NumPy Aggregate and Statistical Functions

Functions	Description
np.mean()	Compute the arithmetic mean along the specified axis.
np.std()	Compute the standard deviation along the specified axis.
np.var()	Compute the variance along the specified axis.
np.sum()	Sum of array elements over a given axis.
np.prod()	Return the product of array elements over a given axis.
np.cumsum()	Return the cumulative sum of the elements along a given axis.
np.cumprod()	Return the cumulative product of elements along a given axis.
np.min(), np.max()	Return the minimum / maximum of an array or minimum along an axis.
np.argmin(), np.argmax()	Returns the indices of the minimum / maximum values along an axis
np.all()	Test whether all array elements along a given axis evaluate to True.
np.any()	Test whether any array element along a given axis evaluates to True.

import numpy as np
 
array1 = np.array([[10, 20, 30], [40, 50, 60]])
 
print("Mean: ", np.mean(array1))
 
print("Std: ", np.std(array1))
 
print("Var: ", np.var(array1))
 
print("Sum: ", np.sum(array1))
 
print("Prod: ", np.prod(array1))

Sample output of above program.

Mean:  35.0

Std:  17.07825127659933

Var:  291.6666666666667

Sum:  210

Prod:  720000000

Create NumPy Array

Transform List or Tuple into NumPy array

Special NumPy functions for generating arrays

Arrays with arange()

Shape of an array

Data Types Supported by NumPy

Dimension of an array

Resize an array

Reshape an array

Arrays with linspace()

Zero Array

One Array

Eye Array

Arrays with logspace()

Full Array

Random Number Array

Identity and Diagonal Array

Operations on NumPy Arrays

Indexing

Multidimensional Indexing

Single Dimensional Slicing

Multidimensional Slicing

Manipulating the Dimensions and the Shape of Arrays

Flips the order of the Axes

Joining and Stacking

Algebra with Arrays

Arithmetic Operations

Scalar Arithmetic Operations

Elementary Mathematical Functions

Element-wise Mathematical Operations

Aggregate and Statistical Functions

Useful functions for Conditional and Logical Expressions

Updating using where()

Updating using select()

Selection using choose()

Logical Operations

Standard Set Operations

Python Programming

NumPy Aggregate and Statistical Functions

Sample output of above program.