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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

How Does DevOps Speeds up Delivery

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The DevOps is basically a Software development system and most popular in Cloud computing. On-device software and storage may not be pass just yet, but it’s getting there, as more and more computing processes are taking place in the cloud. How Does DevOps Speeds up Delivery Many companies are also preferring distributed computing, which allows multiple computers to network with one another to solve a task (and, unlike the cloud, gives companies control over the actual hardware involved). Many of the skills involved with cloud computing and distributed computing are related, so the two are often grouped together: Skills to learn include SQL for database management, programming languages like Ruby, JavaScript, and Python for building cloud-based applications, and DevOps (a software development system popular in the cloud computing field). Specific in-demand programs include Microsoft Azure and Amazon Web Services. Also Read: 2017 Fast Growing IT Skills For instance, Agile, Scrum, C