Python for Analytics Full Course for Beginners | Numpy, Pandas, Matplotlib, Seaborn

Learn Python for analytics with Numpy, Pandas, Matplotlib and Seaborn! Python is a high-level programming language, with basic syntax, very much similar to the English Language. Python programming language is extensively used for the purpose of data analytics, and what makes it extremely versatile to work with is the multitudes of libraries it presents, which is exactly why it is a supremely popular programming language with huge amounts of people learning it every day.

Great Learning brings you this full course on Python For Analytics to help you understand everything you need to know about some of the popular Python libraries and getting started on the journey to learn about them well. During the course of the video, we discuss four popular Python libraries popularly used for the purpose of data analysis, Numpy, Pandas, Matplotlib and Seaborn.

Topics covered in this video:

• 2:10 - Agenda
• 3:11 - Numpy
• 39:30 - Pandas
• 1:04:02 - Matplotlib
• 1:50:56 - Seaborn
• 2:31:00 - IPL Project
• 3:15:00 - Fifa Project
• 4:28:53 - Covid-19 Project
• 5:04:21 - Python Interview Questions
• 6:14:00 - Data Science Interview Questions

#python #pandas #numpy #seaborn #matplotlib

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top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

…

#python #python hacks tricks #python learning tips #python programming tricks #python tips #python tips and tricks #python tips and tricks advanced #python tips and tricks for beginners #python tips tricks and techniques #python tutorial #tips and tricks in python #tips to learn python #top 30 python tips and tricks for beginners

Python for Analytics Full Course for Beginners | Numpy, Pandas, Matplotlib, Seaborn

Learn Python for analytics with Numpy, Pandas, Matplotlib and Seaborn! Python is a high-level programming language, with basic syntax, very much similar to the English Language. Python programming language is extensively used for the purpose of data analytics, and what makes it extremely versatile to work with is the multitudes of libraries it presents, which is exactly why it is a supremely popular programming language with huge amounts of people learning it every day.

Great Learning brings you this full course on Python For Analytics to help you understand everything you need to know about some of the popular Python libraries and getting started on the journey to learn about them well. During the course of the video, we discuss four popular Python libraries popularly used for the purpose of data analysis, Numpy, Pandas, Matplotlib and Seaborn.

Topics covered in this video:

• 2:10 - Agenda
• 3:11 - Numpy
• 39:30 - Pandas
• 1:04:02 - Matplotlib
• 1:50:56 - Seaborn
• 2:31:00 - IPL Project
• 3:15:00 - Fifa Project
• 4:28:53 - Covid-19 Project
• 5:04:21 - Python Interview Questions
• 6:14:00 - Data Science Interview Questions

#python #pandas #numpy #seaborn #matplotlib

Learn Python - Full Course for Beginners [Tutorial]

This course will give you a full introduction into all of the core concepts in python. Follow along with the videos and you’ll be a python programmer in no time!
⭐️ Contents ⭐
⌨️ (0:00) Introduction
⌨️ (1:45) Installing Python & PyCharm
⌨️ (6:40) Setup & Hello World
⌨️ (10:23) Drawing a Shape
⌨️ (15:06) Variables & Data Types
⌨️ (27:03) Working With Strings
⌨️ (38:18) Working With Numbers
⌨️ (48:26) Getting Input From Users
⌨️ (52:37) Building a Basic Calculator
⌨️ (58:27) Mad Libs Game
⌨️ (1:03:10) Lists
⌨️ (1:10:44) List Functions
⌨️ (1:18:57) Tuples
⌨️ (1:24:15) Functions
⌨️ (1:34:11) Return Statement
⌨️ (1:40:06) If Statements
⌨️ (1:54:07) If Statements & Comparisons
⌨️ (2:00:37) Building a better Calculator
⌨️ (2:07:17) Dictionaries
⌨️ (2:14:13) While Loop
⌨️ (2:20:21) Building a Guessing Game
⌨️ (2:32:44) For Loops
⌨️ (2:41:20) Exponent Function
⌨️ (2:47:13) 2D Lists & Nested Loops
⌨️ (2:52:41) Building a Translator
⌨️ (3:00:18) Comments
⌨️ (3:04:17) Try / Except
⌨️ (3:12:41) Reading Files
⌨️ (3:21:26) Writing to Files
⌨️ (3:28:13) Modules & Pip
⌨️ (3:43:56) Classes & Objects
⌨️ (3:57:37) Building a Multiple Choice Quiz
⌨️ (4:08:28) Object Functions
⌨️ (4:12:37) Inheritance
⌨️ (4:20:43) Python Interpreter
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=rfscVS0vtbw&list=PLWKjhJtqVAblfum5WiQblKPwIbqYXkDoC&index=3

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Thanks for visiting and watching! Please don’t forget to leave a like, comment and share!

#python #learn python #learn python for beginners #learn python - full course for beginners [tutorial] #python programmer #concepts in python

Python for Beginners #2 — Importing files to python with pandas

Use pandas to upload CSV, TXT and Excel files

Story time before we begin

Learning Python isn’t the easiest thing to do. But consistency is really the key to arriving at a level that boosts your career.

We hear a lot about millennials wanting things to easy. In reality, there are a lot of young professionals who believe that they can do more for their companies but are being held back by the work cultures they are faced with at the onset of their careers.

