Python: Identify If a Variable Is an Array or a Scalar

Working with various types of data is an extremely common activity in Python. Often, you may need to distinguish between an array and a scalar and this is the primary requirement to efficiently handle numerical computations. There are libraries like NumPy, which give you various functions to check whether a variable is an array or a scalar.

In this blog, we are going to explore various methods using functions such as isinstance(), ndim, len(), and isscalar() by which you can determine if the variable is an array or a scalar in Python.

Table of Contents:

• Ways to Identify Arrays and Scalars in Python
  • Using isinstance() for Type Checking:
  • Using NumPy’s ndim Attribute
  • Using Numpy’s isscalar() Function
  • Checking len() for Non-NumPy Data
• Example of Identifying the Scalars and Arrays in NumPy
  • Handle the Mixed Data Types
• Conclusion

Ways to Identify Arrays and Scalars in Python

1. Using isinstance() for Type Checking:

The isinstance() function checks whether the variable you’re using is an instance of numpy.ndarray (array) or a standard scalar type. It is one of the easiest ways to check the variable type; it also works well with inheritance, making it better suited for more general data type checks.

import numpy as np

def check_yourData(variable):
    if isinstance(variable, np.ndarray):
        return "Array"
    elif isinstance(variable, (int, float, complex, str)):
        return "Scalar"
    else:
        return "Try Again"

print(check_yourData(np.array([1, 2, 3])))  
print(check_yourData(42))

Output:

Array

Scalar

2. Using NumPy’s ndim Attribute

When you are working with NumPy, ndim is an attribute that returns the dimensions of an array.  Scalars have zero dimensions (ndim == 0)

import numpy as np

arr = np.array([89, 20, 30])
scalar = np.array(50)

print(arr.ndim) 
print(scalar.ndim)

Output:

1 (Array)

0 (Scalar)

3. Using Numpy’s isscalar() Function

NumPy gives the np.isscalar() function for checking if a variable is a scalar.

import numpy as np

print(np.isscalar(10))  
print(np.isscalar(np.array([1, 2, 3])))

Output:

True

False

4. Checking len() for Non-NumPy Data

For the generic Python data structures like the lists and tuples, checking with the len() can help to distinguish between the array and scalars. Scalars will give an error when it is passed into len().

def is_scalar(variable):
    try:
        len(variable)
        return False  
    except TypeError:
        return True  
print(is_scalar(10))  
print(is_scalar([1, 2, 3]))

Output:

True

False

Examples of Identifying the Scalars and Arrays in NumPy

This example explains how to identify scalars and arrays in a NumPy-based dataset using np.isscalar() and isinstance() functions.

import numpy as np

data = [50, np.array(10), np.array([10, 20, 30])]

for variable in data:
    if np.isscalar(variable):
        print(f"{variable} is a Scalar")
    elif isinstance(item, np.ndarray):
        print(f"{variable} is an Array")

Output:

50 is a Scalar

10 is an Array

[10 20 30] is an Array

Handle the Mixed Data Types

When you are working with mixed data types, you can use isinstance() along with the np.isscalar():

import numpy as np

def check_data(variable):
    if np.isscalar(variable):
        return "Scalar"
    elif isinstance(variable, (list, tuple, np.ndarray)):
        return "Array"
    else:
        return "Try Again"

print(check_data(3.14))  # Output: Scalar
print(check_data(np.array([10, 20, 30])))  # Output: Array
print(check_data("Hello Intellipaat"))  # Output: Scalar

Output:

Scalar

Array

Scalar

Conclusion

Identifying if a variable is an array or a scalar is very crucial for writing powerful Python code. You can use built-in functions such as type(), isinstance(), and len(), and you can efficiently determine the type of a variable. These are the methods that help to stop when you are handling mixed data types in any Python code.