Python provides some built-in functions to do statistics. These built-in functions are more useful when you analyzing your data sets. The `statistics`

module was new in Python 3.4. Click here to see list of functions available in this module and also please go throw once how to use each and every function.

Here I am presenting some functions by constraining to our requirement. If you to learn all functions you can to throw the link provided above and it is good to lean all these functions.

# Python code to demonstrate stdev() function # importing Statistics module import statistics # creating a simple data - set sample = [1, 2, 3, 4, 5] # Prints standard deviation # xbar is set to default value of 1 print("Standard Deviation of sample is % s "% (statistics.stdev(sample)))

The output is

Standard Deviation of sample is 1.5811388300841898

Python program for calculating Mean

# Python program to demonstrate mean() # function from the statistics module # Importing the statistics module import statistics # list of positive integer numbers data1 = [1, 3, 4, 5, 7, 9, 2] x = statistics.mean(data1) # Printing the mean print("Mean is :", x)

Output:

Mean is : 4.428571428571429

Python program for calculating frequencies of numbers

def CountFrequency(my_list): # Creating an empty dictionary freq = {} for item in my_list: if (item in freq): freq[item] += 1 else: freq[item] = 1 for key, value in freq.items(): print ("% d : % d"%(key, value)) # Driver function if __name__ == "__main__": my_list =[1, 1, 1, 5, 5, 3, 1, 3, 3, 1, 4, 4, 4, 2, 2, 2, 2] CountFrequency(my_list)

Output:

1 : 5 5 : 2 3 : 3 4 : 3 2 : 4

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