#Python splice how to#
#Python splice code#

We have just selected all the elements as required! :) Consolidate Step 1 (start and end) and Step 2 ('jumping')

#Python splice code#

In code (note the double colons): In : X3 = X2 We can now specify the 'jump steps' in both row-wise and column-wise directions (to select elements in a 'jumping' way) like this: (read on!) Step 2 - Select elements (with the 'jump step' argument) Notice now we've just obtained our subset, with the use of simple start and end indexing technique. Specify the 'start index' and 'end index' in both row-wise and column-wise directions. Read on! (We can do this in a 2-step approach) Step 1 - Obtain subset Say for some reason, your boss wants you to select the following elements: Say we have a NumPy matrix that looks like this: In : import numpy as np This example does not cover native Python data structures like List). (Caution: this is a NumPy array specific example with the aim of illustrating the a use case of 'double colons' :: for jumping of elements in multiple axes. Step 2 below illustrate the usage of that 'double colons' :: in question.

#Python splice how to#

Understanding the flexible way of slicing can simplify the manipulation of data.This visual example will show you how to a neatly select elements in a NumPy Matrix (2 dimensional array) in a pretty entertaining way (I promise). Using the slice function or object makes the code more readable. The slice object is reusable, one can use the slice function to encapsulate the slice logic start, stop, and step parameters and create a slice object based on the logic that can be used to extract data from a number of sequences. The slice function in Python is a powerful tool that provides an efficient and flexible way to extract data from a sequence. You can leave any of these parameters or use negative indices for the same.

Flexibility - The slice function takes three parameters start, stop, and steps.

Readability - The slice object is used to encapsulate the slicing logic, which enhances the readability of the code.

Reusability - Once created, the slice object can be applied to slice many sequences making it advantageous in terms of reusability.

Some of the main advantages of the slice function are as follows: In Python, the slice function offers many advantages while working with sequences or collections of data such as lists, tuples, or strings. Advantages of Slice() function in Python:

In the above example, both slicing methods extract every third element from the 'tup' starting from index 0 and ending at index 10 (exclusively).

Slicing using general slicing: (45, 1214, 636)

The general syntax of slicing is as follows: Slicing is a process of extracting data from a collection of data by specifying the starting and ending indices and steps to be taken. We must understand the concept of slicing.

Introduction to Slicing:īefore we deep dive into the Python slice function. For example, if we want to get the first two elements from the list of elements, here slice can be used. This slice object can be used to get a subsection of the collection. The first function takes a single argument, while the second function takes three arguments and returns a slice object. Python provides two overloaded slice functions. You can use the slice function to encapsulate slice logic, such as start, stop, and step parameters. The slice function offers a simple and effective method for extracting a portion of data and modifying data from a sequence of elements. The Python slice function is used to get a slice or a portion of elements from the collection of elements such as a list, tuple, or string. One such function is the Python slice() function. In Python, we have a number of inbuilt functions.