numeric Types:

Python supports several numeric types, including integers, floats, and complex numbers. Integers are whole numbers without decimal points, while floats are numbers with decimal points. Complex numbers consist of a real and imaginary part, expressed as a+bi.

Sequence Types:

Python supports several sequence types, including strings, lists, tuples, and range objects. Strings are sequences of characters, while lists and tuples are sequences of values of any type. Range objects are used to represent sequences of numbers.

Mapping Types:

Python supports mapping types, which are used to store key-value pairs. The most commonly used mapping type is the dictionary, which supports efficient lookup of values based on their associated keys.

Boolean Type:

Python supports a Boolean type, which is used to represent truth values. The Boolean type has two possible values: True and False.

Python has a special value called None, which represents the absence of a value. This type is often used to indicate the result of functions that do not return a value.

Understanding the different variable types available in Python is essential for effective coding. Each type has its own unique properties and uses, and choosing the right type for a given task can help improve code clarity, efficiency, and maintainability.

Python variables are a fundamental concept that every aspiring Python programmer must understand. In this article, we have covered the basics of variable assignment and naming conventions in Python. We have also explored the scope of variables and their different types.

It is important to remember that variables play a crucial role in programming, and their effective use can make your code more efficient and easier to read. Proper naming conventions and good coding practices can also help prevent errors and improve maintainability.

As you continue to explore the vast possibilities of Python programming, we encourage you to practice using variables in your code. With a solid understanding of Python variables, you will be well on your way to becoming a proficient Python programmer.

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1.4 — Variable assignment and initialization

In the previous lesson ( 1.3 -- Introduction to objects and variables ), we covered how to define a variable that we can use to store values. In this lesson, we’ll explore how to actually put values into variables and use those values.

As a reminder, here’s a short snippet that first allocates a single integer variable named x , then allocates two more integer variables named y and z :

Variable assignment

After a variable has been defined, you can give it a value (in a separate statement) using the = operator . This process is called assignment , and the = operator is called the assignment operator .

By default, assignment copies the value on the right-hand side of the = operator to the variable on the left-hand side of the operator. This is called copy assignment .

Here’s an example where we use assignment twice:

This prints:

When we assign value 7 to variable width , the value 5 that was there previously is overwritten. Normal variables can only hold one value at a time.

One of the most common mistakes that new programmers make is to confuse the assignment operator ( = ) with the equality operator ( == ). Assignment ( = ) is used to assign a value to a variable. Equality ( == ) is used to test whether two operands are equal in value.

Initialization

One downside of assignment is that it requires at least two statements: one to define the variable, and another to assign the value.

These two steps can be combined. When an object is defined, you can optionally give it an initial value. The process of specifying an initial value for an object is called initialization , and the syntax used to initialize an object is called an initializer .

In the above initialization of variable width , { 5 } is the initializer, and 5 is the initial value.

Different forms of initialization

Initialization in C++ is surprisingly complex, so we’ll present a simplified view here.

There are 6 basic ways to initialize variables in C++:

You may see the above forms written with different spacing (e.g. int d{7}; ). Whether you use extra spaces for readability or not is a matter of personal preference.

Default initialization

When no initializer is provided (such as for variable a above), this is called default initialization . In most cases, default initialization performs no initialization, and leaves a variable with an indeterminate value.

We’ll discuss this case further in lesson ( 1.6 -- Uninitialized variables and undefined behavior ).

Copy initialization

When an initial value is provided after an equals sign, this is called copy initialization . This form of initialization was inherited from C.

Much like copy assignment, this copies the value on the right-hand side of the equals into the variable being created on the left-hand side. In the above snippet, variable width will be initialized with value 5 .

Copy initialization had fallen out of favor in modern C++ due to being less efficient than other forms of initialization for some complex types. However, C++17 remedied the bulk of these issues, and copy initialization is now finding new advocates. You will also find it used in older code (especially code ported from C), or by developers who simply think it looks more natural and is easier to read.

For advanced readers

Copy initialization is also used whenever values are implicitly copied or converted, such as when passing arguments to a function by value, returning from a function by value, or catching exceptions by value.

Direct initialization

When an initial value is provided inside parenthesis, this is called direct initialization .

Direct initialization was initially introduced to allow for more efficient initialization of complex objects (those with class types, which we’ll cover in a future chapter). Just like copy initialization, direct initialization had fallen out of favor in modern C++, largely due to being superseded by list initialization. However, we now know that list initialization has a few quirks of its own, and so direct initialization is once again finding use in certain cases.

Direct initialization is also used when values are explicitly cast to another type.

One of the reasons direct initialization had fallen out of favor is because it makes it hard to differentiate variables from functions. For example:

List initialization

The modern way to initialize objects in C++ is to use a form of initialization that makes use of curly braces. This is called list initialization (or uniform initialization or brace initialization ).

List initialization comes in three forms:

As an aside…

Prior to the introduction of list initialization, some types of initialization required using copy initialization, and other types of initialization required using direct initialization. List initialization was introduced to provide a more consistent initialization syntax (which is why it is sometimes called “uniform initialization”) that works in most cases.

Additionally, list initialization provides a way to initialize objects with a list of values (which is why it is called “list initialization”). We show an example of this in lesson 16.2 -- Introduction to std::vector and list constructors .

List initialization has an added benefit: “narrowing conversions” in list initialization are ill-formed. This means that if you try to brace initialize a variable using a value that the variable can not safely hold, the compiler is required to produce a diagnostic (usually an error). For example:

In the above snippet, we’re trying to assign a number (4.5) that has a fractional part (the .5 part) to an integer variable (which can only hold numbers without fractional parts).

Copy and direct initialization would simply drop the fractional part, resulting in the initialization of value 4 into variable width . Your compiler may optionally warn you about this, since losing data is rarely desired. However, with list initialization, your compiler is required to generate a diagnostic in such cases.

Conversions that can be done without potential data loss are allowed.

To summarize, list initialization is generally preferred over the other initialization forms because it works in most cases (and is therefore most consistent), it disallows narrowing conversions, and it supports initialization with lists of values (something we’ll cover in a future lesson). While you are learning, we recommend sticking with list initialization (or value initialization).

Best practice

Prefer direct list initialization (or value initialization) for initializing your variables.

Author’s note

Bjarne Stroustrup (creator of C++) and Herb Sutter (C++ expert) also recommend using list initialization to initialize your variables.

In modern C++, there are some cases where list initialization does not work as expected. We cover one such case in lesson 16.2 -- Introduction to std::vector and list constructors .

Because of such quirks, some experienced developers now advocate for using a mix of copy, direct, and list initialization, depending on the circumstance. Once you are familiar enough with the language to understand the nuances of each initialization type and the reasoning behind such recommendations, you can evaluate on your own whether you find these arguments persuasive.

Value initialization and zero initialization

When a variable is initialized using empty braces, value initialization takes place. In most cases, value initialization will initialize the variable to zero (or empty, if that’s more appropriate for a given type). In such cases where zeroing occurs, this is called zero initialization .

Q: When should I initialize with { 0 } vs {}?

Use an explicit initialization value if you’re actually using that value.

Use value initialization if the value is temporary and will be replaced.

Initialize your variables

Initialize your variables upon creation. You may eventually find cases where you want to ignore this advice for a specific reason (e.g. a performance critical section of code that uses a lot of variables), and that’s okay, as long as the choice is made deliberately.

Python Numerical Methods

This notebook contains an excerpt from the Python Programming and Numerical Methods - A Guide for Engineers and Scientists , the content is also available at Berkeley Python Numerical Methods .

The copyright of the book belongs to Elsevier. We also have this interactive book online for a better learning experience. The code is released under the MIT license . If you find this content useful, please consider supporting the work on Elsevier or Amazon !

< 2.0 Variables and Basic Data Structures | Contents | 2.2 Data Structure - Strings >

Variables and Assignment ¶

When programming, it is useful to be able to store information in variables. A variable is a string of characters and numbers associated with a piece of information. The assignment operator , denoted by the “=” symbol, is the operator that is used to assign values to variables in Python. The line x=1 takes the known value, 1, and assigns that value to the variable with name “x”. After executing this line, this number will be stored into this variable. Until the value is changed or the variable deleted, the character x behaves like the value 1.

TRY IT! Assign the value 2 to the variable y. Multiply y by 3 to show that it behaves like the value 2.

A variable is more like a container to store the data in the computer’s memory, the name of the variable tells the computer where to find this value in the memory. For now, it is sufficient to know that the notebook has its own memory space to store all the variables in the notebook. As a result of the previous example, you will see the variable “x” and “y” in the memory. You can view a list of all the variables in the notebook using the magic command %whos .

TRY IT! List all the variables in this notebook

Note that the equal sign in programming is not the same as a truth statement in mathematics. In math, the statement x = 2 declares the universal truth within the given framework, x is 2 . In programming, the statement x=2 means a known value is being associated with a variable name, store 2 in x. Although it is perfectly valid to say 1 = x in mathematics, assignments in Python always go left : meaning the value to the right of the equal sign is assigned to the variable on the left of the equal sign. Therefore, 1=x will generate an error in Python. The assignment operator is always last in the order of operations relative to mathematical, logical, and comparison operators.

