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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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Understand Data power why quality everyone wants

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Information and data quality is new service work for data intense companies. I have seen not only in Analytics projects but in Mainframe projects, there is the Data Quality team.

How incorrect data impact on us

Information quality problems and their impact are all around us:
  • A customer does not receive an order because of incorrect shipping information.
  • Products are sold below cost because of wrong discount rates.
  • A manufacturing line is stopped because parts were not ordered—the result of inaccurate inventory information.
  • A well-known U.S. senator is stopped at an airport (twice) because his name is on a government "Do not fly" list.
  • Many communities cannot run an election with results that people trust.
  • Financial reform has created new legislation such as Sarbanes—Oxley. 
Incorrect data leads to many problems. The role of Data Science is to use quality data for effective decisions.

What is information

  1. Information is not simply data, strings of numbers, lists of addresses, or test results stored in a computer. Information is the product of business processes and is continuously used and reused by them. 
  2. It takes human beings to bring information to its real-world context and give it meaning. 
  3. Every day human beings use the information to make decisions, complete transactions and carry out all the other activities that make a business run. Applications come and applications go, but the information in those applications lives on.
  4. Effective business decisions and actions can only be made when based on high-quality information—the key here being effective. Yes, business decisions are based all the time on poor-quality data, but effective business decisions cannot be made with flawed, incomplete, or misleading data. 
  5. People need information they can trust to be correct and current if they are to do the work that furthers business goals and objectives.

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