A list is the most flexible data structure in Python. Whereas, a 2D list which is commonly known as a list of lists, is a list object where every item is a list itself
A list is the most flexible data structure in Python. Whereas, a 2D list which is commonly known as a list of lists, is a list object where every item is a list itself - for example:
[[1,2,3], [4,5,6], [7,8,9]].
Flattening a list of lists entails converting a 2D list into a 1D list by un-nesting each list item stored in the list of lists - i.e., converting
[[1, 2, 3], [4, 5, 6], [7, 8, 9]] into
[1, 2, 3, 4, 5, 6, 7, 8, 9].
The process of flattening can be performed using nested for loops, list comprehensions, recursion, built-in functions or by importing libraries in Python depending on the regularity and depth of the nested lists.
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.
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. We gonna use Python OS remove( ) method to remove the duplicates on our drive. Well, that's simple you just call remove ( ) with a parameter of the name of the file you wanna remove done.
Learn about NumPy Array, NumPy Array creation, various array functions, array indexing & Slicing, array operations, methods and dimensions,It also includes array splitting, reshaping, and joining of arrays. Even the other external libraries in Python relate to NumPy arrays.
NumPy in Python explains what exactly is Numpy and how it is better than Lists. It also explains various Numpy operations with examples.
In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.