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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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Computer Science Vs Information Science Top Differences

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Computer Science Vs Information Science Top Differences

Here are the differences between Computer Science and Information Science.

Computer Science


Computer scientists are, in fact, scientists. They are focused on the theory of computational applications.


That means they understand the “why” behind computer programs. Using algorithms and advanced mathematics, computer scientists invent new ways to manipulate and transfer information. Computer scientists are generally concerned with software, operating systems, and implementation.


Like Neo in The Matrix, computer scientists can see and make sense of code. Computer science students will learn the fundamentals of different programming languages, linear and discrete mathematics, and software design and development.


Computer scientists study the machine itself and understand how and why various computer processes operate the way they do.  



Information Science


To put it bluntly, computer engineers make computer parts work together. Computer engineers are responsible for the research, design, and development of computer equipment like circuit boards, microchips, routers, video cards, etc. Some universities may treat this discipline as an off-shoot of electrical engineering.


It is beneficial for computer engineers to have a grasp of computer science. Computer engineers often deal with hardware-to-software integration, meaning they have to design and build processors and hardware that can support a given program. 


As technology advances and our devices become smaller and smaller, the main goal of computer engineers is to create microchips and microprocessors that work economically and efficiently.


Computer engineering students will study concepts in computer science, engineering, and mathematics. 


By combining these three fields, computer engineers are able to solve hardware problems and create state-of-the-art machines that can handle the many tasks computers perform. 


Summary

In reality, both are different subjects, and computer science deals with software programs, and information science deals with hardware requirements to meet software applications requirements.

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