Web scraping the President's lies in 16 lines of Python

Note: This tutorial is available as a video series and a Jupyter notebook, and the dataset of lies is available as a CSV file. Summary This an introductory tutorial on web scraping in Python. All that is required to follow along is a basic understanding of the Python programming language. By the end of this tutorial, you will be able to scrape data from a static web page using the requests and Beautiful Soup libraries, and export that data into a structured text file using the pandas library. Outline What is web scraping? Examining the New York Times article Examining the HTML Fact 1: HTML consists of tags Fact 2: Tags can have attributes Fact 3: Tags can be nested Reading the web page into Python Parsing the HTML using Beautiful Soup Collecting all of the records Extracting the date Extracting the lie Extracting the explanation Extracting the URL Recap: Beautiful Soup methods and attributes Building the dataset Applying a tabular data structure Exporting the dataset to a CSV file Summary: 16 lines of Python code Appendix A: Web scraping advice Appendix B: Web scraping resources Appendix C: Alternative syntax for Beautiful Soup What is web scraping? On July 21, 2017, the New York Times updated an opinion article called Trump's Lies, detailing every public lie the President has told since taking office.

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