# How to Calculate minimum() of Array in NumPy?

Python NumPy `minimum()` function is used to compare the two arrays, element wise and returns the minimum values in a new array that contains element-wise minimum. While comparing, one of the elements of two arrays is a NaN, then that element is returned. If both elements of two arrays are NaNs then the first element is returned.

In this article, I will explain how to find the minimum value of Numpy arrays using `numpy.minimum(`) functions with examples.

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

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

``````
# Below are the quick examples
# Example :1 Get minimum value
arr = 34
arr1 = 65
arr2 = np.minimum(arr, arr1)

# Example 2: Get minimum value of 1-D arrays
arr = np.array([26,38,68,79])
arr1 = np.array([43,28,55,84])
arr2 = np.minimum(arr,arr1)

# Example 3: Use numpy.minimum() Function & NaN
arr = np.array([np.nan, 8, 17, np.nan, 48])
arr1 = np.array([np.nan, 24, np.nan, np.nan, 35])
arr2 = np.minimum(arr,arr1)

# Example 4: Get minimum value of two-D arrays
arr = np.array([[26,38,68,79],[34,47,np.nan,20]])
arr1 = np.array([[43,28,55,84],[np.nan,32,43,np.nan]])
arr2 = np.minimum(arr,arr1)
``````

## 2. Syntax of minimum()

Following is the syntax of the `numpy.minimum()` function.

``````
# Syntax of numpy.minimum()
numpy.minimum(arr1, arr2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, ufunc 'minimum')
``````

### 2.1 Parameters of minimum()

• `arr,arr1`– Input arrays
• `out` – ndarray, optional] A location in which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned.
• `where` – This condition is broadcast over the input, at locations where the condition is True, the out array will be set to the ufunc result.
• `**kwargs` – allows you to pass keyword variable length of argument to a function. It is used when we want to handle a named argument in a function.
• `where` – [array_like, optional]True value means to calculate the universal functions(ufunc) at that position, False value means to leave the value in the output alone.

### 2.2 Return Value of minimum()

It returns the minimum of arr1 and arr2 arrays, element-wise. This returns a scalar if both arr1 and arr2 are scalars.

## 3. Usage of Numpy minimum()

`minimum()` function is used to get a new array that contains element-wise minimum values of two arrays. It compares two arrays and returns a new array containing the minimum values. If one of the elements being compared is `NaN` (Not a Number), `NaN` is returned. If both elements being compared are `NaN` (Not a Number), then `NAN` is returned.

### 3.1 Get Minimum Value of Two Scalars

If we use `numpy.minimum()` function to compare two scalar values, it will return the minimum scalar value of two scalars. For example,

``````
import numpy as np
arr = 34
arr1 = 65
# Get minimum value
arr2 = np.minimum(arr, arr1)
print (arr2)

# Output :
# 34
``````

### 3.2 Get Minimum Values of 1-D Array

The following example demonstrates how to get the minimum values of 1-D NumPy arrays using `minimum()`. Let’s create 1-D arrays using numpy.array() and pass these two arrays as input to the minimum() function. For example,

``````
import numpy as np
# Create 1-D arrays
arr = np.array([26,38,68,79])
arr1 = np.array([43,28,55,84])

# Get minimum value of 1-D arrays
arr2 = np.minimum(arr,arr1)
print(arr2)

# Output :
# [26 28 55 79]
``````

## 4. Using NaN in NumPy Arrays

If there is a NaN in the given NumPy array then `minimum()` will return NaN as the minimum value. If both elements of two arrays are NaNs then it returns the first element.

``````
arr = np.array([np.nan, 8, 17, np.nan, 48])
arr1 = np.array([np.nan, 24, np.nan, np.nan, 35])

# Use numpy.minimum() Function & NaN
arr2 = np.minimum(arr,arr1)
print(arr2)

# Output:
# [nan  8. nan nan 35.]
``````

## 5. Get Minimum Value of 2-D Arrays

Finally, let’s get the minimum values element-wise by comparing two 2-D NumPy arrays.

``````
# Create 2-D arrays
arr = np.array([[26,38,68,79],[34,47,np.nan,20]])
arr1 = np.array([[43,28,55,84],[np.nan,32,43,np.nan]])
# Get minimum value of two-D arrays
arr2 = np.minimum(arr,arr1)
print(arr2)

# Output :
# [[26. 28. 55. 79.]
# [nan 32. nan nan]]
``````

## 6. Conclusion

In this article, I have explained how to get the minimum values of Numpy arrays using `minimum()` function with examples. While comparing, one of the elements of two arrays is a NaN, then that element is returned. If both elements of two arrays are NaNs then the first element is returned.

Happy Learning!!

## References 