# How to find skewness of data using Python

In this tutorial, we are going to learn how to find skewness of data using Python. We can easily find skewness of any data in Python using the following library that is Scipy.stats.

## Find skewness of data in Python using Scipy

we simply use this library by

`from Scipy.stats import skew`

### Skewness based on its types

There are three types of skewness :

• Normally Distributed: In this, the skewness is always equated to zero.

Skewness=0

• Positively skewed distribution: In this, A Positively-skewed distribution has a long right tail, that’s why this is also known as right-skewed distribution. the reason behind it, in this value of mode is highest and mean is least which leads to right peak.

Skessness >o

• Negatively skewed distribution: In this, a negatively skewed distribution has a long left tail, that’s why this is also known as left-skewed distribution. the reason behind it, in this value of mode is least and mean is highest just reverse to right-skewed which leads to the left peak.

Skewness<0

## The formula to find skewness of data

Skewness =3(Mean- Median)/Standard Deviation

Example: skewness for given data

Input: Any random ten input

```from scipy.stats import skew
import numpy as np
x= np.random.normal(0,5,10)
print("X:",x)
print("Skewness for data :",skew(x))
```

Output:

```X: [ 5.51964388 -1.69148439 -5.55162585 -5.6901246   2.38861009  2.73400871
3.77918369 -2.30759396  3.67021073  1.48142813]
Skewness for data : -0.4625020248485552```

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