# Python NumPy ceil() Function

Python NumPy `ceil()` function is used to return the ceil values for each element of an input array (element-wise). This function takes two arguments `arr` and `out` and returns a new array with ciel values for the source array `arr`. The ceil of the scalar `x` is the smallest integer `i`, such that `i >= x`. In simple words, the ceil value is always greater than equal to the given value.

In this article, I will explain how to find the ceil values of elements of an input array, using the `numpy.ceil()` function with examples.

## 1. Quick Examples of Python NumPy ceil() Function

If you are in a hurry, below are some quick examples of how to use Python NumPy `ceil()` function.

``````
# Below are the quick examples

# Example 1: Create single element array
arr = np.array([7.8])
arr1 = np.ceil(arr)

# Example 2: Create an array
arr = [.6, 5.5, 8.5, 3.5, 4.5, 11.1]
arr1 = np.ceil(arr)

# Example 3: Create an 1-D NumPy array
arr = np.array([-0.8, -4.1, -9.7, -8.0, -5, -6])
arr1 = np.ceil(arr)

# Example 4: Create 2-D array
arr = np.array([[0.8, 4.1, 9.7],[ 8.0, 5 ,6]])
arr1 = np.ceil(arr)
``````

## 2. Syntax of NumPy ceil()

Following is the syntax of `numpy.ceil()`.

``````
# Syntax of ceil()
numpy.ceil(arr [, out]) = ufunc ‘ceil’)
``````

### 2.1 Parameters of NumPy ceil ()

The ceil() function allows mainly two parameters:

`arr`: The values whose ceil values are required. Input array.

`out`: A ndarray the result is stored in. If given, it must have a shape of input `arr`. If not given or None, it returns a freshly-allocated array. It also takes a tuple as input, if given a tuple must have a length equal to the number of outputs (possible only as a keyword argument).

### 2.2 Return Value of ceil()

The `ceil()` function returns the ceil value of each array element and the elements in a returned array would be `float` data type.

## 3. Usage of NumPy ceil() Function

The `numpy.ceil()` is a mathematical function that returns the ceil value of an element array with float data type. The input array elements should have a real numbers and assume x, it rounds the variable in an upwards manner to the nearest integer, and finally returns the nearest integers as ceil values. If a value of x is an integer, it just returns the x value as-is.

The `ciel()` function varies from another NumPy function floor() which is used to return the variable rounded downwards.

Below I have covered some examples to understand the concept of `ceil()`. In order to find out the ceil values of a NumPy array first, we have to create the NumPy array using `numpy.array()`.

## 4. Get the Single ceil Value of 1-Dimensional NumPy Array

To calculate the ceil values of 1-D array elements using `numpy.ceil()` function.

``````
# Import numpy module
import numpy as np

# Create single element array
arr = np.array([7.8])
arr1 = np.ceil(arr)
print(arr1)

# Output:
# [8.]
``````

From the above code, we got a ceil value of the input array named `arr`. That means 7.8 is our float element and its ceil value is 8. (i.e after the nearest integer)

## 5. Get the Multiple ceil Values of 1-D Array

Let’s get the ceil values of the input array with multiple elements. For example,

``````
# Create an 1-D input array
arr = np.array([0.8, 4.1, 9.7, 8.0, 5, 6])
arr1 = np.ceil(arr)
print(arr1)

# Output:
# [ 1.  5. 10.  8.  5.  6.]
``````

## 6. Get the ceil Values of Negative Elements

Let’s calculate the ceil value for negative values. Here I will be using the same as the above example but with negative values.

``````
# Create an 1-D input array
# Use ceil() function
arr = np.array([-0.8, -4.1, -9.7, -8.0, -5, -6])
arr1 = np.ceil(arr)
print(arr1)

# Output :
# [-0. -4. -9. -8. -5. -6.]
``````

From the above, as you can observe the ceil values of negative elements and positive elements of the same array are different.

## 7. Get the ceil() Value of the 2-D NumPy Array

Finally, Let’s use the `ceil()` function for 2-dimensional arrays. Note that syntax doesn’t change for 1-D or 2-D.

``````
# Create 2-D array
arr = np.array([[0.8, 4.1, 9.7],[ 8.0, 5 ,6]])
arr1 = np.ceil(arr)
print(arr1)

# Output:
# [[ 1.  5. 10.]
# [ 8.  5.  6.]]
``````

## 8. Conclusion

In this article, I have explained how to use Python `numpy.ceil()` function, and using this how to calculate the ceil values of all the array elements with examples.

Happy learning !!

## References

### Vijetha

With 5 of experience in technical writing, I have had the privilege to work with a diverse range of technologies like Python, Pandas, NumPy and R. During this time, I have consistently demonstrated my ability to grasp intricate technical details and transform them into comprehensible materials. 