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Showing posts with the label Relational Operators

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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 Use Relational Operators in Python

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If you are working with numeric values in Python, you may find it helpful to use comparison operators to compare them. In this article, we'll explore eight different comparison operators that you can use, and provide examples of how each one works. So if you're looking to compare numeric values in Python, read on to learn more! Python comparison operators list < <= > >= == != Is is not Sample python program Assign 23 to a and 11 to b. Then, apply all the comparison operators. The output is self-explanatory. Bookmark this article to refresh when you are in doubt. Example a = 23 b = 11 print("Is a greater than b?", a > b) #greater than print("Is a less than b?", a < b) #less than print("Is a greater or equal to b?", a >= b) #greater or equal print("Is a less or equal to b?", a <= b) #less or equal print("Is a equal to b (option 1)?", a == b) #test for equality print("Is a equal to b (option 2)?",
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