# How to compute the standard deviation of a DataFrame column

1 min

You will often need to compute the standard deviation of a DataFrame column.

Furthermore, in statistics the standard deviation is referred as sigma.

An quite famous analysis is to approximate the range of a value given its two sigma value.

Why ?

Well as you can see 95% of your data will be located between our mu - 2 sigma and mu + 2 sigma.

So it is most probable that our variable value will end up in this range.

Let's have a look at real world example data.

# Reading an example dataframe

``````import pandas as pd

# We read a sample dataset from the web.
df = pd.read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv')
``````

Here we have a example dataset that is about iris flowers.

If we look at the sepal_length of versicolor irises and compute the mean and the std.

This is how we compute the standard deviation using the DataFrame.std() method.

# Computing the standard deviation

## Computing the two sigma range

Here you are, you now know how to compute the two sigma range and will be able to perform statistical tests about it.