# How to calculate percentiles in NumPy?

In this tutorial, we will learn how to calculate percentiles in NumPy? By Pranit Sharma Last updated : May 25, 2023

A percentile is a score (value) that a specific percentage falls at or below. For example, the 21st percentile is the score below which 21% of the score will be found.

We can understand it by another example, let's suppose if you got 91st percentile in any exam, that means you’re above 91% of the students.

Suppose we are given a sequence for a single-dimensional NumPy array and we need to find a convenient way to calculate percentile from this array.

## Calculating percentiles in NumPy array

To calculate percentiles in NumPy, you can use numpy.percentile() method which calculates and returns the nth percentile of the given data (NumPy array).

### numpy.percentile() Syntax

```numpy.percentile(a, q, axis=None, out=None, overwrite_input=False,
method='linear', keepdims=False, *, interpolation=None)
```

Let us understand with the help of an example,

## Python Programs to Calculate Percentiles in NumPy

Consider the below-given examples to calculate the percentiles with NumPy:

### Example 1: Calculate percentiles with NumPy 1D Array

```# Import numpy
import numpy as np

# data (NumPy array)
arr = np.array([87, 93, 65, 75, 85, 90])

# Printing array
print("Data (arr):\n",arr,"\n")

# Calculating 50th percentile
res = np.percentile(arr, 50)
print("50th Percentile is:\n",res)

# Calculating 91st percentile
res = np.percentile(arr, 91)
print("91st Percentile is:\n",res)
```

#### Output

```Data (arr):
[87 93 65 75 85 90]

50th Percentile is:
86.0
91st Percentile is:
91.65
```

### Example 2: Calculate percentiles with NumPy 2D Array

```# Import numpy
import numpy as np

# data (NumPy array)
arr = np.array([[50,60,80],[60,90,20]])

# Printing array
print("Data (arr):\n",arr,"\n")

# Calculating 99th percentile
res = np.percentile(arr, 99)
print("99th Percentile is:\n",res)

# Calculating 93rd percentile
res = np.percentile(arr, 93)
print("93rd Percentile is:\n",res)
```

#### Output

```Data (arr):
[[50 60 80]
[60 90 20]]

99th Percentile is:
89.5
93rd Percentile is:
86.5
```