Originally published by Krunal at appdividend.com
It is very much similar to the variance, gives the measure of deviation, whereas variance provides a squared value. In this blog, we have already covered Python mean(), Python median(), Python mode(), and Python variance() function.
Content Overview
- 1 Python Stddev() Example
- 2 #Pass the xbar parameter
- 3 #Python standard deviation example using pstdev
- 4 #Use stdev() on a varying set of data types
- 5 #Python standard deviation example using numpy
- 6 #Difference between variance() and stddev()
- 7 #StatisticsError
Python Stddev() Example
There are two ways to calculate a standard deviation in Python.
- Using stdev or pstdev functions of statistics package.
- Using std function of numpy package.
The stdev is used when the data is just a sample of the entire dataset.
The pstdev is used when the data represents the whole population. Note that statistics is a lightweight module added in Python 3.x.
The process of finding standard deviation requires you to know whether the data you have is the entire dataset or it is a sample of a group.
Let’s see the syntax of stddev() function.
stdev([data-set], xbar)
See the following parameters.
[data]: An iterable with real-valued numbers.
xbar (Optional): Takes actual mean of the data-set as value.
See the following code example.
# app.pyimport statistics
dataset = [1, 2, 3, 4, 5]
print("Standard Deviation of a dataset is % s "
% (statistics.stdev(dataset)))
See the following output.
➜ pyt python3 app.py
Standard Deviation of a dataset is 1.5811388300841898
➜ pyt
Let’s take another example.
# app.pyimport statistics
dataset = [11, 21, 18, 19, 46]
print("Standard Deviation of dataset is % s "
% (statistics.stdev(dataset)))
See the following output.
➜ pyt python3 app.py
Standard Deviation of dataset is 13.397761006974262
➜ pyt
Pass the xbar parameter
Okay, let’s take the list and now while finding the stddev, we pass the second parameter to the function called xbar and see the output.
# app.pyimport statistics
dataset = [11, 21, 18, 19, 46]
meanValue = statistics.mean(dataset)
print("Standard Deviation of the dataset is % s "
% (statistics.stdev(dataset, xbar=meanValue)))
See the output.
➜ pyt python3 app.py
Standard Deviation of the dataset is 13.397761006974262
➜ pyt
Python standard deviation example using pstdev
Let’s take an example using Python Statistics pstdev() function.
# app.pyimport statistics
dataset = [11, 21, 18, 19, 46]
print("Standard Deviation of a dataset is % s "
% (statistics.pstdev(dataset)))
See the following output.
➜ pyt python3 app.py
Standard Deviation of a dataset is 11.983321743156194
➜ pyt
Use stdev() on a varying set of data types
See the following code.
# app.pyfrom statistics import stdev
from fractions import Fraction as fr
sample1 = (21, 19, 11, 14, 18, 19, 46)
sample2 = (-21, -19, -11, -14, -18, -19, -46)
sample3 = (-9, -1, -0, 2, 1, 3, 4, 19)
sample4 = (21.23, 19.45, 29.1, 11.2, 18.9)
print(“The Standard Deviation of Sample1 is % s”
% (stdev(sample1)))print(“The Standard Deviation of Sample2 is % s”
% (stdev(sample2)))print(“The Standard Deviation of Sample3 is % s”
% (stdev(sample3)))print(“The Standard Deviation of Sample4 is % s”
% (stdev(sample4)))
See the following output.
➜ pyt python3 app.py
The Standard Deviation of Sample1 is 11.480832888319723
The Standard Deviation of Sample2 is 11.480832888319723
The Standard Deviation of Sample3 is 7.8182478855559445
The Standard Deviation of Sample4 is 6.388906792245447
➜ pyt
Python standard deviation example using numpy
We can execute numpy.std() to calculate standard deviation. First, we need to import numpy library.
See the following output.
# app.pyimport numpy as np
num = [21, 19, 11, 14, 18, 19, 46]
print(“The Standard Deviation of Numpy Data is % s”
% (np.std(num)))
See the following output.
➜ pyt python3 app.py
The Standard Deviation of Numpy Data is 10.629185850136157
➜ pyt
Difference between variance() and stddev()
Okay, let’s take a simple Python List and get its variance() and stddev().
# app.pyimport statistics
dataset = [11, 21, 18, 19, 46]
print("Standard Deviation of the dataset is % s "
% (statistics.stdev(dataset)))
print(“Variance of the dataset is % s”
% (statistics.variance(dataset)))
See the following output.
➜ pyt python3 app.py
Standard Deviation of the dataset is 13.397761006974262
Variance of the dataset is 179.5
➜ pyt
StatisticsError
Okay, now if we only pass the one data point, then it will raise the StatisticsError because the stddev() function requires a minimum of two data points. See the following code.
# app.pyimport statistics
dataset = [11]
print("Standard Deviation of the dataset is % s "
% (statistics.stdev(dataset)))
See the following output.
➜ pyt python3 app.py
Traceback (most recent call last):
File “app.py”, line 6, in <module>
% (statistics.stdev(dataset)))
File “/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/statistics.py”, line 650, in stdev
var = variance(data, xbar)
File “/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/statistics.py”, line 588, in variance
raise StatisticsError(‘variance requires at least two data points’)
statistics.StatisticsError: variance requires at least two data points
➜ pyt
Finally, Python stddev() Example | Standard Deviation In Python Tutorial is over.
Originally published by Krunal at appdividend.com
===================================================================
Thanks for reading :heart: If you liked this post, share it with all of your programming buddies! Follow me on Facebook | Twitter
Learn More
☞ Complete Python Bootcamp: Go from zero to hero in Python 3
☞ Python for Time Series Data Analysis
☞ The complete beginner’s guide to JSON
☞ The Complete Guide to JSON Web Tokens
☞ Python Programming For Beginners From Scratch
☞ Python Network Programming | Network Apps & Hacking Tools
☞ Intro To SQLite Databases for Python Programming
☞ Ethical Hacking With Python, JavaScript and Kali Linux
☞ Beginner’s guide on Python: Learn python from scratch! (New)
☞ Python for Beginners: Complete Python Programming
#python
