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The Quick and Easy Way to Analyze Numpy Arrays

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

6 Python Directory Commands Useful to Read

Here's logic to create Python Directory . You need to import the 'OS' package to create Python directory. Here're the list of Python directory commands. Python How to Create Directory Here's Logic You can create and delete directories in Python. Here's the helpful logic you can use for your projects. For this, you need to import 'os'.  Python Directories 1. How to Create a Directory Import os  os.mkdir('datafiles') 2. How to Change Directory os.chdir('newdirectory') 3. How to Create a Directory and then Create a file in it import os  os.mkdir('datafiles/newfiles');  os.chdir('datafiles/newfiles');  fp=open('input.txt', 'w')  fp.write('Hello, Welcome to Programming in Python')  fp.close() 4. How to Know Present Working Directory os.getcwd() 5. How to delete a directory os.rmdir('directoryname') 6. How to get the List of Directories os.listdir() Keep Reading You May Also Like:   55 Best Gift I