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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

12 Must Read DevOps Principles That Give Fair Idea on The Concept

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Here're twelve essential DevOps Principles. Below is the useful list for your sure success in your next interview. 12 DevOps principles To deliver rapidly without affecting the quality. Improved Communication and Collaboration. Multiple deploys are possible if the code in the development team is automated. Once you commit to the repository, it tests the code automatically using the automated test scripts. If the Build passed, it installs automatically. Installs automatically to n number of servers. Minor changes take place in isolation - it creates a separate server to deploy minor changes. Speed in DevOps helps organizations to serve their clients faster and more effectively. Quality and Security teams. Automating the process improves productivity over the manual method. Deploy frequently - the changes can be small or big. DevOps has multiple benefits over traditional approach. Related What is DevOps