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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

How to Decode Python Exception Messages Like a Pro

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While developing python programs, you might see exception messages from python. Here's an explanation to understand each part of the message. Here're tips on how to understand python exceptions. You can find two kinds of exceptions. These are StandardError and StopIteration errors. Here is a chart that shows the types of python errors. Python exceptions class Python exceptions are basically three parts. Reading an error message produced by  Python is not very difficult . The error type, the error description, and the traceback. Understand the python exception message The Error Type There are so many in-built exception types in python. Here is the command to get all the exception types: [x for x in dir(__builtins__) if 'Error' in x] The Error description The text message right after the error type gives us a description of what exactly the problem was. These descriptions are sometimes very accurate, sometimes not. Sample error Traceback (most recent call last):       Fil