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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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How to Understand AWS CloudFormation Easily

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AWS CloudFormation is a service that helps you model and set up your Amazon Web Services resources so that you can spend less time managing those resources and more time focusing on your applications that run in AWS.

You create a template that describes all the AWS resources you want (like Amazon EC2 instances or Amazon RDS DB instances), and AWS CloudFormation provides and configures those resources for you.

cloud formation

 

You don't need to individually create and configure AWS resources and figure out what's dependent on what; AWS CloudFormation handles all of that. 

Managing Infrastructure

  • For a scalable web application that also includes a back-end database, you might use an Auto Scaling group, an Elastic Load Balancing load balancer, and an Amazon Relational Database Service database instance. 
  • Normally, you might use each individual service to provide these resources. And after you create the resources, you would have to configure them to work together. All these tasks can add complexity and time before you even get your application up and running. 
  • Instead, you can create or modify an existing AWS CloudFormation template. A template describes all of your resources and their properties. 
  • When you use that template to create an AWS CloudFormation stack, AWS CloudFormation provisions the Auto Scaling group, load balancer, and database for you. After the stack has been created, your AWS resources are up and running. You can delete the stack quickly. which deletes all the resources in the stack. By using AWS CloudFormation, you easily manage a collection of resources as a single unit.

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