Python program to find standard deviation (2024)

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Home »Python »Python Programs

Standard deviation in Python: Here, we are going to learn how to find the standard deviation using python program?By Anuj Singh Last updated : January 04, 2024

Problem statement

Given a dataset (list), you have to write a Python program to find the standard deviation based on the given dataset.

Standard deviation in Python

While dealing with a large data, how many samples do we need to look at before we can have justified confidence in our answer? This depends on the variance of the dataset.

Variance tells us about the divergence and the inconsistency of the sample. The standard deviation of a collection of values is the square root of the variance. While it contains the same information as the variance. But Standard deviation is quite more referred. Why? Look at the below statement:

  • The mean income of the population is 846000 with a standard deviation of 4000.
  • The mean income of the population is 846000 with a variance of 16000000.

Now see which statement is more favorable and therefore we use standard deviation.

So in this article, we are going to build a function for finding the standard deviation.

So the following function can be used while working on a program with big data which is very useful and help you a lot.

So here is the function code:

Python program to find standard deviation

# Code to find standard deviation# Defining the function to find the# standard deviationdef stdv(X): mean = sum(X) / len(X) tot = 0.0 for x in X: tot = tot + (x - mean) ** 2 return (tot / len(X)) ** 0.5# Main code# Simple datasetsample = [1, 2, 3, 4, 5]print("Standard Deviation of the sample is: ", stdv(sample))sample = [1, 2, 3, -4, -5]print("Standard Deviation of the sample is: ", stdv(sample))sample = [10, -20, 30, -40, 50]print("Standard Deviation of the sample is: ", stdv(sample))

Output

The output of the above example is:

Standard Deviation of the sample is: 1.4142135623730951 Standard Deviation of the sample is: 3.2619012860600183 Standard Deviation of the sample is: 32.61901286060018 

To understand the above program, you should have the basic knowledge of the following Python topics:

  • Python Variables
  • Python Data Types
  • Python print() Method
  • Python Functions
  • Python Loops
  • Python len() Method

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Python program to find standard deviation (2024)

FAQs

How to find std deviation in Python? ›

stdev() method calculates the standard deviation from a sample of data. Standard deviation is a measure of how spread out the numbers are. A large standard deviation indicates that the data is spread out, - a small standard deviation indicates that the data is clustered closely around the mean.

Is there an easier way to find standard deviation? ›

To do this, subtract the mean value from each data point value. Square each variance and add the totals together to get a single figure. You can then divide this by the total number of data points, minus one. Find standard deviation by calculating the square root of the variance you've just calculated.

How to find standard deviation in Python without inbuilt function? ›

By Hand
  1. First, find the mean of the list: (1 + 5 + 8 + 12 + 12 + 13 + 19 + 28) = 12.25.
  2. Find the difference between each entry and the mean and square each result: (1 - 12.25)^2 = 126.5625. ...
  3. Find the sum of all the squared differences: ...
  4. Divide the sum by n , the number of entries in the list: ...
  5. Finally, take the square root!
Sep 29, 2022

How to get std of a list in Python? ›

The numpy. std() function calculates the statistical measure of how the data in a NumPy array or list is spread out from the mean. It returns the standard deviation, which is a measure of the amount of variation or dispersion of the data in the array.

How do you find standard deviation in coding? ›

Population standard deviation is computed using the formula square root of ( ∑ ( Xi – ų ) ^ 2 ) / N, where: ∑ is the sum of each element. Xi is each element of the array. ų is the mean of the elements of the array.

How do you calculate STD deviation? ›

  1. Step 1: Find the mean.
  2. Step 2: Subtract the mean from each score.
  3. Step 3: Square each deviation.
  4. Step 4: Add the squared deviations.
  5. Step 5: Divide the sum by one less than the number of data points.
  6. Step 6: Take the square root of the result from Step 5.

What is the quick method for standard deviation? ›

Step 1: Find the mean. Step 2: For each data point, find the square of its distance to the mean. Step 3: Sum the values from Step 2. Step 4: Divide by the number of data points.

Why is standard deviation so hard? ›

Last, standard deviation can be difficult to calculate manually. As opposed to other measurements of dispersion such as range (the highest value minus the lowest value), standard deviation requires several cumbersome steps and is more likely to incur computational errors compared to easier measurements.

How to find standard deviation of a particular column in Python? ›

Pandas DataFrame std() Method

The var() method calculates the variance for each column. By specifying the column axis ( axis='columns' ), the var() method searches column-wise and returns the variance for each row.

What is a good standard deviation? ›

Statisticians have determined that values no greater than plus or minus 2 SD represent measurements that are are closer to the true value than those that fall in the area greater than ± 2SD. Thus, most QC programs require that corrective action be initiated for data points routinely outside of the ±2SD range.

How to find standard deviation using Python? ›

Statistics module in Python provides a function known as stdev() , which can be used to calculate the standard deviation. stdev() function only calculates standard deviation from a sample of data, rather than an entire population.

How to calculate standard deviation with numpy? ›

The numpy module of Python provides a function called numpy. std(), used to compute the standard deviation along the specified axis. This function returns the standard deviation of the array elements. The square root of the average square deviation (computed from the mean), is known as the standard deviation.

How to calculate standard deviation in pandas? ›

Computing the Standard Deviation of a Pandas Series

It is computed by taking the square root of the sum of the squared differences between each value and the mean, divided by the total number of values. To compute the standard deviation of a Pandas series, you can use the std() method.

How to calculate std deviation in numpy? ›

Use numpy. std() to calculate the standard deviation of the entire array (no axis specified). it will calculate all the values in an array and return the std value.

How do you find the mean deviation in Python? ›

Explanation
  1. A list is defined and is displayed on the console.
  2. The 'sum' of the list and the 'len' of the list is obtained.
  3. The 'sum' is divided by the 'len'.
  4. This is assigned to a variable.
  5. Now, the elements in the list are iterated and squared.
  6. Their sum is obtained and assigned to another variable.
Sep 20, 2021

How to get sqrt in Python? ›

Python math.sqrt() Method

The math.sqrt() method returns the square root of a number. Note: The number must be greater than or equal to 0.

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