Numpy is numerical library of python. Numpy used for numerical and scientific computing.

NumPy is a multidimensional array and a collection of routines for processing those arrays. We can work with multidimensions x,y and z axis.

We have some methods in numPy library using this we can process multidimensional array.

## How to create single dimension array?

```
import numpy as np
n1 = np.array([10,20,30,40])
```

## How to create multi dimensional array?

```
import numpy as np
n2 = np.array([10,20,30], [40,50,60])
```

## How to initializing numPy array?

**1: With Zero: **We can initialize numpy array with zeros.

```
import numpy as np
n1 = np.zeros((1,2))
```

We will numPy array with zeros in which one row and two column.

**2: With same values: **We can initialize numpy array with same values.

```
import numpy as np
n1 = np.full((2,2),13)
```

In this we creating a array of two columns and two rows where value is 13.

3: **With Range**: We can initialize numpy array within a range.

```
import numpy as np
n1 = np.arange(10,50,5)
Output: ([10,15,20,25,30,35,40,45])
```

## How to change shape of numPy array?

```
import numpy as np
n1=np.array([1,2,3][4,5,6])
n1.shape
Output: (2,3)
```

## How to change shape of numpy array?

```
import numpy as np
n1.shape = (3,2)
```

## How to join numPy array?

1: **vstack**: We can join numPy array vertically.

```
import numpy as np
n1 = np.array([10,20,30])
n2 = np.array([40,50,60])
np.vstack((n1,n2))
Output: ([ [10,20,30],
[40,50,60] ])
```

2: Hstack: We can join numPy array Horizontally .

```
import numpy as np
n1 = np.array([10,20,30])
n2 = np.array([40,50,60])
np.vstack((n1,n2))
Output: ( [10,20,30, 40,50,60] )
```

3: Column stack: We can join numPy array column wise.

```
import numpy as np
n1 = np.array([10,20,30])
n2 = np.array([40,50,60])
np.column_stack((n1,n2))
Output: ([ [10,20],
[30, 40],
[50,60] ])
```