Inheritance (Python) - Data Structures and Algorithms

Today I am going to be showing you (hands on) how to create classes that derive from other classes. This is important for inheritance and polymorphism. We are coding this in Python, but you an do similar things in C#, Java, C++, and most if not all modern languages.

#python

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Inheritance (Python) - Data Structures and Algorithms

Types of Inheritance in Python | Python Inheritance [With Example] | upGrad blog

Introduction

The struggle for a clean code is a battle joined by all the programmers. And that battle can be conquered with a proper armour of object-oriented programming concepts. And proper utilization of OOP concepts helps us to improve code reusability, readability, optimal time and space complexity.

Coding in Python is super fun. It has a whopping number of library support, object-oriented, GUI programmability makes it a hot cake among all the programming languages.

Inheritance is one of the most utilized object-oriented features and implementing it in python is an enthusiastic task. So, let’s start now!

First things first let’s understand the definition of inheritance.

#data science #inheritance #inheritance in python #python #types of inheritance #types of inheritance in python

 iOS App Dev

iOS App Dev

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Arvel  Parker

Arvel Parker

1593156510

Basic Data Types in Python | Python Web Development For Beginners

At the end of 2019, Python is one of the fastest-growing programming languages. More than 10% of developers have opted for Python development.

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.

Table of Contents  hide

I Mutable objects

II Immutable objects

III Built-in data types in Python

Mutable objects

The Size and declared value and its sequence of the object can able to be modified called mutable objects.

Mutable Data Types are list, dict, set, byte array

Immutable objects

The Size and declared value and its sequence of the object can able to be modified.

Immutable data types are int, float, complex, String, tuples, bytes, and frozen sets.

id() and type() is used to know the Identity and data type of the object

a**=25+**85j

type**(a)**

output**:<class’complex’>**

b**={1:10,2:“Pinky”****}**

id**(b)**

output**:**238989244168

Built-in data types in Python

a**=str(“Hello python world”)****#str**

b**=int(18)****#int**

c**=float(20482.5)****#float**

d**=complex(5+85j)****#complex**

e**=list((“python”,“fast”,“growing”,“in”,2018))****#list**

f**=tuple((“python”,“easy”,“learning”))****#tuple**

g**=range(10)****#range**

h**=dict(name=“Vidu”,age=36)****#dict**

i**=set((“python”,“fast”,“growing”,“in”,2018))****#set**

j**=frozenset((“python”,“fast”,“growing”,“in”,2018))****#frozenset**

k**=bool(18)****#bool**

l**=bytes(8)****#bytes**

m**=bytearray(8)****#bytearray**

n**=memoryview(bytes(18))****#memoryview**

Numbers (int,Float,Complex)

Numbers are stored in numeric Types. when a number is assigned to a variable, Python creates Number objects.

#signed interger

age**=**18

print**(age)**

Output**:**18

Python supports 3 types of numeric data.

int (signed integers like 20, 2, 225, etc.)

float (float is used to store floating-point numbers like 9.8, 3.1444, 89.52, etc.)

complex (complex numbers like 8.94j, 4.0 + 7.3j, etc.)

A complex number contains an ordered pair, i.e., a + ib where a and b denote the real and imaginary parts respectively).

String

The string can be represented as the sequence of characters in the quotation marks. In python, to define strings we can use single, double, or triple quotes.

# String Handling

‘Hello Python’

#single (') Quoted String

“Hello Python”

# Double (") Quoted String

“”“Hello Python”“”

‘’‘Hello Python’‘’

# triple (‘’') (“”") Quoted String

In python, string handling is a straightforward task, and python provides various built-in functions and operators for representing strings.

The operator “+” is used to concatenate strings and “*” is used to repeat the string.

“Hello”+“python”

output**:****‘Hello python’**

"python "*****2

'Output : Python python ’

#python web development #data types in python #list of all python data types #python data types #python datatypes #python types #python variable type

Ray  Patel

Ray Patel

1619510796

Lambda, Map, Filter functions in python

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

Virgil  Hagenes

Virgil Hagenes

1603357200

Python+ 101: Most useful data structures and algorithms

Python is undoubtedly one of the most widely used programming languages of this century that has given a whole new perspective to programming in terms of ease of use and intuitiveness. Besides having a rich set of the most common data structures, it provides a number of standard libraries that can greatly reduce the burden of developing codes from scratch for a variety of problems pertaining to different fields. In this tutorial, I will focus on some of the most common problems or should I say, encounters, and their solutions using data structures and algorithms of standard python modules. So let’s dive into the world of “Python+” which is all about adding something more into what we know of Python.

1. N largest or smallest elements in a list, tuple, set or numpy array

In many scenarios, we need to extract the largest or smallest elements in a collection. The nlargest and nsmallest methods of the heapq module of python can be used to obtain N largest and smallest elements in a list. nlargest(n,iterable) and nsmallest(n,iterable) where n is the number of largest or smallest elements that need to be obtained and iterable can be a list, a tuple, a set or a numpy array can be used as follows.

Figure 1. Smallest and largest elements in a list, tuple and array

These methods are faster and more efficient in case more than one largest or smallest elements in a collection is needed. If the single largest or smallest element is needed, the min and max functions in python are more efficient. Note that the _nlargest_ and _nsmallest_ functions always return a list irrespective of the type of the collection.

#python-standard-library #python #data-structures #algorithms #data-science