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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

Data analytics popular free video course on SAS

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The Introduction to Analytics course is a set of 12 videos that take you through the basics of data analytics and the language of SAS.You should do this course if you are interested in data analytics and would like to pursue it as a career or if you have heard about the buzz it is creating and just want to know what it is all about. Each video is 5 to 30 minutes in length. If done in one go, it should take you about two hours to cover the course. The course is divided into three sections. The first section 'Introduction to Analytics' is a set of 6 videos. Here is a snapshot of the 6 videos: 1. What is analytics? This module explains the basis of analytics. 2. Why is analytics popular? This module talks about why analytics has become a big buzzword in business circles and the advantages of analytics. 3. Analytics applications? Here you will be introduced to the various analytics applications popularly used today. 4. Analytics technology Link to free course L