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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

Social Media and Mobile Technology for Health care

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(People also click these jobs to  know skill set  and to apply  even from your phone!!) The ubiquity of mobile phone accessibility around the world is increasing. Worldwide the number of mobile phones in use grew from fewer than 1 billion in 2000 to around 6 billion in 2012. Recent estimates conclude that over 75% of the world' s population have access to a mobile phone (World Bank, 2012). Globally, there has been a rapid rise in the use of smart phones by consumers with over 1 billion Smart Phones subscribers (Approximately 30% of smartphone users are likely to use wellness apps by 2015, (Bjornland, Goh, Haanæs, Kainu, & Kennedy, 2012) with more than 30 billion mobile applications being downloaded in 2011 (World Bank, 2012). Along with this increase in penetration, there has been a significant increase in the development and deployment of mobile software applications across multiple computing platforms (e.g. smart phones, tablets and laptops). The most pop