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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
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4 Top Upcoming IoT Applications

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New types of applications now part of Vehicle and the smart-house, in which appliances and services that provide notifications, security, energy-saving, automation, telecommunication, computers, and entertainment into a single ecosystem with a shared user interface.

4 Top Upcoming IoT Applications

Four Top IoT Applications

Developing technology in Europe right now—demonstrating, testing, and deploying products—it will be much nearer to implementing smart environments by 2022.
  • In the future, computation, storage, and communication services will lead. Those are:
  • Smart objects
  • The machines, platforms, and the surrounding space (e.g., with wireless/wired sensors, M2M devices, RFID tags, etc.) will create a highly decentralized pool of resources (up to the very edge of the “network”) interconnected by a dynamic network of networks.
  • The “communication language” will be based on interoperable protocols, operating in heterogeneous environments and platforms.
Sources
  1. European market potential for integrated internet of things and big data services

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