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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 Default Argument is Self Why do We Need it

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Python self as default argument, here is the reason. Below, you will find an example and the importance of self-argument. Structure of a class The default argument is self. The self-argument states the function belongs to the class that we refer to here. Access to class members' details of one member to another is possible through self-argument. So self-argument is mandatory. class <name of the class>: def <function name>(<arguments>): ... <members> Self Argument A python class consists of methods these also called functions. The default self-argument you need to supply in all the class methods . Python class with self argument class employee:      def getdata(self):           self.name=input('Enter name\t:')           self.age=input('Enter age\t:')     def putdata(self):           print('Name\t:',self.name)          print('Age\t:',self.age)  e1=employee()  e1.getdata()  e1.putdata() Output from python class Here,  I have I
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