Python 3: Slicing(Efficient method to access elements) Explained

python-logoWelcome to 3rd post on Python. In this post, I’ll discuss slicing. Just as the name suggests, slicing is to slice data into parts and get the required part from that data. As you learn more and more Python, you’ll come across slicing in different data structures in different applications. So let’s get started.

Indexing

The most common indexing used in Python is 0-indexing(i.e: position of the element at leftmost position is 0 and increases by 1 as we move to right side). We can also access elements with -1 index(i.e: index of the element at the rightmost position is -1 and decrements by 1 as we move to left).

sentence = "This is a slicing example"
print(sentence[0])  #prints T
print(sentence[1])  #prints h
print(sentence[24]) #prints last e
print(sentence[-1]) #prints e
print(sentence[-2]) #prints l
print(sentence[-25])#prints T

In the above example, sentence[0] prints T, as we have used 0-index and sentence[-1] prints e which is the last element and this is due to -1 index.

Remember: 0-index starts at leftmost position and increments by 1 as we move to the right side and -1 index starts at rightmost position and decrements by 1 as we move to left side.

Accessing elements

Now as we know two forms of indexing used in Python, we can start accessing elements from any collection(string, list, tuple, dictionary). Syntax for slicing goes like this:

variable[start_position:end_position:step]
  • start_position: position to start accessing element. This position is inclusive, hence is included while accessing element.
  • end_position: position to stop accessing element. This is an exclusive, hence is not included while accessing element.
  • step: steps to increment the position while traversing through the collection. Step can be either negative or positive. Negative will access elements through left and positive will access elements through right.
countries = ["Nepal", "India", "USA", "China", "UK", "Canada", "Japan"]
print(countries[0])         #prints Nepal
print(countries[1:4])       #prints ['India', 'USA', 'China']
print(countries[0:6:2])     #prints ['Nepal', 'USA', 'UK']<span id="mce_SELREST_start" style="overflow:hidden;line-height:0;"></span>
print(countries[-5:-1:2])   #['USA', 'UK']
print(countries[4:0:-1])    #prints ['UK', 'China', 'USA', 'India']

In case of countries[0:6:2], elements from 0 till 6 index are printed with step of 2. Index 6 is exclusive and 0 is inclusive in this case. If we don’t give the value for step, then it is 1 by default(eg: countries[1:4])

countries[4:0:-1] is the example of negative step. It starts to print at index 4 and moves till 0. Step is being decreased by 1 in this case. Element at index 4 is inclusive and element at index 0 is exclusive.

Trick: Reverse with slicing

word="Hello"
rev = word[::-1]
print(rev)   #prints olleH

Since there are no start and end positions, all elements are printed. Due to step being -1, string is reversed.

Slice function

Slicing can also be used in the form of a function.  slice function takes the following syntax

slice(start_position, end_position, step)

numbers = [1, 2, 3, 4, 5, 6, 7]
s = slice(1, 4, 2)
print(numbers[s])

Here we’ve used slice function and assigned it to variable s. This is pretty easy to understand.

I would like to end the post here. I hope this post was helpful. Please leave comments for any queries and suggestions. I’ll see you in the next one. Cheers 🙂

 

Advertisements

One thought on “Python 3: Slicing(Efficient method to access elements) Explained

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s