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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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Switching Career Top Skills for Mainframe Programmers

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Read my part-1 post. Secondly, the programmers who are working on the mainframe have very good business knowledge. 

People who have the following skills are a valuable asset to any organization. Mainframe programmers if they learn other skills and try for new jobs they can earn more money.

Programmer Roles.

A programmer who can do analysis, create database structures, write clean code, create testing structures, and clearly communicate all that has been done is a very valuable asset.

Background of Mainframe.

The mainframe was leading in the market since 1950. All the big companies in the world are running their business in mainframes. 

Yes, many American universities now teaching mainframe technology in their education curriculum, since in the future possibility is there for mainframe skill shortage.

Skills You Need to Switch Career.

  1. It may become more important for IT professionals to gain experience working with analytics technology, as research firm Gartner predicted a surge in demand in this area in the next two years. According to CIO contributor Hamish Barwick, the big data trend alone is expected to create 4.4 million jobs worldwide.
  2. Analysts warned that only a third of those jobs are likely to be filled due to difficulties in recruiting analytics talent.
  3. An opportunity for every IT Professional: "Dark data is the data being collected, but going unused despite its value and leading organizations of the future will be distinguished by the quality of their predictive algorithms.

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