 ## डिप्लोमा इन ऑफिस मैनेजमेंट एण्ड अकाउटिंग ## Full Stack Web Development with Laravel ×

# Python Numpy tutorial

NumPy stands for Numerical Python.
NumPy is used for working for arrays.
Numpy are faster than lists because numpy arrays are stored at one continuous place in a memory.

## Install NumPy

`pip install numpy`

## Importing Numpy Module

`import numpy`

## Create an array

`import numpy as npl=[1, 2, 3]x=np.array(l)print(x)`

## Array dimensions

1. 0-D array
2. 1-D array
3. 2-D array
`import numpy as np x=np.array(0)print(type(x))y=np.array([1, 2, 3])print(type(y))z=np.array([[1, 2],[3, 4]])print(type(z))`

`ndim`

## Array indexing

```import numpy as np

x=np.array([1, 2, 3, 4, 5])
print(x)

y=np.array([ [1, 2, 3], [4, 5, 6]])
print(y[1, 0 ])```

## Slicing in 2-D

`y=np.array([ [1, 2, 3], [4, 5, 6]])print(y[1, 0:2 ])`

## Shape of an array

Number of elements in each dimension
`array.shape`

## Reshape an array

Reshape means changing dimension of array.
```import numpy as np
x=np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
print(x.reshape(2, 5))```

## Joining Numpy arrays

Concat more than one arrays together.
`concatenate(arr1, arr2)`
```import numpy as np
x=np.array([1,2,3])
y=np.array([4,5,6])
z=np.concatenate((x,y))
print(z)```

## Splitting numpy arrays

Break a single array into multiple arrays.
`array_split(arr, number_of_array)`
```import numpy as np
x = np.array([1, 2, 3, 4, 5, 6])
y = np.array_split(x, 2)
print(y)```

## Methods

 dot() Return product of two array ```import numpy as np x=np.array([ [1,2], [3,4]]) y=np.array([ [1,2], [3,4] ]) print(x.dot(y)) ``` max Return max value from an array ```import numpy as np x=np.array([ [1,2], [3,4]]) print(x.max()) ``` min Return minimum value fron an array ```import numpy as np x=np.array([ [1,2], [3,4]]) print(x.min()) ``` prod Return product of elements of given axis. ```import numpy as np x=np.array([ [1,2], [3,4]]) print(np.prod( x, axis=1 ))``` sum() Return sum of elements of given array ```import numpy as np x=np.array([ [1,2], [3,4]]) print(np.sum( x))```