Having been lucky enough to have found a job after my studies, I remember immediately feeling a wave of disappointment a very short while after starting my new job. I felt like a cog in a massive machine. I wasn’t really anything other than a ‘resource’. An extra 8–15 hours of daily man power depending on my boss’ whim.

The result, was the eventual disenchantment and lack of motivation simply because, for the most part, I was expected to be quiet and do my job in the hope of one day being senior enough to effect significant changes. And while the older generation would generally tell me to suck it up, I couldn’t see myself sucking it up for 5 years or more. I knew I’d get stale and afraid of change, much like those telling me to stay in my place.

For anyone in a similar situation,**_ do your best to improve on your skills _**and find an environment that works for you. That’s the whole purpose of these articles. To get you on your way to freedom.

Introduction

For this demonstration, I’ll use data from this Kaggle competition. It’s a simple CSV file containing data on individuals in the Titanic and the different profiles i.e. (age, marital status etc.)

I want to import this file to python. I’ll show you how to do this alongside all the possible troubleshoots you may encounter.

Table of Contents

1. Where should you put your files?
2. Reading CSV and TXT files
3. Reading excel (XLSX) files

#python #programming #pandas #python for beginners #importing files to python with pandas #python for beginners #2 — importing files to python with pandas

Python Django Web Framework - Full Course for Beginners. DO NOT MISS!!!

Learn the Python Django framework with this free full course. Django is an extremely popular and fully featured server-side web framework, written in Python. Django allows you to quickly create web apps.
⭐️Course Contents ⭐️
⌨️ (0:00:00) 1 - Welcome
⌨️ (0:01:14) 2 - Installing to Get Started
⌨️ (0:05:02) 3 - Setup your Virtual Environment for Django
⌨️ (0:14:39) 4 - Create a Blank Django Project
⌨️ (0:18:54) 5 - Setup Your Code Text Editor
⌨️ (0:22:27) 6 - Settings
⌨️ (0:29:58) 7 - Built-In Components
⌨️ (0:33:57) 8 - Your First App Component
⌨️ (0:42:34) 9 - Create Product Objects in the Python Shell
⌨️ (0:46:18) 10 - New Model Fields
⌨️ (0:52:52) 11 - Change a Model
⌨️ (0:59:27) 12 - Default Homepage to Custom Homepage
⌨️ (1:04:48) 13 - URL Routing and Requests
⌨️ (1:10:23) 14 - Django Templates
⌨️ (1:16:50) 15 - Django Templating Engine Basics
⌨️ (1:24:00) 16 - Include Template Tag
⌨️ (1:26:49) 17 - Rendering Context in a Template
⌨️ (1:33:21) 18 - For Loop in a Template
⌨️ (1:37:01) 19 - Using Conditions in a Template
⌨️ (1:42:17) 20 - Template Tags and Filters
⌨️ (1:48:59) 21 - Render Data from the Database with a Model
⌨️ (1:59:55) 22 - How Django Templates Load with Apps
⌨️ (2:06:50) 23 - Django Model Forms
⌨️ (2:14:16) 24 - Raw HTML Form
⌨️ (2:25:33) 25 - Pure Django Form
⌨️ (2:35:30) 26 - Form Widgets
⌨️ (2:41:29) 27 - Form Validation Methods
⌨️ (2:48:59) 28 - Initial Values for Forms
⌨️ (2:51:42) 29 - Dynamic URL Routing
⌨️ (2:54:26) 30 - Handle DoesNotExist
⌨️ (2:56:24) 31 - Delete and Confirm
⌨️ (2:58:24) 32 - View of a List of Database Objects
⌨️ (3:00:00) 33 - Dynamic Linking of URLs
⌨️ (3:01:17) 34 - Django URLs Reverse
⌨️ (3:03:10) 35 - In App URLs and Namespacing
⌨️ (3:07:35) 36 - Class Based Views - ListView
⌨️ (3:10:45) 37 - Class Based Views - DetailView
⌨️ (3:15:38) 38 - Class Based Views - CreateView and UpdateView
⌨️ (3:21:23) 39 - Class Based Views - DeleteView
⌨️ (3:24:02) 40 - Function Based View to Class Based View
⌨️ (3:27:15) 41 - Raw Detail Class Based View
⌨️ (3:30:31) 42 - Raw List Class Based View
⌨️ (3:33:32) 43 - Raw Create Class Based View
⌨️ (3:26:03) 44 - Form Validation on a Post Method
⌨️ (3:37:58) 45 - Raw Update Class Based View
⌨️ (3:41:13) 46 - Raw Delete Class Based View
⌨️ (3:42:17) 47 - Custom Mixin for Class Based Views

📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=F5mRW0jo-U4&list=PLWKjhJtqVAbnqBxcdjVGgT3uVR10bzTEB&index=6
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⭐ ⭐ ⭐The project is of interest to the community. Join to Get free ‘GEEK coin’ (GEEKCASH coin)!
☞ **-----CLICK HERE-----**⭐ ⭐ ⭐
Thanks for visiting and watching! Please don’t forget to leave a like, comment and share!

#python #django #python django web framework #beginners #full course #python django web framework - full course for beginners