TRY IT! The mathematical statement x=x+1 has no solution for any value of x . In programming, if we initialize the value of x to be 1, then the statement makes perfect sense. It means, “Add x and 1, which is 2, then assign that value to the variable x”. Note that this operation overwrites the previous value stored in x .

There are some restrictions on the names variables can take. Variables can only contain alphanumeric characters (letters and numbers) as well as underscores. However, the first character of a variable name must be a letter or underscores. Spaces within a variable name are not permitted, and the variable names are case-sensitive (e.g., x and X will be considered different variables).

TIP! Unlike in pure mathematics, variables in programming almost always represent something tangible. It may be the distance between two points in space or the number of rabbits in a population. Therefore, as your code becomes increasingly complicated, it is very important that your variables carry a name that can easily be associated with what they represent. For example, the distance between two points in space is better represented by the variable dist than x , and the number of rabbits in a population is better represented by nRabbits than y .

Note that when a variable is assigned, it has no memory of how it was assigned. That is, if the value of a variable, y , is constructed from other variables, like x , reassigning the value of x will not change the value of y .

EXAMPLE: What value will y have after the following lines of code are executed?

WARNING! You can overwrite variables or functions that have been stored in Python. For example, the command help = 2 will store the value 2 in the variable with name help . After this assignment help will behave like the value 2 instead of the function help . Therefore, you should always be careful not to give your variables the same name as built-in functions or values.

TIP! Now that you know how to assign variables, it is important that you learn to never leave unassigned commands. An unassigned command is an operation that has a result, but that result is not assigned to a variable. For example, you should never use 2+2 . You should instead assign it to some variable x=2+2 . This allows you to “hold on” to the results of previous commands and will make your interaction with Python must less confusing.

You can clear a variable from the notebook using the del function. Typing del x will clear the variable x from the workspace. If you want to remove all the variables in the notebook, you can use the magic command %reset .

In mathematics, variables are usually associated with unknown numbers; in programming, variables are associated with a value of a certain type. There are many data types that can be assigned to variables. A data type is a classification of the type of information that is being stored in a variable. The basic data types that you will utilize throughout this book are boolean, int, float, string, list, tuple, dictionary, set. A formal description of these data types is given in the following sections.

Learning Python by doing

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Variables, Expressions, and Assignments

Variables, expressions, and assignments 1 #, introduction #.

In this chapter, we introduce some of the main building blocks needed to create programs–that is, variables, expressions, and assignments. Programming related variables can be intepret in the same way that we interpret mathematical variables, as elements that store values that can later be changed. Usually, variables and values are used within the so-called expressions. Once again, just as in mathematics, an expression is a construct of values and variables connected with operators that result in a new value. Lastly, an assignment is a language construct know as an statement that assign a value (either as a constant or expression) to a variable. The rest of this notebook will dive into the main concepts that we need to fully understand these three language constructs.

Values and Types #

A value is the basic unit used in a program. It may be, for instance, a number respresenting temperature. It may be a string representing a word. Some values are 42, 42.0, and ‘Hello, Data Scientists!’.

Each value has its own type : 42 is an integer ( int in Python), 42.0 is a floating-point number ( float in Python), and ‘Hello, Data Scientists!’ is a string ( str in Python).

The Python interpreter can tell you the type of a value: the function type takes a value as argument and returns its corresponding type.

Observe the difference between type(42) and type('42') !

Expressions and Statements #

On the one hand, an expression is a combination of values, variables, and operators.

A value all by itself is considered an expression, and so is a variable.

When you type an expression at the prompt, the interpreter evaluates it, which means that it calculates the value of the expression and displays it.

In boxes above, m has the value 27 and m + 25 has the value 52 . m + 25 is said to be an expression.

On the other hand, a statement is an instruction that has an effect, like creating a variable or displaying a value.

The first statement initializes the variable n with the value 17 , this is a so-called assignment statement .

The second statement is a print statement that prints the value of the variable n .

The effect is not always visible. Assigning a value to a variable is not visible, but printing the value of a variable is.

Assignment Statements #

We have already seen that Python allows you to evaluate expressions, for instance 40 + 2 . It is very convenient if we are able to store the calculated value in some variable for future use. The latter can be done via an assignment statement. An assignment statement creates a new variable with a given name and assigns it a value.

The example in the previous code contains three assignments. The first one assigns the value of the expression 40 + 2 to a new variable called magicnumber ; the second one assigns the value of π to the variable pi , and; the last assignment assigns the string value 'Data is eatig the world' to the variable message .

Programmers generally choose names for their variables that are meaningful. In this way, they document what the variable is used for.

Do It Yourself!

Let’s compute the volume of a cube with side $s = 5$ . Remember that the volume of a cube is defined as $v = s^3$ . Assign the value to a variable called volume .

Well done! Now, why don’t you print the result in a message? It can say something like “The volume of the cube with side 5 is $volume$ ”.

Beware that there is no checking of types ( type checking ) in Python, so a variable to which you have assigned an integer may be re-used as a float, even if we provide type-hints .

Names and Keywords #

Names of variable and other language constructs such as functions (we will cover this topic later), should be meaningful and reflect the purpose of the construct.

In general, Python names should adhere to the following rules:

It should start with a letter or underscore.

It cannot start with a number.

It must only contain alpha-numeric (i.e., letters a-z A-Z and digits 0-9) characters and underscores.

They cannot share the name of a Python keyword.

If you use illegal variable names you will get a syntax error.

By choosing the right variables names you make the code self-documenting, what is better the variable v or velocity ?

The following are examples of invalid variable names.

These basic development principles are sometimes called architectural rules . By defining and agreeing upon architectural rules you make it easier for you and your fellow developers to understand and modify your code.

If you want to read more on this, please have a look at Code complete a book by Steven McConnell [ McC04 ] .

Every programming language has a collection of reserved keywords . They are used in predefined language constructs, such as loops and conditionals . These language concepts and their usage will be explained later.

The interpreter uses keywords to recognize these language constructs in a program. Python 3 has the following keywords:

False class finally is return

None continue for lambda try

True def from nonlocal while

and del global not with

as elif if or yield

assert else import pass break

except in raise

Reassignments #

It is allowed to assign a new value to an existing variable. This process is called reassignment . As soon as you assign a value to a variable, the old value is lost.

The assignment of a variable to another variable, for instance b = a does not imply that if a is reassigned then b changes as well.

You have a variable salary that shows the weekly salary of an employee. However, you want to compute the monthly salary. Can you reassign the value to the salary variable according to the instruction?

Updating Variables #

A frequently used reassignment is for updating puposes: the value of a variable depends on the previous value of the variable.

This statement expresses “get the current value of x , add one, and then update x with the new value.”

Beware, that the variable should be initialized first, usually with a simple assignment.

Do you remember the salary excercise of the previous section (cf. 13. Reassignments)? Well, if you have not done it yet, update the salary variable by using its previous value.

Updating a variable by adding 1 is called an increment ; subtracting 1 is called a decrement . A shorthand way of doing is using += and -= , which stands for x = x + ... and x = x - ... respectively.

Order of Operations #

Expressions may contain multiple operators. The order of evaluation depends on the priorities of the operators also known as rules of precedence .

For mathematical operators, Python follows mathematical convention. The acronym PEMDAS is a useful way to remember the rules:

Parentheses have the highest precedence and can be used to force an expression to evaluate in the order you want. Since expressions in parentheses are evaluated first, 2 * (3 - 1) is 4 , and (1 + 1)**(5 - 2) is 8 . You can also use parentheses to make an expression easier to read, even if it does not change the result.

Exponentiation has the next highest precedence, so 1 + 2**3 is 9 , not 27 , and 2 * 3**2 is 18 , not 36 .

Multiplication and division have higher precedence than addition and subtraction . So 2 * 3 - 1 is 5 , not 4 , and 6 + 4 / 2 is 8 , not 5 .

Operators with the same precedence are evaluated from left to right (except exponentiation). So in the expression degrees / 2 * pi , the division happens first and the result is multiplied by pi . To divide by 2π, you can use parentheses or write: degrees / 2 / pi .

In case of doubt, use parentheses!

Let’s see what happens when we evaluate the following expressions. Just run the cell to check the resulting value.

Floor Division and Modulus Operators #

The floor division operator // divides two numbers and rounds down to an integer.

For example, suppose that driving to the south of France takes 555 minutes. You might want to know how long that is in hours.

Conventional division returns a floating-point number.

Hours are normally not represented with decimal points. Floor division returns the integer number of hours, dropping the fraction part.

You spend around 225 minutes every week on programming activities. You want to know around how many hours you invest to this activity during a month. Use the $//$ operator to give the answer.

The modulus operator % works on integer values. It computes the remainder when dividing the first integer by the second one.

The modulus operator is more useful than it seems.

For example, you can check whether one number is divisible by another—if x % y is zero, then x is divisible by y .

String Operations #

In general, you cannot perform mathematical operations on strings, even if the strings look like numbers, so the following operations are illegal: '2'-'1' 'eggs'/'easy' 'third'*'a charm'

But there are two exceptions, + and * .

