# NumPy full() Function with Examples

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• Post category:NumPy / Python

The NumPy full() function in Python is used to create an array with a specified shape and fill it with a given value. In this article, I will explain syntax and how to use the `numpy.full()` function which returns an array of fill_value with the given shape, order, and datatype.

## 1. Quick Examples of full() Function

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

``````
# Quick examples of full() function

# Example 1: Use numpy.full() function
# On 1-D array
arr2 = np.full(6, 4)

# Example 2: Use numpy.full() function
# With two-dimensional arrays
arr2 = np.full((4, 3),8)

# Example 3: Return array with dtype=str
arr2 = np.full(shape=(4,3),fill_value='2',dtype=str)

# Example 4: Return array with dtype=str
arr2 = np.full(shape=(3,4),fill_value='3',dtype=float)

# Example 5: Return array with dtype=int
arr2 = np.full((2,4),'7',dtype=int)
``````

## 2. Syntax of NumPy full()

Following is the syntax to create `numpy.full()` function.

``````
# Syntax of numpy.full()
numpy.full(shape, fill_value, dtype=None, order='C', *, like=None)
``````

### 2.1 Parameters of full()

Following are the parameters of full().

• `shape` –  It defines the shape of the array which is an int or sequence of ints. The shape of the new array, e.g., (4, 3) or 2.
• `fill_value `– Value to fill the array with.
• `dtype` – It is an optional parameter that specifies the data type of the returned array.
• `order` – {‘C’, ‘F’}, optional: To store multi-dimensional data in row-major (C) or column-major (F) order/pattern in the memory location.
• `like` – value should be array_like, optional

### 2.2 Return value of full()

It returns ndarray of fill_value with the given shape, order, and datatype.

## 3. Use NumPy full() Function on 1-D Array

To create a one-dimensional Numpy array of size `6`, with the value `4` use NumPy `full()` function. Here `shape=6` is used to specify the length of the array, you’re indicating that you want the output to have six elements and `fill_value=4` specifies the array to be filled with value 4.

In the below example, `np.full(shape=6, fill_value=4)` creates a 1-D array with a shape of 6, and all elements are filled with the value `4`. Adjust the `shape` and `fill_value` parameters as needed for your specific use case.

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

# Use numpy full() function on 1-D array
arr2 = np.full(shape=6, fill_value=4)
print("Full 1-D array:\n", arr2)
``````

Yields below output.

## 4. Use NumPy full() Function with Two-Dimensional Arrays

You can use the `numpy.full()` function to create a two-dimensional array. For instance, `np.full(shape=(4, 3),fill_value=8)` creates a 2-D array with a shape of (4, 3), and all elements are filled with the value `8`. Adjust the `shape` and `fill_value` parameters as needed for your specific use case.

``````
# Use numpy full() function
# With two-dimensional arrays
arr2 = np.full(shape=(4, 3),fill_value=8)
print("Full 2-D array:\n", arr2)

# Output:
# Full 2-D array:
#  [[8 8 8]
#  [8 8 8]
#  [8 8 8]
#  [8 8 8]]
``````

## 5. Return Array with dtype=str

To create a NumPy array with a specified data type (`dtype`) of string, you can use the `dtype` parameter in the `numpy.full()` function.

In the below example, `np.full(shape=(4,3),fill_value='2',dtype=str)` creates a 2-D array with a shape of (4, 3), and all elements are filled with the string value `'2'`, and the data type is set explicitly to `str`. Adjust the `shape`, `fill_value`, and `dtype` parameters as needed for your specific use case.

``````
# Return array with dtype=str
arr2 = np.full(shape=(4,3),fill_value='2',dtype=str)
print("2-D Array with dtype=str::\n", arr2)

# Output:
# 2-D Array with dtype=str::
#  [['2' '2' '2']
#  ['2' '2' '2']
#  ['2' '2' '2']
#  ['2' '2' '2']]
``````

## 6. Return Array with dtype=float

If you want to create a NumPy array with a specified data type (`dtype`) of float, you can use the `dtype` parameter in the `numpy.full()` function.

In the below example, `np.full(shape=(3,4),fill_value='3',dtype=float)` creates a 2-D array with a shape of (3, 4), and all elements are filled with the float value `3`, and the data type is set explicitly to `float`. Adjust the `shape`, `fill_value`, and `dtype` parameters as needed for your specific use case.

``````
# Return array with dtype=str
arr2 = np.full(shape=(3,4),fill_value='3',dtype=float)
print("2-D Array with dtype=float:\n", arr2)

# Output:
# 2-D Array with dtype=float:
#  [[3. 3. 3. 3.]
#  [3. 3. 3. 3.]
#  [3. 3. 3. 3.]]
``````

What does the numpy.full() function do?

The `numpy.full()` function in NumPy is used to create an array with a specified shape and fill it with a constant value. Its primary purpose is to initialize an array where all elements have the same predetermined value.

Can I create a 1-D array using numpy.full()?

You can create a 1-D array using the `numpy.full()` function by specifying the shape parameter as a single integer.

How do I create a 2-D array with numpy.full()?

o create a 2-D array using `numpy.full()`, you need to specify the `shape` parameter as a tuple of two integers representing the number of rows and columns in the array.

How can I create an array with a specific data type?

To create an array with a specific data type using `numpy.full()`, you can use the `dtype` parameter. The `dtype` parameter allows you to explicitly specify the data type of the array.

How do I create a 2-D array with a specific order?

To create a 2-D array with a specific order (either row-major or column-major), you can use the `order` parameter in the `numpy.full()` function. The `order` parameter takes a string argument, where ‘C’ stands for row-major (default), and ‘F’ stands for column-major.

Can I create an array with a different fill value for each element?

The `numpy.full()` function fills the entire array with a constant value. If you need different values for each element, consider using other functions like `numpy.array()` or specifying a list of values manually.

## Conclusion

In this article, I have explained how to use `numpy.full()` function which returns an array of fill_value with the given shape, order, and datatype. By using this function, I have also explained how to fill values on 1-D and 2-D arrays and fill values with string & float types.

Happy Learning!!

## References

### Malli

Malli is an experienced technical writer with a passion for translating complex Python concepts into clear, concise, and user-friendly articles. Over the years, he has written hundreds of articles in Pandas, NumPy, Python, and takes pride in ability to bridge the gap between technical experts and end-users. 