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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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Cloud Storage as a Service Basics(1 of 3)

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Cloud storage is a model of networked enterprise storage where data is stored in virtualized pools of storage which are generally hosted by third parties. Hosting companies operate large data centers, and customers that require their data to be hosted buy or lease storage capacity from these hosting companies.

The data center operators virtualize the resources according to customer requirements and expose them as storage pools, which the customers can use to store data. Physically, the resource may span multiple servers and multiple locations. The safety of the data depends upon the hosting companies and on the applications that leverage the cloud storage.

Cloud storage is based on highly virtualized infrastructure and has the same characteristics as cloud computing in terms of agility, scalability, elasticity, and multi-tenancy. It is available both off-premises and on-premises. 

While it is difficult to declare a canonical definition of cloud storage architecture, object storage is reasonably analogous. Cloud storage software such as OpenStack Cinder, cloud storage products like EMC Atmos® and Hitachi Content Platform, and distributed storage research projects like OceanStore or VISION Cloud are examples of object storage and infer the following guidelines.

Cloud storage is:

  • Made up of many distributed resources but still acts as one; often referred to as federated storage clouds. 
  • Highly fault tolerant through redundancy and distribution of data. 
  • Highly durable through the creation of versioned copies. 
  • Typically eventually consistent with regard to data replicas. 


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