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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

Hadoop: How to Improve College a Mini Project

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This is based on my research of developing an engineering college using data analytics. This is a great subject that can be applied by all engineering aspirants in their final project. In my view it has dual benefits. The one is for student they can gain lot of analytics knowledge and application to develop engineering college to keep it in the list of top colleges. The second is for Engineering colleges they can benefit to improve quality of education and to become one of the top colleges. Hadoop: How to Improve College a Mini Project The project theme is data analytics: There are total 2 parts: Use Hadoop technologies to study student database what they did in School level- This gives lot of insights on the Student interests. Approach each student and get some innovative ideas to improve the college Use Faculty database to get the skills and projects what they did in previous years. This helps to get right faculty for new innovative project Basically the qualities of g