filter() function takes a function and a sequence as arguments and returns an iterable, only yielding the items in sequence for which function returns True. If None is passed instead of a function, all the items of the sequence which evaluates to False are removed. The syntax of the
In this tutorial, you’ll learn how to use the
filter() function with different types of sequences. Also, you can refer to the examples that we’ve added to bring clarity.
The filter() function accepts only two parameters. The first argument is the name of a user-defined function, and second is iterable like a list, string, set, tuple, etc.
It calls the given function for every element of iterable, just like in a loop. It has the following syntax
# Python filter() syntax filter(in_function|None, iterable) |__filter object
The first parameter is a function which has a condition to filter the input. It returns True on success or False otherwise. However, if you provide a None, then it removes all items except those evaluate to True.
Next parameter is iterable, i.e., a sequence of elements to test against a condition. Each function call carries one item from the seq for testing.
The return value is a filter object a sequence having elements that passed the function check.
Here are some examples to explain how to use filter() function.
In this example, we have an iterable list of numeric values out of which some are even, and few are odd.
# list of numbers numbers = [1, 2, 4, 5, 7, 8, 10, 11]
Now, here is a function that filters out the odd number from the given list. We’ll be passing it as the first argument to the
# function that filters odd numbers def filterOddNum(in_num): if(in_num % 2) == 0: return True else: return False
Let’s now join the bricks and see the full working code:
""" Desc: Python program to filter odd numbers from the list using filter() function """ # list of numbers numbers = [1, 2, 4, 5, 7, 8, 10, 11] # function that filters vowels def filterOddNum(in_num): if(in_num % 2) == 0: return True else: return False # Demonstrating filter() to remove odd numbers out_filter = filter(filterOddNum, numbers) print("Type of filter object: ", type(out_filter)) print("Filtered seq. is as follows: ", list(out_filter))
A couple of points to notice in the example are:
After running the example, you should see the following outcome:
Type of filter object: <class 'filter'> Filtered seq. is as follows: [2, 4, 8, 10]
It printed only the even numbers filtering out the odd ones.
We can use
filter() function to get the difference between two sequences. For this, we’ve to filter out duplicate items.
So, let’s assume the following two list of strings.
You can check that given lists have common entries for some of the programming languages. So, we need to write a function that checks for duplicates names.
# function that filters duplicate string def filterDuplicate(string_to_check): if(string_to_check in ll): return False else: return True
Let’s now get all the bits and pieces together.
After executing the example, it produces the following result:
As desired, our code printed the difference between the two given lists. However, it was merely an illustration for learning how Python
filter() function works.
Python lambda expression also works as an inline function. Hence, we can specify it instead of a function argument in the
In this way, we can get away from writing a dedicated function for the filtering purpose.
Let’s consider some examples to see how to use lambda with
In this example, we are going to remove stop words from a given string. We’ve mentioned them in the below list.
list_of_stop_words = ["in", "of", "a", "and"]
Below is the string that contains the stop words.
string_to_process = "A citizen of New York city fought and won in the election."
Now, we’ll see the complete code to filter stop words.
""" Desc: Python program to remove stop words from string using filter() function """ # List of stop words list_of_stop_words = ["in", "of", "a", "and"] # String containing stop words string_to_process = "a citizen of New York city fought and won in the election." # Lambda expression that filters stop words split_str = string_to_process.split() filtered_str = ' '.join((filter(lambda s: s not in list_of_stop_words, split_str))) print("Filtered seq. is as follows: ", filtered_str)
Since we had to remove a whole word, so we split the string into words. After that, we filtered the stop words and joined the rest.
You should get the following outcome after execution:
Filtered seq. is as follows: citizen New York city fought won the election.
In this example, we’ll create a lambda expression and apply filter() function to find the common elements in two arrays.
Below is the input data for our test.
# Defining two arrays having some common elements arr1 = ['p','y','t','h','o','n',' ','3','.','0'] arr2 = ['p','y','d','e','v',' ','2','.','0']
Let’s create the lambda expression that will filter the difference and return common elements.
# Lambda expression using filter() to find common values out = list(filter(lambda it: it in arr1, arr2))
Now, we’ll see the full implementation:
""" Desc: Python program to find common items in two arrays using lambda and filter() function """ # Defining two arrays having some common elements arr1 = ['p','y','t','h','o','n',' ','3','.','0'] arr2 = ['p','y','d','e','v',' ','2','.','0'] def interSection(arr1, arr2): # find identical elements # Lambda expression using filter() to find common values out = list(filter(lambda it: it in arr1, arr2)) return out # Main program if __name__ == "__main__": out = interSection(arr1, arr2) print("Filtered seq. is as follows: ", out)
You should get the following outcome after execution:
Filtered seq. is as follows: ['p', 'y', ' ', '.', '0']
Yes, you can call
filter() without passing an actual function as the first argument. Instead, you can specify it as None.
When None is specified in the
filter(), then it pops out all elements that evaluate to False. Let’s consider the following list for illustration:
# List of values that could be True or False bools = ['bool', 0, None, True, False, 1-1, 2%2]
Here is the full code to analyze the behavior of
filter() with None as the function argument.
""" Desc: Calling filter() function without a function """ # List of values that could True or False bools = ['bool', 0, None, True, False, 1, 1-1, 2%2] # Pass None instead of a function in filter() out = filter(None, bools) # Print the result for iter in out: print(iter)
The following is the result after execution:
bool True 1
We hope that after wrapping up this tutorial, you should feel comfortable in using the Python
filter() function. However, you may practice more with examples to gain confidence.
Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.
Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is
Syntax: x = lambda arguments : expression
Now i will show you some python lambda function examples:
#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map
Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.
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Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?
In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.
Swapping value in Python
Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead
>>> FirstName = "kalebu" >>> LastName = "Jordan" >>> FirstName, LastName = LastName, FirstName >>> print(FirstName, LastName) ('Jordan', 'kalebu')
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Today you’re going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates.
In many situations you may find yourself having duplicates files on your disk and but when it comes to tracking and checking them manually it can tedious.
Heres a solution
Instead of tracking throughout your disk to see if there is a duplicate, you can automate the process using coding, by writing a program to recursively track through the disk and remove all the found duplicates and that’s what this article is about.
But How do we do it?
If we were to read the whole file and then compare it to the rest of the files recursively through the given directory it will take a very long time, then how do we do it?
The answer is hashing, with hashing can generate a given string of letters and numbers which act as the identity of a given file and if we find any other file with the same identity we gonna delete it.
There’s a variety of hashing algorithms out there such as
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Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc…
You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like init, call, str etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).
Now there are a number of such special methods, which you might have come across too, in Python. We will just be taking an example of a few of them to understand how they work and how we can use them.
class AnyClass: def __init__(): print("Init called on its own") obj = AnyClass()
The first example is _init, _and as the name suggests, it is used for initializing objects. Init method is called on its own, ie. whenever an object is created for the class, the init method is called on its own.
The output of the above code will be given below. Note how we did not call the init method and it got invoked as we created an object for class AnyClass.
Init called on its own
Let’s move to some other example, add gives us the ability to access the built in syntax feature of the character +. Let’s see how,
class AnyClass: def __init__(self, var): self.some_var = var def __add__(self, other_obj): print("Calling the add method") return self.some_var + other_obj.some_var obj1 = AnyClass(5) obj2 = AnyClass(6) obj1 + obj2
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