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Web Scrapping and Data Visualisation with Python

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Web Scrapping and Data Visualisation with Python, available at $19.99, has an average rating of 3.95, with 24 lectures, based on 29 reviews, and has 129 subscribers.

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You will learn about Creating a automatic web scraper to extract financial data using Beautiful Soup Creating interactive graphs and other visualizations using Pandas, Matplotlib and Plotly Use your Python and HTML knowledge to build a practical project about Finance Learn how to use Chrome Inspector to inspect the HTML elements of a website Google Colab Notebooks for all Tutorials and Exercises can be accessed Q&A board to ask your questions and get your answers This course is ideal for individuals who are Perfect if you have just learnt Python and looking for building some practical tool about Finance using Python or Anyone who is interested in data science and data analytics or Anyone who is interested in automatically copying information from websites with web scraping technique or Anyone who is interested in data wrangling and manipulation in Python or Anyone who is interested in making interactive dashboard and graphs in Python or Anyone who is interested in making a personal project about Finance and Computer Science It is particularly useful for Perfect if you have just learnt Python and looking for building some practical tool about Finance using Python or Anyone who is interested in data science and data analytics or Anyone who is interested in automatically copying information from websites with web scraping technique or Anyone who is interested in data wrangling and manipulation in Python or Anyone who is interested in making interactive dashboard and graphs in Python or Anyone who is interested in making a personal project about Finance and Computer Science.

Enroll now: Web Scrapping and Data Visualisation with Python

Summary

Title: Web Scrapping and Data Visualisation with Python

Price: $19.99

Average Rating: 3.95

Number of Lectures: 24

Number of Published Lectures: 24

Number of Curriculum Items: 24

Number of Published Curriculum Objects: 24

Original Price: $39.99

Quality Status: approved

Status: Live

What You Will Learn

  • Creating a automatic web scraper to extract financial data using Beautiful Soup
  • Creating interactive graphs and other visualizations using Pandas, Matplotlib and Plotly
  • Use your Python and HTML knowledge to build a practical project about Finance
  • Learn how to use Chrome Inspector to inspect the HTML elements of a website
  • Google Colab Notebooks for all Tutorials and Exercises can be accessed
  • Q&A board to ask your questions and get your answers

Who Should Attend

  • Perfect if you have just learnt Python and looking for building some practical tool about Finance using Python
  • Anyone who is interested in data science and data analytics
  • Anyone who is interested in automatically copying information from websites with web scraping technique
  • Anyone who is interested in data wrangling and manipulation in Python
  • Anyone who is interested in making interactive dashboard and graphs in Python
  • Anyone who is interested in making a personal project about Finance and Computer Science

Target Audiences

  • Perfect if you have just learnt Python and looking for building some practical tool about Finance using Python
  • Anyone who is interested in data science and data analytics
  • Anyone who is interested in automatically copying information from websites with web scraping technique
  • Anyone who is interested in data wrangling and manipulation in Python
  • Anyone who is interested in making interactive dashboard and graphs in Python
  • Anyone who is interested in making a personal project about Finance and Computer Science

Welcome to Web Scraping and Data Visualization with Python!

Are you looking for creating practical applications with your Python and HTML skills? Do you want to stay up to trend of what’s latest about data science and analytics?

Many industries are harnessing the beauty of web scraping and data visualization in manifold ways. Examples are e-commerce companies, financial institutions, hiring and even the government who make use of these data-driven approaches and help them make better decision.

You can also be like them through learning the essential concepts by completing two projects at this course.

In the course, you will understand a variety of important concepts regarding web scraping and data visualization. Here are the course highlights:

  • Essentials of web scraping, including basic knowledge of HTML and web components, Beautiful Soup APIs, different web scraping techniques, and writing a modular web scraper

  • Know how to process and manipulate data extracted by web scraping through learning how to create, filter and sort data frames with Pandas (Python module)

  • Know how to use matplotlib and Plotly (Python modules) to create stunning looking and interactive charts (e.g. bar/pie/line/area/bubble/candlestick/heatmap)

You will be given access to all the materials used in this course, including the lesson notes, quizzes, and the google collaborators Python notebooks.

Access the student forum to interact with me and other fellow students. You are also welcome to ask any questions regarding the course, and discuss with each other.

Join me now and wish you have a happy learning journey!

Course Curriculum

Chapter 1: Course Overview

Lecture 1: Course Introduction

Lecture 2: Introducing the Yahoo! Finance Website

Lecture 3: Introducing Google Collaboratory

Chapter 2: Web Basics

Lecture 1: Using the Chrome Inspector

Lecture 2: (Optional) Review of HTML elements

Chapter 3: Building A Simple Web Scraper

Lecture 1: Resources for Web Scraping (Project 1)

Lecture 2: Extract data using Beautiful Soup

Lecture 3: Full Table Scraping: Scraping Active Stocks

Lecture 4: Row Scraping: Scraping Currencies

Lecture 5: Header Scraping: Scraping Active Stocks

Chapter 4: Building An Advanced Web Scraper

Lecture 1: Generic function for scraping ANY HTML tables

Lecture 2: Scraping the other financial products

Chapter 5: Processing the Scraped Data

Lecture 1: Data Type Conversions

Lecture 2: Filtering Stocks

Lecture 3: Sorting Stocks

Chapter 6: Visualising Stock Market Data

Lecture 1: Resources for Data Visualization (Project 2)

Lecture 2: Scraping stock price history data

Lecture 3: Introducing graph libraries in Python

Lecture 4: Matplotlib: Plotting Stock Price Trend in Python

Chapter 7: Creating Basic Charts Visualizations

Lecture 1: Creating Pie Charts

Lecture 2: Creating Candlestick Charts

Chapter 8: Creating Advanced Charts Visualizations

Lecture 1: Creating Area Chart and Multi-line Charts

Lecture 2: Creating Heatmaps

Lecture 3: Creating Bubble Charts

Instructors

Rating Distribution

  • 1 stars: 2 votes
  • 2 stars: 0 votes
  • 3 stars: 2 votes
  • 4 stars: 9 votes
  • 5 stars: 16 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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