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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

6 Top IT Skills that have Huge demand for the next 5 Years

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These are top IT skills you need to know. Also, these are highly employable skills. These you can say as digital skills. Digital skills fetch you best salary, according to surveys by top job portals . 6 Top IT SKills SAS and R Programming Full stack development Data Engineering Data Scinece Mobile development - Perl, Ruby and Python Middleware integration software. The Bottom Line The trend is now changed. You can attend off-line and On-line courses and you can practices daily two hours. Within 2 or 3 months you can be perfect. Select any one skill for your employability. You cannot learn all the skills. It is dofficult to tell answers in the interviews.