The + operator performs string concatenation, which means it joins the strings by linking them end-to-end.

The * operator also works on strings; it performs repetition.

Speedy Gonzales is a cartoon known to be the fastest mouse in all Mexico . He is also famous for saying “Arriba Arriba Andale Arriba Arriba Yepa”. Can you use the following variables, namely arriba , andale and yepa to print the mentioned expression? Don’t forget to use the string operators.

Asking the User for Input #

The programs we have written so far accept no input from the user.

To get data from the user through the Python prompt, we can use the built-in function input .

When input is called your whole program stops and waits for the user to enter the required data. Once the user types the value and presses Return or Enter , the function returns the input value as a string and the program continues with its execution.

Try it out!

You can also print a message to clarify the purpose of the required input as follows.

The resulting string can later be translated to a different type, like an integer or a float. To do so, you use the functions int and float , respectively. But be careful, the user might introduce a value that cannot be converted to the type you required.

We want to know the name of a user so we can display a welcome message in our program. The message should say something like “Hello $name$ , welcome to our hello world program!”.

Script Mode #

So far we have run Python in interactive mode in these Jupyter notebooks, which means that you interact directly with the interpreter in the code cells . The interactive mode is a good way to get started, but if you are working with more than a few lines of code, it can be clumsy. The alternative is to save code in a file called a script and then run the interpreter in script mode to execute the script. By convention, Python scripts have names that end with .py .

Use the PyCharm icon in Anaconda Navigator to create and execute stand-alone Python scripts. Later in the course, you will have to work with Python projects for the assignments, in order to get acquainted with another way of interacing with Python code.

This Jupyter Notebook is based on Chapter 2 of the books Python for Everybody [ Sev16 ] and Think Python (Sections 5.1, 7.1, 7.2, and 5.12) [ Dow15 ] .

Python Variables and Assignment

Python variables, variable assignment rules, every value has a type, memory and the garbage collector, variable swap, variable names are superficial labels, assignment = is shallow, decomp by var.

Variables and Assignment

Variables and assignment #.

Watch a walk-through of this lesson on YouTube

Download all the Jupyter notebooks and other files you need to complete the lessons in this chapter (Chapter 3)

Turn off the GitHub Copilot AI assistant so you can focus on learning Python using your HI (human intelligence). Click the Deactivate Copilot button in the bottom right of VS Code, if it is currently activated.

Questions #

How can I store data in programs?

Learning Objectives #

Write programs that assign values to variables and perform calculations with those values.

Correctly trace value changes in programs that use scalar assignment.

Use variables to store values. #

Variables are names for values.

In Python the = symbol assigns the value on the right to the name on the left.

The variable is created when a value is assigned to it.

Here, Python assigns an age to a variable age and a name in quotes to a variable first_name .

Variable names

can only contain letters, digits, and underscore _ (typically used to separate words in long variable names)

cannot start with a digit

are case sensitive (age, Age and AGE are three different variables)

Variable names that start with underscores like __aarons_real_age have a special meaning so we won’t do that until we understand the convention.

Use print to display values. #

Python has a built-in function called print that prints things as text.

Call the function (i.e., tell Python to run it) by using its name.

Provide values to the function (i.e., the things to print) in parentheses.

To add a string to the printout, wrap the string in single or double quotes.

The values passed to the function are called arguments

print automatically puts a single space between items to separate them.

It also wraps around to a new line at the end.

Variables must be created before they are used. #

If a variable doesn’t exist yet, or if the name has been mis-spelled, Python reports an error. (Unlike some languages, which “guess” a default value.)

The last line of an error message is usually the most informative.

We will look at error messages in detail later.

Variables persist between cells #

Be aware that it is the order of execution of cells that is important in a Jupyter notebook, not the order in which they appear. Python will remember all the code that was run previously, including any variables you have defined, irrespective of the order in the notebook. Therefore if you define variables lower down the notebook and then (re)run cells further up, those defined further down will still be present. As an example, consider the following

If you execute this in order, the first cell will give an error. However, if you run the first cell after the second cell it will print out 1 . It’s possible to drag ‘n drop cells in CoCalc, to reorder them.

If you start to get confused about what order you’ve run cells in, it can be helpful to use the Kernel - Restart & Run All menu option which clears the interpreter and runs everything from a clean slate going top to bottom.

Variables can be used in calculations. #

We can use variables in calculations just as if they were values.

Remember, we assigned the value 42 to age a few lines ago.

Python is case-sensitive. #

Python thinks that upper- and lower-case letters are different, so Name and name are different variables. You can prove this by running print(Age) in the cell below.

There are conventions for using upper-case letters at the start of variable names— they should only be used in specific circumstances in Python — so it is good practice to only use lower-case letters for variable names

Use meaningful variable names. #

Python doesn’t care what you call variables as long as they obey the rules (alphanumeric characters and the underscore).

However, if you use meaningful variable names, you help other people (and your future self!) understand what the program does

Although Python allows you to use virtually any characters in variable names, there are style conventions that you should learn and follow. Python PEP 8]( https://www.python.org/dev/peps/pep-0008/#naming-conventions ) (PEPs are the “Python Enhancement Proposals” that provide standards for the language) specifies that regular variables “should be lowercase, with words separated by underscores as necessary to improve readability”.

So, you should only use lower-case letters in variable names. This is because upper-case letters are used for specific purposes in Python. As well, if your variable name is more than one word (such as first_name ), you should use underscores to separate the words. This naming convention is called snake case .

You may encounter different conventions as standard in other programming languages (or in examples of Python that don’t properly follow style conventions), such as camel case which would be FirstName or possibly firstName (for the aficionados: the first is is a sub-type of camel case called Pascal case , while the second is dromedary case ).

There is a good reason for following these conventions: when a seasoned Python programmer sees something in camel case, they will expect it to be a class or type variable, not a regular variable. Following Python’s conventions thus improves the readability, sharability, and transparency of code.

Exercises #

Exercises in this workshop are tasks that we encourage you to work on , on your own. We’ll give you some time to work on them and then check in and discuss.

What’s in a name? #

Which is a better variable name, m , min , or minutes ? Why? (Hint: think about which code you would rather inherit from someone who is leaving the lab):

Variables only change value when something is assigned to them #

If we make one cell in a spreadsheet depend on another, and update the latter, the former updates automatically

This does not happen in programming languages

The computer reads the value of first when doing the multiplication, creates a new value, and assigns it to second .

After that, second does not remember where it came from.

Swapping Values #

Try to follow what happens in the following sequence of commands. Guess what the final values of x and y will be, then run the code yourself to check your guess.

These three lines exchange the values in x and y using the swap variable for temporary storage. This is a fairly common programming idiom.

Key Points Summary: #

Use variables to store values

Use print to display values

Variables persist between cells

Variables must be created before they are used

Variables can be used in calculations

Python is case-sensitive

Variables only change value when something is assigned to them

Use meaningful variable names

Use only lower-case letters, separated by underscores, in variable names

This lesson is adapted from the Software Carpentry Plotting and Programming in Python workshop.

Introduction to Programming

Variables in python.

The purpose of a variable is to store information within a program while it is running.
A variable is a named storage location in computer memory. Use the name to access the value.
To store a value in a variable, use the = operator (called the assignment operator).
An = sign in Python is nothing like an equal sign in mathematics. Think of it more like an arrow going from right to left. The expression on the right is evaluated and then stored in the variable named on the left.
For example, the line of code hourly_wage = 16.75 stores the value 16.75 in the variable called hourly_wage
You can change the value of a variable with another assignment statement, such as hourly_wage = 17.25
Every value has a type ( int for integers, float for decimals, str for text). In python, when you store a value in a variable (with = ), that variable then automatically has a type. For example, after the above assignment, hourly_wage is of type float .

Rules and conventions for naming variables in python

The first character must be a letter or an underscore. For now, stick to letters for the first character.
The remaining characters must be letters, numbers or underscores.
No spaces are allowed in variable names.
Legal examples: _pressure , pull , x_y , r2d2
Invalid examples, these are NOT legal variable names: 4th_dimension , %profit , x*y , four(4) , repo man
In python, it's a conventiion to use snake case to name variables. This means that we use all lower-case letters and we separate words in the variable name with underscores. Examples include age , x_coordinate , hourly_wage , user_password
If the value stored in a variable is a true constant (in other words, its value will never change throughout the program), then we use all capital letters: COURSE_ENROLLMENT_LIMIT , MAX_PASSWORD_ATTEMPTS .
For high quality code, it is crucial that you give descriptive names for variables. The variable names must help the reader of your program understand your intention.

Typical way we visualize variables

We usually draw variables by putting the value in a box, and labelling the box with the name of the variable:

Types of variables

Each variable has a name, a value, and a type. Types are necessary because different kinds of data are stored differently within the computer's memory. For now, we will learn three different types, for storing signed (positive or negative) whole numbers, signed decimals, and text.

Creating a variable with an assignment operator

A variable is created or declared when we assign a value to it using the assignment operator = . In python, the code looks like this: variable_name = <value> .

Notice that the left hand side of an assignment must be a variable name. Non-example:

After creating a variable, you can change the value stored in a variable with another assignment operator at any time. This is called reassignment .

