Python is great for cleaning text in data pipelines. There are so many helper functions I thought I'd put together a list of functions to manipulate text. It can be tricky to remember all the functions available. Python is a highly mature language in 2021 with multiple ways to achieve the same thing.
"100".isnumeric()=True"100t".isnnumeric()=False"2abc".isalpha()=False"abc".isalpha()=True"Very Good !".endswith("!")=True"1. Hello".startswith("1")=Trueint("100")=100" Hello ".lstrip()="Hello "" Hello ".rstrip()=" Hello"" Hello ".rstrip()="Hello""Learn Python".casefold()="learn python""LEArn python".title()="Learn Python""TestPython".removeprefix("Test")="Python""TestPython".removesuffix("Python")="Test""1,2,3".split(',')=['1','2','3']"1-100-2-Python-Is-Great".split('-',maxsplit=2)=['1','100','2-Python-Is-Great']|"Py"in"Python"=True"Python 100".find("100")=7points=19total=22print('Correct answers: {:.2%}'.format(points/total))print(f'Correct answers: {points/total:.0%}'.format(points/total))Correctanswers:86.36%Correctanswers:86%nums=[2,4,2,4,1,3,3]distinct_nums=set(nums){1,2,3,4}importredata="First Name: Bob Last Name: Dylan"reg=re.compile(r'First Name: (.*) Last Name: (.*)')match=reg.search(data)match.group(1)match.group(2)BobDylan