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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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Bank ATM Analytics - SAP Hana

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Problem: ATM(Automated Teller Machine) has become an integral part of our society. Recent estimates developed by ATMIA place the number of ATMs in use currently at over 2.2 million, or 1 ATM per around over 3000 people in the world. If we think of very specific banks than a recent information in wikipedia states that SBI Group (State Bank Of India) has around 45000+ ATM. So we see the numbers are huge. But there is a very big problem and i would like to use a typical example from India to illustrate this. Here, many times the ATM runs out of currency notes of specific denomination as lets say Rs 100. The end consumer is left with the option of either accepting currency of higher denomination or seek a different ATM. Here we also have a charge applied by the bank if a consumer withdraws money from a ATM of a bank different from the one in which he holds his account. Now this is a major inconvenience for the end consumer and also a loss for the bank as their reputation is effecte
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