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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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Python Function: How to Write Error Logic

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Here's an example python user-defined function. Here, you'll know how to write error conditions. The best examples is if and else. I have shared the logic here for your reference. Python is one of the top programming languages. Python does support Functions . While writing functions you also need to consider some errors. Those are called exceptions. I am explaining how to give error logic in a function of Python. Exception-handling means to have logic for error scenarios. Writing exception I will show in a simple Function. In this post I will give you syntax for writing function and exception.  Here is my simple Function that multiplies two numbers. Logic to write Function in Python to Multiply Two Numbers  def product (num1,num2): prod=num1*num2 print( ' The product of the numbers is \t: '+str(prod) Parameters used the Python Function The 'def' means you are defining function with a name of 'product'. In the parameters of 'product', you can s
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