# Python programs using NumPy

NumPy in Python a vast library for the Python programmers and users. By providing a large collection of high-level mathematical functions to operate arrays and matrices and many more.

## Some example programs using NumPy in Python

To know more about NumPy math functions: Mathematical Functions In Numpy

### Python program to check the NumPy version in any system-

```import numpy as npcheck
print(npcheck.__version__)```

Write a Python program to create a 3×3 matrix with values ranging from 2 to 10.

```import numpy as np
x = np.array([1,2,3,4,5,6,7,8,9,100,20,30,45,30])
print ("max=",x.max(),"min=",x.min(),"mean=",x.mean(),"var=",x.var())```

Output-

```max= 100

min= 1

mean= 19.285714285714285

var= 664.4897959183675```

### Python program to multiply all values in the list using numpy.prod()-

```import numpy
list1 = [1, 2, 3]
list2 = [3, 2, 4]

# using numpy.prod() to get the multiplications
result1 = numpy.prod(list1)
result2 = numpy.prod(list2)
print("List 1=",result1)
print("List 2=",result2)
```

Output-

```List 1= 6
List 2= 24```

Second Method-

```from functools import reduce
list1 = [1, 2, 3]
list2 = [3, 2, 4]

result1 = reduce((lambda x, y: x * y), list1)
result2 = reduce((lambda x, y: x * y), list2)
print("list 1=",result1)
print("list 2=",result2)
```

Output-

```list 1= 6
list 2= 24

```

### Write a Python program to create a 3×3 matrix-

```import numpy as np
x =  np.arange(2, 11).reshape(3,3)
print(x)
```

Output-

```[[ 2 3 4]
[ 5 6 7]
[ 8 9 10]]```

### Python program to reverse an array-

```import numpy as np
x = np.arange(12, 38)
print("Original array:")
print(x)
print("Reverse array:")
x = x[::-1]
print(x)```

Output-

```Original array:
[12 13 14 15 16 17 18 19]
Reverse array:
[19 18 17 16 15 14 13 12]```

### Python program to append values to the end of an array-

```import numpy as npappend
x = [100, 200, 300]
print("Original array:")
print(x)
x = npappend.append(x, [[400, 500, 610], [700, 810, 900]])
print("After append the values are:")
print(x)```

Output-

```Original array:
[100, 200, 300]
After append  array be like:
[100 200 300 400 500 610 700 810 900]```

### Python program to append values to start and the end of an array-

```import numpy as np
x = [100, 200, 300]
print("Original array:")
print(x)
x = np.append([400, 500, 600],x)
x1=np.append(x,[700,800,900])
print("After appending values:")
print(x1)
```

Output-

```Original array:
[100, 200, 300]
After append values  array will be like:
[400 500 600 100 200 300 700 800 900]```

### Python program for checking the unique elements of an array-

```import numpy as np
x = np.array([10, 10, 20, 20, 30, 30])
print("Original array:")
print(x)
print("Unique elements of the above array:")
print(np.unique(x))
x = np.array([[1, 1], [2, 3]])
print("Original array:")
print(x)
print("Unique elements of the above array:")
print(np.unique(x))
```

Output-

```Original array:
[10 10 20 20 30 30]
Unique elements of the above array:
[10 20 30]
Original array:
[[1 1]
[2 3]]
Unique elements of the above array:
[1 2 3]```