Python – Extract Particular data type rows

When working with lists of lists in Python, you may need to extract rows that contain only elements of a particular data type. This can be achieved using list comprehension combined with the isinstance() method and all() operator.

Syntax

result = [row for row in data if all(isinstance(element, data_type) for element in row)]

Example

Here's how to extract rows containing only integers from a mixed-type list ?

my_list = [[14, 35, "Will"], [12, 26, 17], ["p", "y", "t"], [29, 40, 21]]

print("The list is:")
print(my_list)

my_data_type = int

my_result = [row for row in my_list if all(isinstance(element, my_data_type) for element in row)]

print("The result is:")
print(my_result)

The list is:
[[14, 35, 'Will'], [12, 26, 17], ['p', 'y', 't'], [29, 40, 21]]
The result is:
[[12, 26, 17], [29, 40, 21]]

Extract String Rows

You can also extract rows containing only strings ?

mixed_data = [[1, 2, 3], ["apple", "banana"], [4.5, 6.7], ["cat", "dog", "bird"]]

string_rows = [row for row in mixed_data if all(isinstance(element, str) for element in row)]

print("String rows:")
print(string_rows)

String rows:
[['apple', 'banana'], ['cat', 'dog', 'bird']]

How It Works

• List comprehension iterates through each row in the main list

• isinstance(element, data_type) checks if each element matches the specified type

• all() ensures that every element in the row matches the data type

• