# How to get the floor, ceiling and truncated values of the elements of a numpy array?

• Last Updated : 29 Aug, 2020

In this article, let’s discuss how to get the floor, ceiling, and truncated values of the elements of a Numpy array. First, we need to import the NumPy library to use all the functions available in it. This can be done with this import statement:

```import numpy as np
```

### Getting the floor value

The greatest integer that is less than or equal to x where x is the array element is known as floor value. It can found using the function numpy.floor()

Syntax:

```numpy.floor(x[, out]) = ufunc ‘floor’)
```

Example 1:

## Python

 `# Import the numpy library``import` `numpy as np`` ` ` ` `# Initialize numpy array``a ``=` `np.array([``1.2``])`` ` `# Get floor value``a ``=` `np.floor(a)``print``(a)`

Output:

```[1.]
```

Example 2:

## Python

 `import` `numpy as np`` ` ` ` `a ``=` `np.array([``-``1.8``, ``-``1.6``, ``-``0.5``, ``0.5``,``              ``1.6``, ``1.8``, ``3.0``])`` ` `a ``=` `np.floor(a)``print``(a)`

OutPut:

```[-2., -2., -1., 0., 1., 1., 3.]
```

### Getting the ceil value

The least integer that is greater than or equal to x where x is the array element is known as ceil value. It can be found using the numpy.ceil() method.

Syntax:

```numpy.ceil(x[, out]) = ufunc ‘ceil’)
```

Example 1:

## Python

 `# Import the numpy library``import` `numpy as np`` ` ` ` `# Initialize numpy array``a ``=` `np.array([``1.2``])`` ` `# Get ceil value``a ``=` `np.ceil(a)``print``(a)`

Output:

```[2.]
```

Example 2:

## Python

 `import` `numpy as np`` ` ` ` `a ``=` `np.array([``-``1.8``, ``-``1.6``, ``-``0.5``, ``0.5``,``              ``1.6``, ``1.8``, ``3.0``])`` ` `a ``=` `np.ceil(a)``print``(a)`

Output:

```[-1., -1., -0., 1., 2., 2., 3.]
```

### Getting the Truncate value

The trunc of the scalar x is the nearest integer i which, closer to zero than x. This simply means that, the fractional part of the signed number x is discarded by this function. It can be found using the numpy.trunc() method.

Syntax:

```numpy.trunc(x[, out]) = ufunc ‘trunc’)
```

Example 1:

## Python

 `# Import the numpy library``import` `numpy as np`` ` ` ` `# Initialize numpy array``a ``=` `np.array([``1.2``])`` ` `# Get truncate value``a ``=` `np.trunc(a)``print``(a)`

Output:

```[1.]
```

Example 2:

## Python

 `import` `numpy as np`` ` ` ` `a ``=` `np.array([``-``1.8``, ``-``1.6``, ``-``0.5``, ``0.5``,``              ``1.6``, ``1.8``, ``3.0``])`` ` `a ``=` `np.trunc(a)``print``(a)`

Output:

```[-1., -1., -0., 0., 1., 1., 3.]
```

Example to get floor, ceil, trunc values of the elements of a numpy array

## Python

 `import` `numpy as np`` ` ` ` `input_arr ``=` `np.array([``-``1.8``, ``-``1.6``, ``-``0.5``, ``0.5``, ``                      ``1.6``, ``1.8``, ``3.0``])``print``(input_arr)`` ` `floor_values ``=` `np.floor(input_arr)``print``(``"\nFloor values : \n"``, floor_values)`` ` `ceil_values ``=` `np.ceil(input_arr)``print``(``"\nCeil values : \n"``, ceil_values)`` ` `trunc_values ``=` `np.trunc(input_arr)``print``(``"\nTruncated values : \n"``, trunc_values)`

Output:

```[-1.8 -1.6 -0.5  0.5  1.6  1.8  3. ]

Floor values :
[-2. -2. -1.  0.  1.  1.  3.]

Ceil values :
[-1. -1. -0.  1.  2.  2.  3.]

Truncated values :
[-1. -1. -0.  0.  1.  1.  3.]
```

My Personal Notes arrow_drop_up