Python Programming Training Certification
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Course Overview
Python is one of the world’s top programming languages used today and Python training has become the most popular training across individuals. Training Basket’s Python Training & Certification course covers basic and advanced Python concepts and how to apply them in real-world applications.Python is a flexible and powerful open-source language that is easy to learn and consists of powerful libraries for data analysis and manipulation. Our Python training course content is curated by experts as per the standard Industry curriculum. The curriculum, coding challenges and real-life problems cover data operations in Python, strings, conditional statements, error handling, shell scripting, web scraping and the commonly used Python web framework Django. Take this Python training and certification course and become job-ready now.
Python statistics module
Python statistics module provides the functions to mathematical statistics of numeric data. There are some popular statistical functions defined in this module.
mean() function
The mean() function is used to calculate the arithmetic mean of the numbers in the list.
Example
-
import statistics
# list of positive integer numbers
datasets = [5, 2, 7, 4, 2, 6, 8]
x = statistics.mean(datasets)
# Printing the mean
print(“Mean is :”, x)
Output:
- Mean is : 4.857142857142857
median() function
The median() function is used to return the middle value of the numeric data in the list.
Example
-
import statistics
datasets = [4, -5, 6, 6, 9, 4, 5, -2]
# Printing median of the
# random data-set
print(“Median of data-set is : % s ”
% (statistics.median(datasets)))
Output:
- Median of data-set is : 4.5
mode() function
The mode() function returns the most common data that occurs in the list.
Example
-
import statistics
# declaring a simple data-set consisting of real valued positive integers.
dataset =[2, 4, 7, 7, 2, 2, 3, 6, 6, 8]
# Printing out the mode of given data-set
print(“Calculated Mode % s” % (statistics.mode(dataset)))
Output:
- Calculated Mode 2
stdev() function
The stdev() function is used to calculate the standard deviation on a given sample which is available in the form of the list.
Example
-
import statistics
# creating a simple data – set
sample = [7, 8, 9, 10, 11]
# Prints standard deviation
print(“Standard Deviation of sample is % s ”
% (statistics.stdev(sample)))
Output:
- Standard Deviation of sample is 1.5811388300841898
median_low()
The median_low function is used to return the low median of numeric data in the list.
Example
-
import statistics
# simple list of a set of integers
set1 = [4, 6, 2, 5, 7, 7]
# Note: low median will always be a member of the data-set.
# Print low median of the data-set
print(“Low median of data-set is % s ”
% (statistics.median_low(set1)))
Output:
- Low median of the data-set is 5
median_high()
The median_high function is used to return the high median of numeric data in the list.
Example
-
import statistics
# list of set of the integers
dataset = [2, 1, 7, 6, 1, 9]
print(“High median of data-set is %s ”
% (statistics.median_high(dataset)))
Output:
- High median of the data-set is 6
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