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Learn how to use Python, Selenium WebDriver, BeautifulSoup, and Pandas to scrape websites and gather large datasets, which you will eventually need for your data science projects. All the coding will be done on Google Colab so it will be very easy for you to follow this tutorial. I will be using Google Colab, and will make the Python notebook available on. Github code: https://github.com/armindocachada/scrape-data-with-beatifulsoup-selenium-panda-df TIMESTAMPS: 0:00 Introduction 4:00 Starting the notebook in Google Colab 4:27 Installing Selenium/Webdriver with headless chrome 4:54 Opening the page to scrape in a chrome web browser 5:14 Using wd.find_element_by_id to enter a search term 6:30 Typing search term using send_keys() 8:30 Clicking search button using click(() 11:00 Using implicit_wait to allow webdriver to wait for an element to be available 12:30 using wd.find_element_by_class_name to find element by class name 13:30 Using the Pandas library pd.read_html() to read a table from HTML 18:00 Using BeatifulSoup to parse the HTML in the page
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