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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

How to Write Python 'Hello World' Program Quickly and Run it

The first Python program looks like the below.  I have explained the steps you need to write your first program in Python.
First Python Program

My first program: odbchelper.py

You can write your program as nameccheck.py module.

if authorsFirstName == 'Irv':
      teachingPython = True
      print 'Pay attention to his wisdom'

How to Run Your Python Program

python namecheck.py

Sample python program

if authorsFirstName == 'Irv':
     teachingPython = True
   print 'Pay attention to his wisdom'

The above if condition checks for first name. 

In python '==', means equal to. It makes true to teachingPython

You can start your python program quickly. Really useful for learning and to use it in projects.


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