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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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How to Initialize Class Variables? The Purpose of Init Method in Python

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The init method is like a constructor in Java. But the usage is different in Python.  Here's the best example to write Class in Python using init method.  The init executes by default and it will initialize all the variable. The dog_1 is an instantiation of dog class. When you print the dog_1, it prints as "I am in the init method", which is from the "init" method. The self means this class. It is mandatory. Not only self, but you can also give any name in that place. Instead of "self" you can give as "This_is_Python_Self". It also will work. How to use init method class dog:    def __init__(self):          print("I am in init method") Now, instantiating the class dog_1=dog() print(dog_1) The output from the above display is as below: I am in init method <__main__.dog object at 0x7fe7b5875be0> Related posts The best Python Interview Questions
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