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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

Major Trends in IT in 2015

As per research paper submitted by Gartner, the following trends will dominate in IT industry.

Advanced, Pervasive and Invisible Analytics:

Analytics will take center stage as the volume of data generated by embedded systems increases and vast pools of structured and unstructured data inside and outside the enterprise are analyzed.

"Every app now needs to be an analytic app," said Mr. Cearley. "Organizations need to manage how best to filter the huge amounts of data coming from the IoT, social media and wearable devices, and then deliver exactly the right information to the right person, at the right time. Analytics will become deeply, but invisibly embedded everywhere."

Big data remains an important enabler for this trend but the focus needs to shift to thinking about big questions and big answers first and big data second — the value is in the answers, not the data.

Cloud/Client Computing:

The convergence of cloud and mobile computing will continue to promote the growth of centrally coordinated applications that can be delivered to any device. "Cloud is the new style of elastically scalable, self-service computing, and both internal applications and external applications will be built on this new style," said Mr. Cearley.

 "While network and bandwidth costs may continue to favor apps that use the intelligence and storage of the client device effectively, coordination and management will be based in the cloud."

In the near term, the focus for cloud/client will be on synchronizing content and application state across multiple devices and addressing application portability across devices. Over time, applications will evolve to support simultaneous use of multiple devices. 

The second-screen phenomenon today focuses on coordinating television viewing with use of a mobile device. In the future, games and enterprise applications alike will use multiple screens and exploit wearables and other devices to deliver an enhanced experience.

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