Map Python Function

Python map() function with EXAMPLES

The map() method in Python takes an iterator as input and applies a function to each individual item in the iterator. For instance, an iterator can take the form of a list, tuple, set, dictionary, or string, and it returns an iterable map object. The map() function is a built-in feature of Python.
Syntax: map (function, iterator1,iterator2 …iteratorN)
Parameters
Here are two essential points:

function is a required function that must be provided to map and will be executed on each and every item that is accessible through the iterator.
Iterator: An iterable object that must be iterated. It could be a list, a tuple, or anything else. The map() function allows for multiple iterator objects to be passed as input.
Return Value
The map() function will run the specified function on each item that is contained within the iterator and return an iterable map object, which could be a tuple, a list, or something else entirely.

How exactly does the map() function work?

A function and an iterable object are both acceptable forms of input for the map() function. The code that is passed to the map() method is a regular function, and it will proceed to iterate over each of the values that are contained in the iterable object that is passed.

Take, as an illustration, the scenario in which you have a list of numbers and you wish to get the square of each of the numbers.

In order to obtain the output, we will require the function that calculates the square root of the specified value. The following will constitute the function:

def square(n): return n*n
The following is a list of things that we need to locate in order to discover the square:

my list = [2,3,4,5,6,7,8,9]
Let’s utilise the built-in method map() in Python to calculate the square root of each item in our my list collection.

The completed code will look like this:

function square(n): return n*n my list = [2,3,4,5,6,7,8,9]
updated list is same to map(square, my list) in algebra.
print(updated list)
print(list(updated list))
Output:

<map object at 0x0000002C59601748>
[4, 9, 16, 25, 36, 49, 64, 81]
The output of the map() function is a map object that is displayed on the screen as map object at 0x0000002C59601748>. This can be observed by looking at the output of the function.

In order to obtain the final result, you will need to either employ a for-loop that iterates the output from the map or use the list() method. In the code that displays the items contained in the provided list, I made use of the list() function.

Consequently, with the help of the map() function, we are able to calculate the square root of each value.

The following list was provided to map: [2,3,4,5,6,7,8,9]. And by making use of the square() function, we were able to obtain the output of map(), which was [4, 9, 16, 25, 36, 49, 64, 81].

The square() function is executed on each and every item in the list when the map() method is called. One example is the my list variable, which calculates and appends the square of each number to the list. The updated list variable is where the out is kept for storage.

Utilizing map() in conjunction with other built-in Python functions

The map() function is a built-in function in Python, and like all other built-in functions in Python, it can be combined with other built-in functions. In this demonstration, we will make use of the built-in Python method called round(), which rounds the values that are passed to it.

Example:

My list is represented by the following equation: my list = [2.6743,3.63526,4.2325,5.9687967,6.3265,7.6988,8.232,9.6907]

I need the values, rounded to the nearest whole number, for each item on the list. As the function to map, we will be making use of the round() method ().

my list = [2.6743,3.63526,4.2325,5.9687967,6.3265,7.6988,8.232,9 .6907]
updated list is equal to map(round, my list) in our example.
print(updated list)
print(list(updated list))
Output:

<map object at 0x000000E65F901748>
[3, 4, 4, 6, 6, 8, 8, 10]
The round() method is used on each and every item in the list, and it then returns a new list to the caller with all of the values rounded to the nearest integer. This is demonstrated in the output.

Employing map() while passing in a string as the iterator
We also have the option of using the map() function on a string. Because a string in Python behaves much like an array, we are able to easily use it within the map ().

In this demonstration, we make use of a function called myMapFunc(), which is responsible for changing all of the characters in the specified string to uppercase. The myMapFunc () function is what is passed along to the map() method. By forwarding the string to be converted to myMapFunc, the map function will ensure that the characters in the string are converted to uppercase ().

def myMapFunc(s):
my str is set to “welcome to guru99 tutorials!” if I use the function return s.upper().
updated list can be created by typing map(myMapFunc, my str).
print (updated list) for each iteration of the updated list variable:
print(i, end=””)
Output:

<map object at 0x000000DF2E711748>
WELCOME TO THE GURU99 TUTORIALS DISCUSSION BOARD!
Employing map() in conjunction with listof Numbers
In order to work with the list in map(), a list of numbers will be taken and then each number in the list will be multiplied by 10.

The following is the order in which we are going to use the items in the list: [2,3,4,5,6,7,8,9]. The operation of multiplying the given number by 10 is taken care of by the function myMapFunc (). In addition to the list, the function is also passed on to map.

Example:

def myMapFunc(n): return n*10

my list = [2,3,4,5,6,7,8,9]

updated list is equal to map(myMapFunc, my list) in this formula.
print(updated list)
print(list(updated list))
Output:

<map object at 0x000000EE2C061898>
[20, 30, 40, 50, 60, 70, 80, 90]
The output that we are presented with reveals that each number in the list is

increased by a factor of 10.

Using map() with Tuple
In Python, an object is referred to as a tuple if it contains items that are delimited by commas and surrounded in round brackets. In this demonstration, we will use a tuple that contains string values. The values that are passed into the function that we will employ will have their case changed to uppercase.

