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The Quick and Easy Way to Analyze Numpy Arrays

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

How to learn Tableau best way with self Study tutorials

#Tips To Mastering Tableau Self Study Video Tutorials
#Tips To Mastering Tableau Self Study Video Tutorials
The Tableau training website offers a multitude of resources for Tableau users with many of the videos being brief and addressing specific topics. This self-study syllabus organizes those videos to help you find the training you need on specific topics quickly. Tableau 9 for Data Science Engineers.

To learn any Software Tool, you need to follow these steps:
  1. Tutorials - Either on-line or class room
  2. Books -Read theory from the scratch
  3. Hands on Training - Just practice what you learnt
  4. Materials -Written by experienced developers
  5. Blogs/Websites/Forums give you much insights
The below link contains valuable video tutorials. You can learn Tableau quickly in a just few days.

Take Video Lessons Here


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