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.
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.
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The pandas.readhtml function uses some scraping libraries such as BeautifulSoup and Urllib to return a list containing all the tables in a page as DataFrames. You just need to pass the URL of the page. 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. Pandas Web Scraping. 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. Is pandas for web scraping? Context: I am trying to make an app that will work with wordreference.com in which I can enter a spanish word and the program will print out the spanish word, the context, and the english translation for that context. This amounts to making the program enter the word on the website and scrape information from that page. The distribution of the remainder is not optimal but we’ll leave it like this for the sake of simplicity. We can implement this as follows: procchunks = for iproc in range(nproc): chunkstart = iproc. chunksize # make sure to include the division remainder for the last process chunkend = (iproc + 1). chunksize if iproc.
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:
Pandas Web Scraping Tables
This outputs:
Because there is one table on the page. If you change the url, the output will differ.
To output the table:
You can access columns like this:
Pandas Web Scraping
Web Scraping Using Pandas
Once you get it with DataFrame, it’s easy to post-process. Drivers amcc. If the table has many columns, you can select the columns you want. See code below:
Pandas Web Scraping Tools
Then you can write it to Excel or do other things:
Pandas Web Scraper
Related course:Data Analysis with Python Pandas