Web Scraping using Python In this tutorial, you'll learn how to extract data from the web, manipulate and clean data using Python's Pandas library, and data visualize using Python's Matplotlib library. Web scraping is a term used to describe the use of a program or algorithm to extract and process large amounts of data from the web. Whether you are a data scientist, engineer, or anybody who analyzes large amounts of datasets, the ability to scrape data from the web is a useful skill to have. Let's say you find data from the web, and there is no direct way to download it, web scraping using Python is a skill you can use to extract the data into a useful form that can be imported. In this tutorial, you will learn about the following: • Data extraction from the web using Python's Beautiful Soup module • Data manipulation and cleaning using Python's Pandas library • Data visualization using Python's Matplotlib library The dataset used in this tutorial was taken from a 10K race that took place in Hillsboro, OR on June 2017. Specifically, you will analyze the performance of the 10K runners and answer questions such as: • What was the average finish time for the runners? • Did the runners' finish times follow a normal distribution? • Were there any performance differences between males and females of various age groups
