# How do you find the standard deviation of a Dataframe in Python?

## How do you find the standard deviation of a Dataframe in Python?

**Standard deviation** is calculated using the function . **std**() . However, the **Pandas** library creates the **Dataframe** object and then the function . **std**() is applied on that **Dataframe** .

## How does Python Numpy calculate standard deviation?

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**.

## Why do we calculate variance?

**Variance** is a measurement of the spread between numbers in a data set. Investors use **variance** to see how much risk an investment carries and whether it **will** be profitable. **Variance** is also used to compare the relative performance of each asset in a portfolio to achieve the best asset allocation.

## What does the variance tell us in statistics?

**Variance** measures how far a set of data is spread out. A **variance** of zero indicates that all of the data values are identical. ... A high **variance** indicates that the data points are very spread out from the **mean**, and from one another. **Variance** is the average of the squared distances from each point to the **mean**.

## What is variance in simple words?

**Variance** describes how much a random variable differs from its expected value. The **variance** is defined as the average of the squares of the differences between the individual (observed) and the expected value. This means that it is always positive.

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