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The Quick and Easy Way to Analyze Numpy Arrays

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

The best career skills need for Social media platform

#How-to-apply-social-media-analytics-for-all-it-developers Listening -  This one is still very much true, and perhaps even more so. The best social media pros listen the most actively and most aggressively. Pattern Recognition -  This is getting more and more critical as the data and complexity of social continues to ratchet up. Are these posts on our Facebook page a crisis in the making, or just noise? Where are the real-time marketing opportunities?  Instantly identifying patterns and being able to capitalize upon them  are some of the skills that separate good social practitioners from great ones. Visual Thinking -  This is perhaps the biggest change in the past year or two. Being a great writer was formerly a key characteristic of many social pros, as being able to coherently write in 140 characters isn’t as easy as it appears. Today, with every social network embracing visuals and multi-media,  being able to represent the brand visually is absolutely critical.  This i