Finding out the type of a variable or value

The type() function in python will return the type of either a variable or a value. Here are examples that show how to use it:

The output of the above code will be:

Casting (changing the type) of a variable or value

You can change the type of a value (called “casting”) using the int() , float() and str() functions. For example:

int(23.7) (truncates the float value 23.7 to the int value 23. This is different from rounding - the decimal part is discarded, regardless of whether it is larger or smaller than 0.5.
float(23) (outputting the result will give 23.0 rather than 23)
str(23) (converts the integer 23 to the text "23" )
int("23") (converts the string "23" into a numerical integer value 23 )
float("23") (converts the string "23" into a numerical decimal value 23.0 )
int("23.5") results in an error
float("hello") results in an error

Doing arithmetic in python

Here are the basic arithmetic operators in python. In these examples, assume

An example of a use of the modulus operator is to determine if an integer is even or odd. Note that if x is an integer, then x%2 takes the value 0 or 1 . So x % 2 == 0 is True when x is even and False when x is odd.

Another example of integer division and modulus: When we divide 3 by 4, we get a quotient of 0 and a remainder of 3. So 3//4 results in 0 and 3%4 results in 3.

Warning note: In python, ^ is not an exponent!

Order of operations

The order of operations in python is similar to the order you are familiar with in math: parentheses, then exponentiation, then multiplication/division/modulus in order from left to right, then addition/subtraction in order from left to right.

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AP®︎/College Computer Science Principles

Course: ap®︎/college computer science principles > unit 3, storing data in variables, assigning variables, displaying variables, re-assigning variables, pseudocode for variables.

(Choice A) x ← 200 A x ← 200
(Choice B) var x = 200 B var x = 200
(Choice C) x = 200 C x = 200
(Choice D) var x ← 200 D var x ← 200

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explain variable assignment with suitable example

Coding Fundamentals and Patterns

In this lesson, we will discuss the use of variables and assignment operators in Python, with a focus on the following key points:

What are variables and the assignment of variables in the Python programming language?
Working with variables and assignment of variables in an introductory programming language.

This is a general purpose tutorial for multiple languages. For the Javascript-specific version of this lesson that focuses on fundamentals frontend engineers need to know, please click here .

Throughout the day, we often need to store a piece of information somewhere and refer to it later.

We encounter these situations while writing a computer program as well, where we often need to store some information or data temporarily. For this specific purpose, variables are used. These variables can store almost any type of data, whether they are numbers, strings, or lists. Data is stored in variables by assign -ing data values to them. This lesson will expand on this topic and discuss variables and their assignment in detail.

As discussed above, variable s can store data. Data values can be assigned to a variable by using the assignment operator , which is the equal sign (=).

Once a value is assigned to the variable, it corresponds to that value unless it is re-assigned. Suppose we assign a value 5 to a variable a . This concept can be visualized as below.

This ensures that whenever we use the variable a in our program, we will get a value of 5. Let's understand this with code examples in Python.

Variables in Python

In Python, variables can be directly created by providing a variable name and assigning it some corresponding value. The code block below shows the creation of the variable number , which has the value 10 .

If we execute this code in a Python interpreter, it will give no output. Why?

Because this is a statement , and this statement did not tell the programming language to display the value of variable number . For that, we'd need to either print() it, or log it out in some other way.

However, it did create a variable number in memory and assigned it the value 10 . To check if the value was properly assigned, type either the variable name on the console, or use the print() function. It will display the variable name on the console.

The value that you stored earlier in number is successfully displayed, and we can see that it correctly assigned the value.

Important Rules while Creating Variables

Programming languages understand instructions only if they are given in a specified format (or syntax). When creating variables, we need to be careful of these rules, or the variables will not be created properly, and the program may give errors.

Variable names can be created using alphabetical letters (a-z and A-Z), digits (0-9), or underscore symbol (_). Special symbols are not allowed. For example, abc&def is an invalid variable name.
Variable names can begin with the underscore symbol or alphabetical letters only, not digits. For example, 123abc is an invalid variable name and will give you an error.
Variables in Python are case-sensitive . This means that if we declare two variables score and Score with different values assigned to them, then they are two different variables (not the same variable!).
Every programming language has certain keywords , that define in-built functionality in the language. These should not be used as variable names. Since it has a different meaning in the language, declaring variables with already existing keyword names will cause an error. These keywords will be highlighted with a different color whenever you type them, so it is easy for you to distinguish. For example, and is a keyword in Python, hence declaring a variable with that name would raise an error.
In Python, it is important to assign a value to a variable. If you only define the variable without assigning it a value, it will produce an error.

Now that we know how to create variables, let's see if we understood them properly.

Let's test your knowledge. Is this statement true or false?

Is the following code snippet a valid way to declare a variable?

Press true if you believe the statement is correct, or false otherwise.

Build your intuition. Is this statement true or false?

Is _name a valid variable name?

Reassigning variables

Values can be reassigned to variables in Python. When variables are reassigned, their value changes to that of the newer value specified, and the previous value is lost.

Let's look at an example. We can reassign variable values in Python as follows.

The reassignment works similarly to how we create the variable. We only provide a different value than what was stored before. Here, the initial value of a was 10 , which was reassigned to 20 from the second line in the above code block.

Operations on Variables

Using variables in the program makes it easy for us to perform various operations on data. Different types of variables support different types of operations. For simplicity, let's consider the type integer. On this type of variable, all mathematical operations are valid.

Let's understand this with a code example.

This code block shows that if we have two integer variables, we can add them and get the result. Similarly, other mathematical operations such as subtraction, multiplication, and division are also supported.

Now let's consider if we have a variable of type string. In this case, the operations are defined differently. Here, a + symbol between two variables will join the two strings together.

Here, the two strings are joined together to produce a new string. This operation is called concatenation . There are several other operations that we can perform on strings, integers, and other types of variables, but we will discuss them in later lessons.

Time for some practice questions!

Try this exercise. Fill in the missing part by typing it in.

What will be the final value of variable a below?

Write the missing line below.

Try this exercise. Click the correct answer from the options.

What will the following program output?

Click the option that best answers the question.

Will give an error

In this lesson, we talked about a basic concept in programming, about the creation of variables and assigning values to them. A useful tip for creating variables is to use meaningful names while creating them. If you have a lot of variables in your program and you don't name them properly, there is a high chance that you'll get confused about which variables were supposed to store what value!

One Pager Cheat Sheet

This lesson will discuss variables and assignment of data values in Python for storing data temporarily.
Variables are placeholders for data values that can be assigned using the assignment operator (=) and re-assigned when needed.
Python can create variables directly by providing a name and assigning it a value, as shown in the code blocks, and then use the print() or variable name to display the stored value.
We need to be careful to follow the specific syntax rules when creating variables, or they may not be created correctly and cause errors.
Creating a variable in Python is done by having a variable name followed by an assignment operator (=) and a value , as is the case with the code snippet words = "Hello World!" , which is a valid way to declare the variable words .
Yes, using an underscore (_) is a valid way to name variables in Python.
Variables can be reassigned in Python, replacing their previous value with a newer one .
We can perform different operations on each type of variable, such as mathematical operations on integers or concatenation of strings.
The final value of a is "World" .
The program prints the result of concatenating the values in the first_name and last_name variables, which is AnnaGreen .
Creating meaningful variable names is key to being able to keep track of values stored in a program .

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Python Variables (With Examples)

Written by Rahul Lath

Python Tutorials

What are Python Variables?

Definition of Variables in Python

Variables are essential components of programming languages that allow programmers to store values in a named container. In Python, a variable is created when a value is assigned to it using the assignment operator “=”. The value can be of any data type, including numbers, strings, booleans, and objects. Once a variable is defined, it can be used throughout the program to refer to the stored value.

Importance of Understanding Variables in Python

It’s essential to comprehend variables if you want to understand Python programming. The fundamental units of any program, variables, are heavily utilized in Python coding. The ability to define and use variables is a requirement for creating programs that can carry out intricate operations and address real-world issues.

Overview of the Article

In this article, we will discuss variables in Python, including their definition, importance, and usage. We will cover the different types of variables, including integers, floating-point numbers, strings, and booleans. Additionally, we will discuss the rules for naming variables and best practices for using them in Python code. By the end of this article, you will have a solid understanding of variables in Python and be able to use them effectively in your own programs.

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Creating and Initializing Variables in Python

Variable Naming Rules

In Python, variable names must follow specific rules to be valid. Variable names can only contain letters, numbers, and underscores, and they cannot start with a number. Variable names are case-sensitive, so “myVar” and “myvar” are two different variables. It’s also good practice to choose a descriptive name for your variable that reflects its purpose.

Data Types in Python

Python supports various data types, including integers, floating-point numbers, strings, and booleans. Integers are whole numbers, such as 1, 2, and 3. Floating-point numbers are decimal numbers, such as 3.14 or 0.5. Strings are a sequence of characters, such as “hello” or “world.” Booleans have two possible values, True and False, and are often used for logical operations.

