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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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Benefits of having Certified SAS Base Programmer

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Why certification is beneficial?

 Professionals in data management, data warehousing or in a business intelligence role would find the certification ideal. In addition, recent college graduates having an inclination to logically solve problems and pursuing to enter the data analysis field will find the certification beneficial to kick start their careers. 
Certification in Base SAS
Base SAS Programmer

This course is also ideal, if you are a working professional OR a recent graduate who is
  • Aspiring to be in fast growing career
  • Looking for a more challenging position
  • Aiming to get into a more skillful role
  • Aspiring to be one of the coolest scientists of 21st century
What is Base Sas?

It's the foundation for all SAS software. Along with an easy-to-learn, flexible programming language, you get a web-based programming interface; ready-to-use programs for data manipulation, information storage and retrieval, descriptive statistics and reporting; a centralized metadata repository; and a macro facility that reduces programming time and maintenance headaches.

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