Pandas makes it easy to scrape a table (
<table>
tag) on a web page. After obtaining it as a DataFrame, it is of course possible to do various processing and save it as an Excel file or csv file.Web Scraping courses offered through Coursera equip learners with knowledge in treating the internet as a source of data; working with HTML, XML, and JSON data formats in Python; using Python to access web data; getting and cleaning data; and more. ?Intellipaat Python training course: In this web scraping tutorial video you will learn web scrapin. Modern Web Scraping with Python using Scrapy Splash Selenium Course Become an expert in web scraping and web crawling using Python 3, Scrapy, Splash and Selenium 2nd EDITION (2019) Modern Web Scraping with Python using Scrapy Splash Selenium Course.
In this article you’ll learn how to extract a table from any webpage. Sometimes there are multiple tables on a webpage, so you can select the table you need.
Related course:Data Analysis with Python Pandas
Pandas web scraping
Install modules
It needs the modules
lxml
, html5lib
, beautifulsoup4
. You can install it with pip.pands.read_html()
You can use the function
read_html(url)
to get webpage contents.The table we’ll get is from Wikipedia. We get version history table from Wikipedia Python page:
![Web Scraping Course Python Web Scraping Course Python](/uploads/1/1/8/7/118716215/394969981.png)
This outputs:
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Because there is one table on the page. If you change the url, the output will differ.
To output the table:
To output the table:
You can access columns like this:
Pandas Web Scraping
Web Scraping Course Python For Beginners
Once you get it with DataFrame, it’s easy to post-process. If the table has many columns, you can select the columns you want. See code below:
Basic Web Scraping In Python
Then you can write it to Excel or do other things:
![Web Web](/uploads/1/1/8/7/118716215/815995195.jpg)
Related course:Data Analysis with Python Pandas