How to Declare and Initialize Variables in Python

To declare a python variable , we use the assignment operator “=” and assign a value to the variable. For example, to create a variable called “age” and assign it the value 10, we would use the following code:

We can also declare and initialize multiple variables in a single line, like this:

Examples of Initializing Variables

Here are some examples of initializing variables in Python:

We can also perform operations on variables, such as arithmetic operations on integers and floating-point numbers. For example:

In summary, creating and initializing variables is an important aspect of programming in Python. By following the naming rules and understanding the different data types, you can create variables that store and manipulate various values in your programs.

Data Types of Python Variables

Numeric Data Types

Complex Numbers

Boolean Data Type

Boolean data types represent a logical value that can be either True or False. For example:

Boolean data types are often used in conditional statements, such as if-else statements and while loops, to control the flow of a program.

String Data Type

String data types represent a sequence of characters. They can be enclosed in single quotes (‘…’) or double quotes (“…”). For example:

Strings can also be concatenated using the + operator, and individual characters can be accessed using indexing.

List Data Type

List data types represent an ordered collection of items. They can contain elements of different data types, such as integers, strings, and even other lists. For example:

Lists can be modified by adding or removing elements using various built-in methods.

Tuple Data Type

Tuple data types are similar to lists but are immutable, meaning that they cannot be modified after they are created. They are often used to store related values that should not be changed. For example:

Tuples can be accessed using indexing, and individual elements can be unpacked into separate variables.

Set Data Type

Set data types represent an unordered collection of unique elements. They can be used to perform set operations such as union, intersection, and difference. For example:

Sets can be modified by adding or removing elements using various built-in methods.

Dictionary Data Type

Dictionary data types represent a collection of key-value pairs. They are often used to store data that can be accessed using a specific key. For example:

Dictionaries can be modified by adding or removing key-value pairs using various built-in methods. Values can be accessed using their corresponding keys.

Type Conversion and Casting

Implicit Type Conversion

Python automatically converts one data type to another when necessary. This is known as implicit type conversion. For example, if we try to add an integer and a float, Python will convert the integer to a float and perform the addition:

Explicit Type Conversion

We can also convert one data type to another explicitly using casting. This is known as explicit type conversion. There are built-in functions in Python that can be used to perform type casting. For example:

We can also convert between different data types using the int(), float(), str(), list(), tuple(), set(), and dict() functions.

Examples of Type Conversion

Type conversion is often used to ensure that the data types of variables are compatible with each other in a program.

Single or Double Quotes?

String Literals in Python

A string literal is a sequence of characters enclosed in quotes. In Python, we can use either single quotes (‘…’) or double quotes (“…”) to create a string. For example:

Choosing the Right Quote Type

The choice between using single or double quotes is mostly a matter of personal preference. However, there are some cases where one is more appropriate than the other.

If the string contains a single quote, we should use double quotes to enclose the string literal. Similarly, if the string contains double quotes, we should use single quotes to enclose the string literal. For example:

Case-Sensitivity in Python Variable Names

Understanding Case-Sensitivity

Python is a case-sensitive language, which means that variable names are distinguished by their case. This means that the variable “my_variable” is different from “My_Variable” and “MY_VARIABLE”.

Conventions for Naming Variables in Python

While Python is case-sensitive, it is recommended to use lowercase letters for variable names. This makes the code easier to read and understand. If a variable name consists of multiple words, it is common to use underscores to separate the words. For example:

In addition to using lowercase letters and underscores, there are some naming conventions that are commonly used in Python. For example, variable names should be descriptive and indicate the purpose of the variable.

It is also common to use all capital letters for constants, which are values that do not change during the execution of the program.

By following these conventions, we can make our code more readable and easier to understand for ourselves and others who may be working with our code.

If the string contains both single and double quotes, we can use either triple single quotes or triple double quotes to enclose the string literal. For example:

In general, it is best to choose the quote type that makes the code easier to read and understand.

Variable Scope in Python

Global Variables

A global variable is a variable that is defined outside of a function or block of code, which means it can be accessed from anywhere in the program. However, it is important to be careful when using global variables, as they can sometimes lead to unexpected behavior.

Local Variables

A local variable is a variable that is defined within a function or block of code, which means it can only be accessed within that function or block. Local variables have a limited scope, which means they are only available for use within the function or block of code where they are defined.

Scope Hierarchy

Python has a hierarchy of scopes, which determines the order in which variables are searched for within a program. The hierarchy is as follows: local scope, enclosing functions, global scope, and built-in scope. When a variable is referenced in a program, Python first looks for it in the local scope, then in any enclosing functions, then in the global scope, and finally in the built-in scope.

In this example, the local variable “x” within the function “my_function” takes precedence over the global variable “x”.

Examples of Global and Local Variables

In this example, the global keyword is used within the function “my_function” to indicate that we want to modify the global variable “x”. Without the global keyword, the function would create a new local variable with the same name as the global variable.

In this example, the variable “x” is defined within the function “my_function” and is not accessible outside of the function. When we try to print the value of “x” outside of the function, we get a NameError because “x” is not defined in the global scope.

Outputting Variables

Using the print() Function to Output Variables

The print() function is a built-in function in Python that allows you to output variables and other data to the console. Here is an example of using the print() function to output a variable:

You can also output multiple variables at once by separating them with commas:

Formatting Output with f-strings

f-strings are a way of formatting strings in Python that allow you to embed variables directly into the string. To use f-strings, you begin the string with the letter “f” and enclose variables in curly braces. Here is an example:

You can also perform calculations or manipulate variables within the curly braces:

Best Practices for Using Variables in Python

Choosing Clear and Descriptive Variable Names

One of the most important best practices when using variables in Python is to choose clear and descriptive variable names. This makes your code more readable and understandable for both yourself and others who may be reading your code. Here are some tips for choosing variable names:

Use meaningful names that describe what the variable represents.
Use lowercase letters for variable names.
Use underscores to separate words in variable names.
Avoid using single-letter variable names, except in cases where the variable represents a common convention (e.g. “i” for loop indices).

Here is an example of choosing clear and descriptive variable names:

Using Constants

Constants are variables whose value is intended to remain constant throughout the program. In Python, constants are typically declared using all capital letters to distinguish them from regular variables. Here is an example of using a constant:

Avoiding Variable Shadowing

Variable shadowing occurs when a variable declared within a certain scope has the same name as a variable declared in an outer scope. This can cause confusion and unexpected behavior in your code. To avoid variable shadowing, it’s best to use unique variable names and avoid reusing variable names in nested scopes. Here is an example of variable shadowing:

Minimizing the Use of Global Variables

Global variables are variables that are declared outside of any function or class, and can be accessed from anywhere in the program. While global variables can be convenient, they can also make your code more difficult to understand and maintain. It’s best to use global variables sparingly, and instead pass variables as arguments to functions or create class instances to store data. Here is an example of minimizing the use of global variables:

In this example, the radius variable is passed as an argument to the calculate_area() function rather than being declared as a global variable. This makes the code more modular and easier to understand.

Debugging with Variables

In programming, debugging is the process of finding and fixing errors or bugs in the code. Variables are often a common source of errors in code. Here are some common variable-related errors and debugging tips to help you fix them:

Common Variable-Related Errors

NameError: This error occurs when a variable is referenced before it is defined or if it is misspelled.
TypeError: This error occurs when an operation is performed on a variable of the wrong data type.
SyntaxError: This error occurs when the code is not written according to the correct syntax rules.

Debugging Tips and Tricks

Check variable names : Make sure that you have spelled the variable name correctly and that it has been defined before it is used.
Check data types: Make sure that you are using variables of the correct data type. If necessary, use type conversion to convert the data type of a variable.
Use print statements: Use print statements to help you debug your code. Print the value of variables to check if they have the expected value.
Use a debugger: A debugger is a tool that allows you to step through your code line by line and see the values of variables at each step. This can be helpful in finding and fixing errors in your code.

By following these debugging tips and best practices, you can easily identify and fix variable-related errors in your code.

In this article, we learned about Python variables, including their definition, importance, and how to create and initialize them. We also explored different data types, type conversion, and variable scope. We discussed best practices for using variables in Python, and common variable-related errors and debugging tips.

Variables are an essential concept in programming and are used to store values that can be used later in the code. By following best practices for variable naming and scope, you can write clean and readable code. Understanding how to use variables correctly can help you write more efficient and effective programs.

What are variables in Python?

Variables in Python are containers that hold values, such as numbers, strings, lists, or other data types. They are used to store and manipulate data within a program.

What is an example of a variable in Python?

An example of a variable in Python is “x”, which can hold a numerical value, such as “5”, or a string value, such as “Hello, World!”

What is a variable?

A variable is a symbolic name that represents a value or data item stored in memory that can be used and manipulated by a program.

What is an array in Python?

In Python, an array is a data structure that stores a fixed-size sequential collection of elements of the same type, such as integers or floats. It is commonly used for numerical computations and data analysis.

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Chelsea Troy

How to implement variable assignment in a programming language.

I’m working my way through Crafting Interpreters . The project guides programmers through building their own interpreters for the Lox programming language. I started writing a blog series about my progress. You can see all the posts so far right here .

In the last post covering part of Chapter 7, we talked about error handling, at that time largely in the context of parsing and interpreting expressions.

