Python Stddev() Example | Standard Deviation In Python Tutorial is today’s topic. Standard Deviation is the measure of spread in the Statistics. It is used to quantify the measure of spread, variation of the set of data values.

*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

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

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

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

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

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

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

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 b**y **Krunal** at** appdividend.com*

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