APIs are not always available. Sometimes you have to scrape data from a webpage yourself. Luckily the modules Pandas and Beautifulsoup can help!
In this video, I will be showing you how to easily web scrape data from websites in Python using the pandas library. Particularly, the readhtml function o. Web Scraping with Pandas and Beautifulsoup. APIs are not always available. Sometimes you have to scrape data from a webpage yourself. Luckily the modules Pandas and Beautifulsoup can help! Related Course: Complete Python Programming Course & Exercises. Pandas has a neat concept known as a DataFrame. Web Scraping with Python: Collecting More Data from the Modern Web — Book on Amazon. Jose Portilla's Data Science and ML Bootcamp — Course on Udemy. Easiest way to get started with Data Science. Covers Pandas, Matplotlib, Seaborn, Scikit-learn, and a lot of other useful topics.
Related Course:Complete Python Programming Course & Exercises
Web scraping basically means that, instead of using a browser, we can use Python to send request to a website server, receive the HTML code, then extract the data we want. Because there is one table on the page. If you change the url, the output will differ. To output the table.
Web scraping
Pandas has a neat concept known as a DataFrame. A DataFrame can hold data and be easily manipulated. We can combine Pandas with Beautifulsoup to quickly get data from a webpage.
If you find a table on the web like this:
We can convert it to JSON with:
And in a browser get the beautiful json output:
Converting to lists
Rows can be converted to Python lists.
We can convert it to a dataframe using just a few lines:
Pretty print pandas dataframe
Python Web Page Scraping
You can convert it to an ascii table with the module tabulate.
This code will instantly convert the table on the web to an ascii table:
This will show in the terminal as: