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Showing posts with the label regular-expressions

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The Quick and Easy Way to Analyze Numpy Arrays

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The quickest and easiest way to analyze NumPy arrays is by using the numpy.array() method. This method allows you to quickly and easily analyze the values contained in a numpy array. This method can also be used to find the sum, mean, standard deviation, max, min, and other useful analysis of the value contained within a numpy array. Sum You can find the sum of Numpy arrays using the np.sum() function.  For example:  import numpy as np  a = np.array([1,2,3,4,5])  b = np.array([6,7,8,9,10])  result = np.sum([a,b])  print(result)  # Output will be 55 Mean You can find the mean of a Numpy array using the np.mean() function. This function takes in an array as an argument and returns the mean of all the values in the array.  For example, the mean of a Numpy array of [1,2,3,4,5] would be  result = np.mean([1,2,3,4,5])  print(result)  #Output: 3.0 Standard Deviation To find the standard deviation of a Numpy array, you can use the NumPy std() function. This function takes in an array as a par
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How to Search for Single CHAR in Python Using Regular-expression

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Here is the logic for searching single CHAR using regular expression(Regex). For instance, we use wildcards to search for anything on our computers. The Regex in Python works similarly. Regular expression People use asterisk * for searching any document. For instance, if you type *.pdf, it returns all the pdfs available in the location (where you are conducting your search). Similar way, in Python, you can search using regular expressions. Import Regex  The first thing you need to do is import 're' if you want to work with regular expressions. import re The Python regular expression library, you can use to improve your skills. Example program: search for single CHAR To match any single character, you can use  [….] . Below, you will find an example to search for: 'l' or 'a' or 'b' import re pattern = r'[lab]' sequence = 'we love python' obj = re.search(pattern,sequence) if obj: print("We found a match here @",obj.group()) else: p
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How to write Regular expression Quickly in python and Examples

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Regular Expressions purpose is to find matching string in another string. You will get either 'True' or 'False' as a response. I am not sharing here how to play tennis. My intention is if you just follow ideas, you can play tennis today.   Python Regular Expressions What is a regular expression How does python support Best examples 1. What is regular expression >>> haystack = 'My phone number is 213-867-5309.'  >>> '213-867-5309' in haystack True This is just a fundamental use of the regular expression. The real use of Regular Expression comes here. That is - to find if the main has any valid phone number. Regular expressions also called regexes. 2. Why do we need regx Data mining - to get required data if it is present are not Data validations - to get an answer if the received string is valid or not. Python support Python has its own regular expression library. That is called re . What you need to do is just import it. >>>imp
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