Now in Chapter 8 we get into some of the fun stuff—state.

I have talked about state a couple of times in the past on this blog—in particular, here , during the series about the book Structure and Interpretation of Computer Programs. If you like this series, you’ll probably like that one 😉.

The short version:

Procedural code without state—for example, a stateless function—amounts to a series of substitution operations in which an argument name serves as a placeholder that gets substituted at runtime with the passed-in inputs. The same inputs always result in the same output, and this makes the function “pure.” (In Crafting Interpreters , Bob Nystrom points out what we’re all thinking: that the programmers who wax poetic about their devotion to dispassionate logic also label said functions with such weighty language as “pure.”)

Add state, though, and this changes . Bob equates the presence of state to the Lox programming language’s “memory.” And just like a human memory, it influences statements’ behavior. The result from print a depends on what we assigned to a .

It also means that the programming language has to recognize a , which we can accomplish by:

Parsing some assignment syntax like var a = "Hallo!"
Interpreting that assignment syntax by assigning a key a in a key-value store to point to the value "Hallo!"

The key-value store doesn’t have to be all that fancy.

In the 80 line Scheme interpreter that we talked about in this previous post , we use a plain Python dictionary for the task. In fact, Python itself used dicts to delineate scope in early versions ( here’s the PEP where Python solidified the thrust of their current approach to state scoping, back in version 2.1). In Crafting Interpreters , Bob does similar:

The Environment class wraps a plain Java HashMap . Two methods wrap the HashMap ‘s put and get functions with semantically relevant names. That’s it.

This implementation of Environment supports only global scope: there’s one environment, all its variables are accessible everywhere, and either they’re in there or they’re not. Later, when we endeavor to include nested scopes, Environment gets a new attribute—a reference to another Environment , set to nil for the global scope—and when a variable is referenced, the environments check themselves and then, recursively, their enclosing environments, until they reach the global one.

I’ll bring up that SICP post one more time here because we do something similar in that implementation, although we copy the parent environment rather than referencing it:

For nested expressions, our nested environments are recursively passed through, first to seval (which evaluates expressions), then back into a new environment if evaluation reveals another procedure. …we’re slapping our new local env on top of a copy of the existing environment, and for a huge environment that will be really space inefficient. We’ve talked on this blog before about a similar situation: tracking nested transactions in an implementation of an in-memory database . If this were a real interpreter and not a toy for learning purposes, I might turn to a solution like that one. Note that the nested scopes wouldn’t face that annoying deletion snafu we faced with the database: local scopes can overwrite the values of variables from broader scopes, but they don’t delete them.

So the implementation isn’t super clever.

P.S. If you’re interested in trying out implementing a nested scope yourself, I gotchu! Here’s an interactive activity that I wrote for my Python Programming students to practice implementing database transactions for a pet shop database (complete with fun, dancing parrots!). It’s level-appropriate for someone who is comfortable using dictionaries/hashmaps/associative arrays in at least one modern (last updated after 2012) object-oriented programming language. To get this running locally, go to your command line and do:

git clone https://github.com/MPCS-51042/materials.git
cd materials
pip install jupyter (there’s also a pipfile if you’re a pipenv user, but I don’t want folks who aren’t regular Pythonistas to have to screw around with virtual environments just to try this exercise)
jupyter notebook (this is going to open a tab in your browser with a list of folders)
Navigate to materials > database_efficiency_exercise > 2_Transactions_(Space_Efficiency).ipynb
The file is a REPL: you can run any of the code cells with SHIFT + ENTER. I recommend starting by going to the top bar and clicking Kernel > Restart and Run All. This will run the code I have provided so you have the Table implementation available in scope, for example.
Try out the activity! I have tried to make the instructions as clear as possible and would welcome feedback on whether you were able to complete the exercise on your own 😊

A simple implementation does not mean an absence of decisions, by the way.

From this chapter of Crafting Interpreters about variable declaration and assignment, one of the things I most appreciated was the time that Bob took to consider the decisions that programming language authors make about how variable referencing and assignment work. Let’s go over some of those decisions:

1. Will the language use lexical or dynamic scope for variables?

That is, will the are over which the variable is defined by visible in the structure of the code and predictable before runtime ( lexical scope )? In most modern programming languages, it is. But we can see an example of dynamic scope with methods on classes. Suppose we have two classes that each possess a method with the same signature, and a function takes in either of those two classes as an argument. Which of the twin methods is in scope at runtime depends on which class the argument passed to the function is an instance of. That class’s method is in scope. The other class’s method is not in scope.

Lexical scope allows us to use specific tokens to identify when to create a new child environment. In Lox, we use curly braces for this {} , as do Swift and Java. Ruby also functions with curly braces, although using do..end is more idiomatic. Python determines scope with level of indentation.

2. Will the language allow variable reassignment?

If we want immutable data that has no chance of changing out from under a programmer, then we can insist that the value of a variable remain the same after it is created until it is destroyed. Haskell does its best to force this, and constants in many languages aim to provide this option.

Most programming languages allow for mutable variables, though, that programmers can define once and then reassign later. Many of them distinguish these from constants with a specific keyword. For example, JavaScript provides const for immutable constant declaration and var for mutable variable declaration. Swift does the same with let and var . Kotlin does it with val and var (“var” is a very popular choice for this).

3. Will the language allow referencing undeclared variables?

What happens if a programmer says print a; and no a has been declared? Lox raises an error at compile time. Ruby, by contrast, allows it. In Ruby, puts a where a is not declared will print nothing, but it won’t error out. puts a.inspect will print nil . Bob calls this strategy “too permissive for me” in the chapter. I…tend to agree, but I also don’t relish being all the way at the other end, say, at Java 6, where we had to null check everything in perpetual fear of the dreaded Null Pointer Exception.

I’m a fan of the Optional paradigm that we’ve seen in some more modern programming language implementations like Java 8, Swift, and Kotlin. I want to know if a variable could be null so I can handle it appropriately.

4. Will the language allow implicit variable declaration?

Lox distinguishes between declaring a new variable ( var a = "What's"; ) and assigning it a new value ( a = "Up?" ;). Without that var keyword, it will assume the intent is to reassign, and it will raise an error at compile time because the variable is not yet declared.

Ruby and Python, by contrast, assume that an assignment to a variable that does not yet exist means declare it . So a = 1 in Ruby sets 1 to a if a is nil, and reassigns a to point to 1 if it was previously pointing to something else.

Convenient, for sure. But in my experience, this does open programmers up to more scope-related insidious bugs because an initialization of a local variable and a reassignment of a global one look the same.

Languages might always differ on some of these questions.

And that’s okay: different languages serve different purposes and different communities. A programming language author can establish and communicate a perspective on a language’s purpose and use cases, then allow those decisions to drive implementation choices.

If you liked this piece, you might also like:

This talk about what counts as a programming language , explained with a raccoon stealing catfood from a cat…somehow

The Raft series, of course! Learn to implement a distributed system from the comfort of your home, complete with gifs and smack talk!

Lessons from Space: Edge Free Programming —about what launchpads have in common with software, and what that means for you and your work!

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Python Tutorials

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Python Data Types

In computer programming, data types specify the type of data that can be stored inside a variable. For example,

Here, 24 (an integer) is assigned to the num variable. So the data type of num is of the int class.

Since everything is an object in Python programming, data types are actually classes and variables are instances(object) of these classes.

Python Numeric Data type

In Python, numeric data type is used to hold numeric values.

Integers, floating-point numbers and complex numbers fall under Python numbers category. They are defined as int , float and complex classes in Python.

int - holds signed integers of non-limited length.
float - holds floating decimal points and it's accurate up to 15 decimal places.
complex - holds complex numbers.

We can use the type() function to know which class a variable or a value belongs to.

Let's see an example,

In the above example, we have created three variables named num1 , num2 and num3 with values 5 , 5.0 , and 1+2j respectively.

We have also used the type() function to know which class a certain variable belongs to.

5 is an integer value, type() returns int as the class of num1 i.e <class 'int'>
2.0 is a floating value, type() returns float as the class of num2 i.e <class 'float'>
1 + 2j is a complex number, type() returns complex as the class of num3 i.e <class 'complex'>
Python List Data Type

List is an ordered collection of similar or different types of items separated by commas and enclosed within brackets [ ] . For example,

Here, we have created a list named languages with 3 string values inside it.

Access List Items

To access items from a list, we use the index number (0, 1, 2 ...) . For example,

In the above example, we have used the index values to access items from the languages list.

languages[0] - access first item from languages i.e. Swift
languages[2] - access third item from languages i.e. Python

To learn more about lists, visit Python List .

Python Tuple Data Type

Tuple is an ordered sequence of items same as a list. The only difference is that tuples are immutable. Tuples once created cannot be modified.

In Python, we use the parentheses () to store items of a tuple. For example,

Here, product is a tuple with a string value Xbox and integer value 499.99 .

Access Tuple Items

Similar to lists, we use the index number to access tuple items in Python . For example,

To learn more about tuples, visit Python Tuples .

Python String Data Type

String is a sequence of characters represented by either single or double quotes. For example,

In the above example, we have created string-type variables: name and message with values 'Python' and 'Python for beginners' respectively.

