stdev() method in Python statistics module

The stdev() function in Python's statistics module is used to calculate the standard deviation of a dataset. It helps to measure the spread or variation of values in a sample. Standard deviation (SD) measures the spread of data points around the mean. A low SD indicates data points are close to the mean, while a high SD shows they are spread out. Unlike variance, SD is in the same units as the data, making it easier to interpret.

Where:

• x_1,x_2,x₃,.......,x_N are the individual data points
• \overline{\rm x} is the mean of the data
• N is the number of data points in the sample

Example:

import statistics

a = [1, 2, 3, 4, 5]
print(statistics.stdev(a))

1.5811388300841898

Syntax of stdev() method

statistics.stdev(data, xbar=None)

Parameters:

• data: The dataset (list, tuple, etc.) of real numbers.
• xbar (optional): The pre-calculated mean if not given, Python computes it.

Returns: The standard deviation of the values in the dataset.

Examples of stdev() method

Example 1: In this example, we calculate the standard deviation for four datasets to measure the spread, including integers, floating-point numbers and negative values.

from statistics import stdev

# different datasets
a = (1, 2, 5, 4, 8, 9, 12)
b = (-2, -4, -3, -1, -5, -6)
c = (-9, -1, 0, 2, 1, 3, 4, 19)
d = (1.23, 1.45, 2.1, 2.2, 1.9)

print(stdev(a))
print(stdev(b))
print(stdev(c))
print(stdev(d))

3.9761191895520196
1.8708286933869707
7.8182478855559445
0.41967844833872525

Example 2: In this example, we calculate the standard deviation and variance for a dataset to measure the spread of values.

import statistics
a = [1, 2, 3, 4, 5]

print(statistics.stdev(a))
print(statistics.variance(a))

1.5811388300841898
2.5

Example 3: In this example, we calculate the standard deviation by providing a precomputed mean using the xbar parameter in the stdev() function to avoid recalculating the mean.

import statistics
a = (1, 1.3, 1.2, 1.9, 2.5, 2.2)

# Precomputed mean
mean_val = statistics.mean(a)
print(statistics.stdev(a, xbar=mean_val))

0.6047037842337906

Example 4: In this example, we attempt to calculate the standard deviation of a dataset with a single data point. Since stdev() requires at least two points, it raises a StatisticsError, which is handled using a try-except block.

import statistics

# single data point
a = [1]

try:
    print(statistics.stdev(a))
except statistics.StatisticsError as e:
    print("Error:", e)

Output

Error: stdev requires at least two data points

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Article Tags :

• Python
• Competitive Programming
• DSA
• Python-Built-in-functions

Practice Tags :

• python