大量のデータ処理業務を自動化するために、VBAを独学で学ぶに至りましたので、その勉強方法の共有です。 まだとても上級とは言えないレベルですが、他人が作ったマクロファイルを手直しして流用したり、複数のデータを紐づけてマスタ '文系が独学2週間でVBAマクロを学び、業務を自動化. This is fantastic! I'm saving hours, possibly days. I was trying to scrap and old site, badly made, no proper divs or markup. Using the WebScraper magic, it somehow 'knew' the pattern after I selected 2 elements. Yes, it's a learning curve and you HAVE to watch the video and read the docs.
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.
Alternately, it looks like you're working from Python 2 examples. Write it in Python 2, then use the 2to3 tool to convert it. On Windows, 2to3.py is in python31 tools scripts. Can someone else point out where to find 2to3.py on other platforms? These days, I write Python 2 and 3 compatible code by using six. DB browsers, email clients. Udger database includes detailed information about every single user agent and operating system. Python is a beautiful language to code in. It has a great package ecosystem, there's much less noise than you'll find in other languages, and it is super easy to use. Python is used for a number of things, from data analysis to server programming. And one exciting use-case of.
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
Python Web Scraper Github
Install modules
It needs the modules lxml, html5lib, beautifulsoup4. You can install it with pip.
Python Web Scraper Script
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:
This outputs:
Python Web Programming
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
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:
Then you can write it to Excel or do other things:
Related course:Data Analysis with Python Pandas