In this post, you’ll explore regular expressions in Python only. Regular expressions are supported by most of the programming languages like Python, Perl, R, Java and many others.
Humans are good at recognising patterns, so you will know that 41 is a phone number, but 6789,78564,67708879 is not. Knowing regular expressions can mean the difference between solving a problem in 3 steps and solving in 3,000 steps.įor example, you may need to find in some text a phone number that you don't know, but if you live in the USA or Canada, you know it will be three digits, followed by a hyphen, then another three digits followed by a hyphen and then four more digits. Essentially RegEx as a sequence of characters that defines a search pattern. Regular expressions go one step further: They allow you to specify a pattern of text to search for. You may be familiar with searching for text using shortcut ctrl + F and entering the text you are looking for. Be it extraction of specific parts of text from web pages, making sense of twitter data or preparing your data for text mining – Regular expressions are your best bet for all these tasks. Regular expressions are the default way of data cleaning and wrangling in Python. RegEx is incredibly useful, and so you must get your head around it early. In this tutorial, you will learn about regular expressions, called RegExes (RegEx) for short, and use Python's re module to work with regular expressions.
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