To learn more about strings, visit Python Strings .

Python Set Data Type

Set is an unordered collection of unique items. Set is defined by values separated by commas inside braces { } . For example,

Here, we have created a set named student_info with 5 integer values.

Since sets are unordered collections, indexing has no meaning. Hence, the slicing operator [] does not work.

To learn more about sets, visit Python Sets .

Python Dictionary Data Type

Python dictionary is an ordered collection of items. It stores elements in key/value pairs.

Here, keys are unique identifiers that are associated with each value.

In the above example, we have created a dictionary named capital_city . Here,

Keys are 'Nepal' , 'Italy' , 'England'
Values are 'Kathmandu' , 'Rome' , 'London'

Access Dictionary Values Using Keys

We use keys to retrieve the respective value . But not the other way around. For example,

Here, we have accessed values using keys from the capital_city dictionary.

Since 'Nepal' is key, capital_city['Nepal'] accesses its respective value i.e. Kathmandu

However, 'Kathmandu' is the value for the 'Nepal' key, so capital_city['Kathmandu'] throws an error message.

To learn more about dictionaries, visit Python Dictionary .

Introduction

Sorry about that.

Python Operators: Arithmetic, Assignment, Comparison, Logical, Identity, Membership, Bitwise

Operators are special symbols that perform some operation on operands and returns the result. For example, 5 + 6 is an expression where + is an operator that performs arithmetic add operation on numeric left operand 5 and the right side operand 6 and returns a sum of two operands as a result.

Python includes the operator module that includes underlying methods for each operator. For example, the + operator calls the operator.add(a,b) method.

Above, expression 5 + 6 is equivalent to the expression operator.add(5, 6) and operator.__add__(5, 6) . Many function names are those used for special methods, without the double underscores (dunder methods). For backward compatibility, many of these have functions with the double underscores kept.

Python includes the following categories of operators:

Arithmetic Operators

Assignment operators, comparison operators, logical operators, identity operators, membership test operators, bitwise operators.

Arithmetic operators perform the common mathematical operation on the numeric operands.

The arithmetic operators return the type of result depends on the type of operands, as below.

If either operand is a complex number, the result is converted to complex;
If either operand is a floating point number, the result is converted to floating point;
If both operands are integers, then the result is an integer and no conversion is needed.

The following table lists all the arithmetic operators in Python:

The assignment operators are used to assign values to variables. The following table lists all the arithmetic operators in Python:

The comparison operators compare two operands and return a boolean either True or False. The following table lists comparison operators in Python.

The logical operators are used to combine two boolean expressions. The logical operations are generally applicable to all objects, and support truth tests, identity tests, and boolean operations.

The identity operators check whether the two objects have the same id value e.i. both the objects point to the same memory location.

The membership test operators in and not in test whether the sequence has a given item or not. For the string and bytes types, x in y is True if and only if x is a substring of y .

Bitwise operators perform operations on binary operands.

Compare strings in Python
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Convert String to Datetime in Python
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Remove duplicate items from list in Python
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Different Types of Variables in Python with Examples

Types of variables in python.

Variable Types in Python are just reserved memory spaces for storing values. This means that when you create a variable, you reserve memory space.

Python is entirely object-oriented and is not “statically typed.” You do not need to declare variables or declare their type before utilizing them.

These are some of the common types of variables in Python.

Assigning Values to Variables

Assigning values to variables in Python is a fundamental concept. It allows you to store and manipulate data within your code.

To assign a value to a variable, you can use the assignment operator “=”.

The name of the variable is the operand to the left of the = operator, and the value stored in the variable is the operand to the right of the = operator.

For instance:

In this case, the values for the counter, miles, and name variables are 100, 98.5, and “Prince” , respectively.

This causes the following to happen:

Multiple Assignment

In Python, you can assign values to multiple variables in a single line using multiple assignments.

This allows concise assignment to multiple variables simultaneously.

In this case, we’re creating an integer object of type 1 and setting all three variables to the same address in memory.

Multi-object assignments to multiple variables are also supported.

For example:

Here, the variables x and y are given the values 1 and 2 , respectively, and the variable z is given the value “ prince ” from a string object.

Different Types of Variables in Python

In Python, there are different types of variables that you can use to store and manipulate data.

Here are some common types of variables:

1. Python Numbers

In Python, the Numbers variable type or data type holds values that number. You make a number object when you give it a value.

You can also use the del statement to remove the reference to a number object.

The del statement’s syntax is:

The del statement lets you delete a single object or a group of objects.

Python can work with four different kinds of numbers.

int (signed integers)
long (long integers, they can also be represented in octal and hexadecimal)
float (floating point real values)
complex (complex numbers)

Here are some examples of the numbers:

Python lets you use a lowercase l with a long, but you should only use an uppercase L to avoid getting confused with the number 1. Python shows long numbers with the capital letter L.
A complex number is made up of two real floating-point numbers in the right order. It is written as x + yj, where x and y are the real numbers and j is the imaginary unit.

2. Python Strings

Python strings are a data type used to represent sequences of characters. They are enclosed in single (‘ ‘) or double (” “) quotes.

Also, in Python, you can extract parts of strings using the slice operator ([] and [:]) and index positions that range from 0 to -1.

Moreover, the plus sign (+) is used to join strings together, and the asterisk (*) is used to repeat something.

3. Python Lists

Python Lists are the most useful compound variable type. The items in a list are separated by commas and put inside square brackets ([]).

This leads to the following:

4. Python Tuples

Python tuple is an ordered collection of elements, similar to a list.

However, tuples are immutable, meaning their values cannot be changed once assigned.

Tuples are created by enclosing items in parentheses ( ) and separating them with commas.

5. Python Dictionary

The Python Dictionary is kind of like hash tables. They are made up of key-value pairs and work like associative arrays or hashes in Perl.

A dictionary key can be almost any type in Python, but numbers and strings are the most common.

How to check the type of variable in Python

You can check the type of a variable in Python, using the built-in type() function. The type() function returns the data type of the specified variable.

Here’s an example of how to use the type() function to check the type of a variable:

In the above examples, the type() function is called with the variable as an argument, and it returns the corresponding data type enclosed in.

In summary, we explored the Types of Variables in Python which is a reserved memory space. Also, we learned how to assign variables, including multiple Assignments .

Python Basic Syntax

Python Operators

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Introduction

Tuples are basically a data type in python . These tuples are an ordered collection of elements of different data types. Furthermore, we represent them by writing the elements inside the parenthesis separated by commas. We can also define tuples as lists that we cannot change. Therefore, we can call them immutable tuples. Moreover, we access elements by using the index starting from zero. We can create a tuple in various ways. Here, we will study tuple assignment which is a very useful feature in python.

In python, we can perform tuple assignment which is a quite useful feature. We can initialise or create a tuple in various ways. Besides tuple assignment is a special feature in python. We also call this feature unpacking of tuple.

The process of assigning values to a tuple is known as packing. While on the other hand, the unpacking or tuple assignment is the process that assigns the values on the right-hand side to the left-hand side variables. In unpacking, we basically extract the values of the tuple into a single variable.

Moreover, while performing tuple assignments we should keep in mind that the number of variables on the left-hand side and the number of values on the right-hand side should be equal. Or in other words, the number of variables on the left-hand side and the number of elements in the tuple should be equal. Let us look at a few examples of packing and unpacking.

Tuple Packing (Creating Tuples)

We can create a tuple in various ways by using different types of elements. Since a tuple can contain all elements of the same data type as well as of mixed data types as well. Therefore, we have multiple ways of creating tuples. Let us look at few examples of creating tuples in python which we consider as packing.

Example 1: Tuple with integers as elements

Example 2: Tuple with mixed data type

Example 3: Tuple with a tuple as an element

Example 4: Tuple with a list as an element

If there is only a single element in a tuple we should end it with a comma. Since writing, just the element inside the parenthesis will be considered as an integer.

For example,

Correct way of defining a tuple with single element is as follows:

Moreover, if you write any sequence separated by commas, python considers it as a tuple.

Browse more Topics Under Tuples and its Functions

Immutable Tuples
Creating Tuples
Initialising and Accessing Elements in a Tuple
Tuple Slicing
Tuple Indexing
Tuple Functions

Tuple Assignment (Unpacking)

Unpacking or tuple assignment is the process that assigns the values on the right-hand side to the left-hand side variables. In unpacking, we basically extract the values of the tuple into a single variable.

Frequently Asked Questions (FAQs)

Q1. State true or false:

Inserting elements in a tuple is unpacking.

Q2. What is the other name for tuple assignment?

A2. Unpacking

Q3. In unpacking what is the important condition?

A3. The number of variables on the left-hand side and the number of elements in the tuple should be equal.

Q4. Which error displays when the above condition fails?

