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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

SAP HANA Top new Applications

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The SAP HANA analytics from German software vendor SAP AG is betting heavily on a new generation of analytic computing it calls HANA.  In this post you will know the new features that are added in HANA. To maintain its position as the world's largest business-application vendor. So, learning HANA is really good and make sure these HANA course contents you need to have in your training. SAP HANA Applications HANA, which is already installed at more than 200 customer locations, processes data in real-time by storing it in live memory rather than in a separate data warehouse, enabling customers to make business decisions faster. >> Liquor distributor Charmer Sunbelt Group finished installing a HANA system , and it says it has helped managers react to logistical problems as they occur. Getting shipments out is essential for Charmer because customers can refuse them if they are late. >> According to Chief Information Officer Paul Fipps, HANA h