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Stone River eLearning - Web Scraping In Python

Stone River eLearning – Web Scraping In Python

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Original price was: $99.00.Current price is: $37.00.

Web scraping is the art of picking out data from a website by looking at the HTML code and identifying patterns that can be used to identify your data. This data can then be gathered and later used for your own analysis.

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Description

Stone River eLearning – Web Scraping In Python

Stone River eLearning - Web Scraping In Python

Web scraping is the art of picking out data from a website by looking at the HTML code and identifying patterns that can be used to identify your data. This data can then be gathered and later used for your own analysis.

In this course we will go over the basic of web scraping, learning all about how we can extract data from websites, and all of this is guided along by a work example.

At the end of the course you should be able to go off on your own, and pick out most common

Course Curriculum

Prerequisite knowledge
  • Introduction (3:20)
  • APIs (2:00)
  • Prerequisite Libraries (3:00)
  • Introduction to The Modulus Operation (5:01)
  • Introduction to Simple Error Handling (4:25)
  • Introduction to Pandas (6:41)
Static Data Extraction/Web Scraping
  • Response Status Codes From a HTTP Request (7:18)
  • Reading The Response Text From Our Request (11:40)
  • First Approach at Parsing The Data (13:18)
  • Understanding The Exception Cases (6:39)
  • Parsing Out All Data for One Company (9:33)
  • Determining Where We Can Get More Ticker Symbols (15:46)
  • Extracting Company Ticker Symbols Part 1 (16:32)
  • Extracting Company Ticker Symbols Part 2 (10:41)
  • Getting Data For All Parsed Companies (8:11)
  • Final Data For All Parsed Companies (5:13)
  • Final Result (1:40)
Scraping Websites That Load Data With Javascript
  • Prerequisite Libraries (5:02)
  • Short review: Recursive Functions (7:43)
  • Getting ed with Selenium (8:47)
  • View The Page Source (9:14)
  • Website Elements and XPath (8:11)
  • Navigating Deeper Into The Page Source (14:37)
  • Identifying The Path To Our Data (19:28)
  • Using The XPath To Our Data (9:50)
  • Parsing Out Our Data (8:42)
  • Getting Our Final Data (14:56)
  • Final Results (4:13)

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