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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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Networking in IoT age for big opportunities (1 of 3)

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Networking is common in the age of IOT. The basics I want to say are networking means connecting objects together. The networking is possible with wires and without cables. The without cables you can say as wireless.

How Computers Connected

  • Computers are connected by using fiber cables. Each computer is connected by cable to a central switch, which connects to the rest of the network  
  • The advantage of wireless networking is no cables required. In a wireless network, most cables and switches are moot. Radio transmitters and receivers take the place of cables.
  • Networking software must be installed. This drives networking functioning.

Benefits of network

  1. To share resources
  2. Sharing information
  3. Sharing applications

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