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## Numpy Mathematical Functions

NumPy contains a large number of various mathematical operations. NumPy provides standard trigonometric functions, functions for arithmetic operations, handling complex numbers, etc.

## Numpy Trigonometric functions

NumPy has standard trigonometric functions which return trigonometric ratios for a given angle in radians.

```
import numpy as np
arr = np.array([0, 30, 60, 90, 120, 150, 180])
print("\nThe sin value of the angles",end = " ")
print(np.sin(arr * np.pi/180))
print("\nThe cosine value of the angles",end = " ")
print(np.cos(arr * np.pi/180))
print("\nThe tangent value of the angles",end = " ")
print(np.tan(arr * np.pi/180))
```

output
```
The sin value of the angles
[0.00000000e+00 5.00000000e-01 8.66025404e-01 1.00000000e+00
8.66025404e-01 5.00000000e-01 1.22464680e-16]

The cosine value of the angles
[ 1.00000000e+00  8.66025404e-01  5.00000000e-01  6.12323400e-17
-5.00000000e-01 -8.66025404e-01 -1.00000000e+00]

The tangent value of the angles [ 0.00000000e+00  5.77350269e-01  1.73205081e+00  1.63312394e+16
-1.73205081e+00 -5.77350269e-01 -1.22464680e-16]
```

## numpy.around() function

This is a function that returns the value rounded to the desired precision.

```import numpy as np
arr = np.array([12.202, 90.23120, 123.020, 23.202])
print("printing the original array values:",end = " ")
print(arr)
print("Array values rounded off to 2 decimal position",np.around(arr, 2))
print("Array values rounded off to -1 decimal position",np.around(arr, -1))

```

output
```
printing the original array values: [ 12.202   90.2312 123.02    23.202 ]
Array values rounded off to 2 decimal position [ 12.2   90.23 123.02  23.2 ]
Array values rounded off to -2 decimal position [ 10.  90. 120.  20.]
```

## numpy.floor() function

This function is used to return the floor value of the input data which is the largest integer not greater than the input value.

```import numpy as np
arr = np.array([12.202, 90.23120, 123.020, 23.202])
print(np.floor(arr))

```

output
```
[ 12.  90. 123.  23.]

```

## numpy.ceil() function

The ceil() function returns the ceiling of an input value,

```import numpy as np
arr = np.array([12.202, 90.23120, 123.020, 23.202])
print(np.ceil(arr))

```

output
```
[ 13.  91. 124.  24.]

```