Example:

def myMapFunc(n): return n.upper ()

my tuple = (‘php’,’java’,’python’,’c++’,’c’)

updated list = map(myMapFunc, my tuple) is the formula for this.
print(updated list)
print(list(updated list)) \sOutput:

map object located at hexadecimal address 0x0000009C3C3A16A0
[‘PHP’, ‘JAVA’, ‘PYTHON’, ‘C++’, ‘C’] Programming languages
The result that we are given is a tuple with all of the items included within it having their case changed to uppercase.

Employing map() in conjunction with Dictionary
In Python, a dictionary is constructed with the help of curly brackets (). You are able to make use of the dictionary within the map() function due to the fact that the dictionary is an iterator. Inside of the map() function, let’s try using a dictionary as an iterator instead.

The following illustration demonstrates how the dictionary iterator works inside of map ()

def myMapFunc(n): return n*10
finalitems is equal to map(myMapFunc, my dict) if my dict contains the values 2, 3, 4, 5, 6, 7, 8, and 9.
print(finalitems)
print(list(finalitems))
Output:

<map object at 0x0000007EB451DEF0>
[20, 30, 40, 50, 60, 70, 80, 90]
Applying the map() function on a Set A Python set is an unordered collection of things enclosed in curly brackets (()). Because set() is also an iterator, you are free to utilise it within the context of the map() function.

An operational illustration of utilising set as an iterator within map can be seen here ()

def myMapFunc(n):
return n*10
my set = {2,3,4,5,6,7,8,9} finalitems = map(myMapFunc, my set)
print(finalitems)
print(list(finalitems))
Output:

<map object at 0x000000AC8F05DEF0>
[20, 30, 40, 50, 60, 70, 80, 90]
Utilizing map() in conjunction with the Lambda function
Expressions called lambdas are used in Python for the construction of anonymous functions. In the same way that you would use the def keyword to define regular functions, you will need to utilise the lambda keyword instead.

Therefore, in the demonstration, we will use the lambda function while we are inside the map (). The lambda function will perform a 10-times multiplication on each value in the list.

Example:

my list = [2,3,4,5,6,7,8,9]
updated list = map(lambda x: x * 10, my list)
print(updated list)
print(list(updated list))
Output:

<map object at 0x000000BD18B11898>
[20, 30, 40, 50, 60, 70, 80, 90]
Utilization of Multiple Iterators within the map() Function
Example 1: Iterators for two different lists are being given to map ()
You are able to pass the map() function more than one iterator at once, such as a list, a tuple, or something else along those lines.

For instance, if you wish to combine two different lists. Utilizing the map() function will accomplish the same thing. We are going to use two different lists, which we will refer to as my list1 and my list2.

In the example that follows, the first item from my list1 is appended to the first item from my list2, which results in the following sentence: The entries from both my list1 and my list2 are incorporated into the computation of the sum that is returned by the myMapFunc() method.

Using the map() method, below is a working example of adding two different lists that have been given.

def myMapFunc(list1, list2): return list1+list2

my list1 = [2,3,4,5,6,7,8,9]
my list2 = [4,8,12,16,20,24,28]

updated list is a formula that looks like this: map(myMapFunc, my list1, my list2)
print(updated list)
print(list(updated list))
Output:

<map object at 0x0000004D5F751860>
[6, 11, 16, 21, 26, 31, 36]
Example 2: One Tuple and a list iterator are being sent to map in this call ()
Within the scope of the map() function, we are going to make use of both a list and a tuple iterator. MyMapFunc() will retrieve the elements from both the list and the Tuple after it has been given the function by map. After that, an underscore (_) will be used to link the items together. The operational example is presented as follows:

def myMapFunc(list1, tuple1): return list1+” “+tuple1

my list = [‘a’,’b’, ‘b’, ‘d’, ‘e’]
my tuple equals “PHP,” “Java,” “Python,” “C++,” and “C.”

updated list is equal to map(myMapFunc, my list, and my tuple).
print(updated list)
print(list(updated list))
Output:

<map object at 0x00000059F37BB4E0>
(‘a PHP,’ ‘b Java,’ ‘b Python,’ ‘d C++,’ and ‘e C’)

Summary

The map() built-in function in Python is a function that applies a function to each individual item of an iterator that is passed in as input. For instance, an iterator can take the form of a list, a tuple, a string, or any other data structure, and it returns an iterable map object.
The map() function will run the specified function on each item that is contained within the iterator and return an iterable map object, which could be a tuple, a list, or something else entirely.
The map() function is a built-in function in Python, and like all other built-in functions in Python, it can be combined with other built-in functions.
In Python, an object is referred to as a tuple if it contains items that are delimited by commas and surrounded in round brackets. In this demonstration, we will use a tuple containing string values. The values that are passed into the function that we will employ will have their case changed to uppercase.
In Python, a dictionary is constructed with the help of curly brackets (). You are able to make use of the dictionary within the map() function due to the fact that the dictionary is an iterator.
A Python set is a collection of objects enclosed in curly brackets (()), but the contents are not sorted. Because set() is also an iterator, you are free to utilise it within the context of the map() function.
For the purpose of constructing anonymous functions in Python, lambda expressions, also known as lambda forms, are deployed. Therefore, if you wish to utilise lambda within the map, you are need to use the lambda keyword ().
When calling the map() function, you have the option of passing in multiple iterators, as well as lists and tuples.