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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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5 Top Code Format Tools

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I have given in this post the list of code formatting tools. These are useful to write better code.

5 Top Code Format Tools
  1. SQL Formatter - This tool helps you format your SQL Queries instantly.
  2. Java Code format Tool - This tool is one of the best tool to format your JAVA code instantly.
  3. Python Code Format Tool - This tool is famous Python online code format tool.
  4. CSS Code format Tool - The best tool to format your CSS code so nicely
  5. JavaScript Code Format Tool - This is one of the best tool to format your JavaScript code

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