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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 Dictionary Vs List With Examples

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Dictionary and List we use interchangeably in Python to store values. For beginners, both look the same. In reality, they both differ. Here are the differences. Dictionary Vs Lists Values in lists are accessed by means of integers called indices, which indicate where in the list a given value is found. Dictionaries access values by means of integers, strings, or other Python objects called keys , which indicate where in the dictionary a given value is found.  In other words, both lists and dictionaries provide indexed access to arbitrary values, but the set of items that can be used as dictionary indices is much larger than, and contains, the set of items that can be used as list indices.   Also, the mechanism that dictionaries use to provide indexed access is quite different from that used by lists. Both lists and dictionaries can store objects of any type. Values stored in a list are implicitly ordered by their positions in the list because the indices that access these values are c
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