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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 Find Factorial in Python for Any Number

I have explained how to find factorial for a given number in Python using my own script fact.fy.
A module is created as a script file, which contains function definitions that can be called in two ways:

  • From the interpreter
  • From another script file or from another function

python factorial logic

How to import a Script from Linux to Python Console

I have written a script fact.fy

# This program illustrates the designing/creation of a module

def factorial(n):
        "This module computes factorial"
        f=1;
        for i in range (1, n+1):
                  f=f*i;
        print(f)
        return 

In interpreter...
>>> import fact       ==> Import from Linux
>>>fact.factorial(5)
120

What is script reloading?

The Python interpreter imports a module only once in a session. 

If some modifications are performed in the script, then it must be reloaded (imported) again in the interpreter for future use.

A script is a reusable component and you can add n number of functions inside of it.

Directory function in Python.

In order to see the list of function names defined in a module, Python is provided with a built-in function called dir().

It displays the list of all the function definition names as follows:

>>>dir()

['__builtins__', '__cached__', '__doc__', '__file__', 
'__loader__','__name__', '__package__','__spec__',
'fib']

Another way if we give 'module' name in dir(), you will get a list of all functions inside of it.

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