# Aggregate and Statistical Functions In Numpy

In this tutorial, we will learn about the **aggregate and statistical** functions in **Numpy**. **Numpy** has fast built-in **aggregate and statistical** for working on arrays. By using these function or if we have good knowledge of these functions than we will play with arrays.

## Aggregate and Statistical Functions in Numpy – Python

First, we have to import Numpy as **import numpy as np. **To make a **Numpy** array, you can just use the **np.array()** function. The aggregate and statistical functions are given below:

**np.sum(m)**: Used to find out the**sum**of the given array.**np.prod(m)**: Used to find out the**product(multiplication)**of the values of m.**np.mean(m)**: It returns the**mean**of the input array m.**np.std(m)**: It returns the**standard deviation**of the given input array m.**np.var(m)**: Used to find out the**variance**of the data given in the form of array m.**np.min(m)**: It returns the**minimum value**among the elements of the given array m.**np.max(m)**: It returns the**maximum value**among the elements of the given array m.**np.argmin(m)**: It returns the**index of the minimum value**among the elements of the array m.**np.argmax(m)**: It returns the**index of the maximum value**among the elements of the array m.**np.median(m)**: It returns the**median**of the elements of the array m.

The code using the above all the function is given below:

import numpy as np a=np.array([1,2,3,4,5]) print("a :",a) sum=np.sum(a) print("sum :",sum) product=np.prod(a) print("product :",product) mean=np.mean(a) print("mean :",mean) standard_deviation=np.std(a) print("standard_deviation :",standard_deviation) variance=np.var(a) print("variance :",variance) minimum=np.min(a) print("minimum value :",minimum) maximum=np.max(a) print("maximum value :",maximum) minimum_index=np.argmin(a) print("minimum index :",minimum_index) maximum_index=np.argmax(a) print("maximum-index :",maximum_index) median=np.median(a) print("median :",median)

Output is:

a : [1 2 3 4 5] sum : 15 product : 120 mean : 3.0 standard_deviation : 1.4142135623730951 variance : 2.0 minimum value : 1 maximum value : 5 minimum index : 0 maximum-index : 4 median : 3.0

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