A4. ValueError: not enough values to unpack

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Initialising and Accessing Elements in Tuple

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Data Visualization

Statistics in R
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Packages in R

R Tutorial | Learn R Programming Language

Introduction

R Programming Language - Introduction
Interesting Facts about R Programming Language
R vs Python
Environments in R Programming
Introduction to R Studio
How to Install R and R Studio?
Creation and Execution of R File in R Studio
Clear the Console and the Environment in R Studio
Hello World in R Programming

Fundamentals of R

Basic Syntax in R Programming
Comments in R
R Operators
R - Keywords
R Data Types
R Variables - Creating, Naming and Using Variables in R
Scope of Variable in R
Dynamic Scoping in R Programming
Lexical Scoping in R Programming

Input/Output

Taking Input from User in R Programming
Printing Output of an R Program
Print the Argument to the Screen in R Programming - print() Function

Control Flow

Control Statements in R Programming
Decision Making in R Programming - if, if-else, if-else-if ladder, nested if-else, and switch
Switch case in R
For loop in R
R - while loop
R - Repeat loop
goto statement in R Programming
Break and Next statements in R
Functions in R Programming
Function Arguments in R Programming
Types of Functions in R Programming
Recursive Functions in R Programming
Conversion Functions in R Programming

Data Structures

Data Structures in R Programming
R - Matrices
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Object Oriented Programming

R - Object Oriented Programming
Classes in R Programming
R - Objects
Encapsulation in R Programming
Polymorphism in R Programming
R - Inheritance
Abstraction in R Programming
Looping over Objects in R Programming
S3 class in R Programming
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Error Handling

Handling Errors in R Programming
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Debugging in R Programming

File Handling

File Handling in R Programming
Reading Files in R Programming
Writing to Files in R Programming
Working with Binary Files in R Programming
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Grid and Lattice Packages in R Programming
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What Are the Tidyverse Packages in R Language?
Data Munging in R Programming

Data Interfaces

Data Handling in R Programming
Importing Data in R Script
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Working with CSV files in R Programming
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Mean, Median and Mode in R Programming
Calculate the Average, Variance and Standard Deviation in R Programming
Descriptive Analysis in R Programming
Normal Distribution in R
Binomial Distribution in R Programming
ANOVA (Analysis of Variance) Test in R Programming
Covariance and Correlation in R Programming
Skewness and Kurtosis in R Programming
Hypothesis Testing in R Programming
Bootstrapping in R Programming
Time Series Analysis in R

Machine Learning

Introduction to Machine Learning in R
Setting up Environment for Machine Learning with R Programming
Supervised and Unsupervised Learning in R Programming
Regression and its Types in R Programming
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Naive Bayes Classifier in R Programming
KNN Classifier in R Programming
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Deep Learning in R Programming

R Variables – Creating, Naming and Using Variables in R

A variable is a memory allocated for the storage of specific data and the name associated with the variable is used to work around this reserved block.

The name given to a variable is known as its variable name . Usually a single variable stores only the data belonging to a certain data type.

The name is so given to them because when the program executes there is subject to change hence it varies from time to time.

Variables in R

R Programming Language is a dynamically typed language, i.e. the R Language Variables are not declared with a data type rather they take the data type of the R-object assigned to them.

This feature is also shown in languages like Python and PHP.

Creating Variables in R Language

Let’s look at ways of declaring and initializing variables in R language:

R supports three ways of variable assignment:

Using equal operator- operators use an arrow or an equal sign to assign values to variables.
Using the leftward operator- data is copied from right to left.
Using the rightward operator- data is copied from left to right.

Syntax for creating R Variables

Types of Variable Creation in R:

Using equal to operators variable_name = value using leftward operator variable_name <- value using rightward operator value -> variable_name

Creating Variables in R With Example

Let’s look at the live example of creating Variables in R:

Nomenclature of R Variables

The following rules need to be kept in mind while naming a R variable:

A valid variable name consists of a combination of alphabets, numbers, dot(.), and underscore(_) characters. Example: var.1_ is valid
Apart from the dot and underscore operators, no other special character is allowed. Example: var$1 or var#1 both are invalid
Variables can start with alphabets or dot characters. Example: .var or var is valid
The variable should not start with numbers or underscore. Example: 2var or _var is invalid.
If a variable starts with a dot the next thing after the dot cannot be a number. Example: .3var is invalid
The variable name should not be a reserved keyword in R. Example: TRUE, FALSE,etc.

Important Methods for R Variables

R provides some useful methods to perform operations on variables. These methods are used to determine the data type of the variable, finding a variable, deleting a variable, etc. Following are some of the methods used to work on variables:

1. class() function

This built-in function is used to determine the data type of the variable provided to it.

The R variable to be checked is passed to this as an argument and it prints the data type in return.

2. ls() function

This built-in function is used to know all the present variables in the workspace.

This is generally helpful when dealing with a large number of variables at once and helps prevents overwriting any of them.

Syntax

3. rm() function

This is again a built-in function used to delete an unwanted variable within your workspace.

This helps clear the memory space allocated to certain variables that are not in use thereby creating more space for others. The name of the variable to be deleted is passed as an argument to it.

Syntax

Example

Scope of Variables in R programming

The location where we can find a variable and also access it if required is called the scope of a variable . There are mainly two types of variable scopes:

1. Global Variables

Global variables are those variables that exist throughout the execution of a program. It can be changed and accessed from any part of the program.

As the name suggests, Global Variables can be accessed from any part of the program.

They are available throughout the lifetime of a program.
They are declared anywhere in the program outside all of the functions or blocks.

Declaring global variables

Global variables are usually declared outside of all of the functions and blocks. They can be accessed from any portion of the program.

In the above code, the variable ‘ global’ is declared at the top of the program outside all of the functions so it is a global variable and can be accessed or updated from anywhere in the program.

2. Local Variables

Local variables are those variables that exist only within a certain part of a program like a function and are released when the function call ends. Local variables do not exist outside the block in which they are declared, i.e. they can not be accessed or used outside that block.

Declaring local variables

Local variables are declared inside a block.

Difference between local and global variables in R

Scope A global variable is defined outside of any function and may be accessed from anywhere in the program, as opposed to a local variable.
Lifetime A local variable’s lifetime is constrained by the function in which it is defined. The local variable is destroyed once the function has finished running. A global variable, on the other hand, doesn’t leave memory until the program is finished running or the variable is explicitly deleted.
Naming conflicts If the same variable name is used in different portions of the program, they may occur since a global variable can be accessed from anywhere in the program. Contrarily, local variables are solely applicable to the function in which they are defined, reducing the likelihood of naming conflicts.
Memory usage Because global variables are kept in memory throughout program execution, they can eat up more memory than local variables. Local variables, on the other hand, are created and destroyed only when necessary, therefore they normally use less memory.

We have covered the concept of “ Variables in R ” to give you overview of R variables. How to create variables in R?, how to use variables in R? and all the other questions have been answered in this article.

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Python Variable Assignment. Explaining One Of The Most Fundamental
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Variable Assignment in Python. Python variables are created when a value is assigned to them using the equals sign (=) operator. For example, the following code snippet assigns the integer value 5 to the variable x: x = 5. From this point forward, whenever x is referenced in the code, it will have the value 5.
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In the previous lesson (1.3 -- Introduction to objects and variables), we covered how to define a variable that we can use to store values.In this lesson, we'll explore how to actually put values into variables and use those values. As a reminder, here's a short snippet that first allocates a single integer variable named x, then allocates two more integer variables named y and z:
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The example in the previous code contains three assignments. The first one assigns the value of the expression 40 + 2 to a new variable called magicnumber; the second one assigns the value of π to the variable pi, and; the last assignment assigns the string value 'Data is eatig the world' to the variable message.
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To create a variable, you just assign it a value and then start using it. Assignment is done with a single equals sign ( = ): Python. >>> n = 300. This is read or interpreted as " n is assigned the value 300 .". Once this is done, n can be used in a statement or expression, and its value will be substituted: Python.
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Python Variables – A Guide to Variable Assignment and Naming

Key Takeaways

Variable Assignment in Python

Common Mistakes in Variable Assignment

Using Variables in Python

Variable Naming Conventions in Python

Scope of Variables in Python

Local Variables in Python

Global Variables in Python

Mathematical Calculations

String Manipulation

Working with Data Structures

Variable Types in Python

Numeric Types:

Sequence Types:

Mapping Types:

Boolean Type:

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Variables, Expressions, and Assignments

Values and Types #

Expressions and Statements #

Assignment Statements #

Names and Keywords #

Reassignments #

Updating Variables #

Order of Operations #

Floor Division and Modulus Operators #

String Operations #

Asking the User for Input #

Script Mode #

Python Variables and Assignment

Variables and Assignment

Questions #

Learning Objectives #

Use variables to store values. #

Use print to display values. #

Variables must be created before they are used. #

Variables persist between cells #

Variables can be used in calculations. #

Python is case-sensitive. #

Use meaningful variable names. #

Exercises #

What’s in a name? #

Variables only change value when something is assigned to them #

Swapping Values #

Key Points Summary: #

Introduction to Programming

Rules and conventions for naming variables in python

Typical way we visualize variables

Types of variables

Creating a variable with an assignment operator

Finding out the type of a variable or value

Casting (changing the type) of a variable or value

Doing arithmetic in python

Order of operations

AP®︎/College Computer Science Principles

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Variables in Python

Important Rules while Creating Variables

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Reassigning variables

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