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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 Prepare Resume Using Online Tool

Here are five ideas to prepare resume using online tools. The resume surely will impress  HR and interviewer. Ideas for Online Resume Here is an open-source tool so that anyone can build a digital resume on their own domain . (It’s free.)  Don’t just showcase your relevant work experience; showcase your personality.  Set up a professional email, preferably at your own domain name.  Empower others to spread the message for you (Social media) Think outside the box to creatively get the attention of decision makers. Related 7 Tips to prepare resume Exclusive ideas to prepare resume for IT jobs