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Graph Theory and Graph-Related Algorithm's Theory and Implementation
Graphs are an extremely versatile data structure. More so than most people realize! Graphs can be used to model practically anything, given their nature of modeling relationships and hierarchies. Nature and human creators are extremely hierarchical. Words in a sentence, and sentences in a book can be graphs - represented...
Python with Pandas: DataFrame Tutorial with Examples
Pandas is an open-source Python library for data analysis. It is designed for efficient and intuitive handling and processing of structured data. The two main data structures in Pandas are Series and DataFrame. Series are essentially one-dimensional labeled arrays of any type of data, while DataFrames are two-dimensional, with potentially...
Guide to Basic Data Types in Python with Examples
In this article, we'll be diving into the Basic Data Types in Python. These form some of the fundamental ways you can represent data. One way to categorize these basic data types is in one of four groups: Numeric: int, float and the less frequently encountered complex Sequence: str (string)...
'is' vs '==' in Python - Object Comparison
Python has two very similar operators for checking whether two objects are equal. These two operators are is and ==. They are usually confused with one another because with simple data types, like ints and strings (which many people start learning Python with) they seem to do the same thing: x...
any() and all() in Python with Examples
In this tutorial, we'll be covering the any() and all() functions in Python. The any(iterable) and all(iterable) are built-in functions in Python and have been around since Python 2.5 was released. Both functions are equivalent to writing a series of or and and operators respectively between each...
Binary Search in Python
In this article, we'll be diving into the idea behind and Python implementation of Binary Search. Binary Search is an efficient search algorithm that works on sorted arrays. It's often used as one of the first examples of algorithms that run in logarithmic time (O(logn)) because of its intuitive...
map(), filter(), and reduce() in Python with Examples
The map(), filter() and reduce() functions bring a bit of functional programming to Python. All three of these are convenience functions that can be replaced with List Comprehensions or loops, but provide a more elegant and short-hand approach to some problems. Before continuing, we'll go over a few things you...
Bubble Sort in Python
For most people, Bubble Sort is likely the first sorting algorithm they heard of in their Computer Science course. It's highly intuitive and easy to "translate" into code, which is important for new software developers so they can ease themselves into turning ideas into a form that can...
Heap Sort in Python
Heap Sort is another example of an efficient sorting algorithm. Its main advantage is that it has a great worst-case runtime of O(n*logn) regardless of the input data. As the name suggests, Heap Sort relies heavily on the heap data structure - a common implementation of a Priority...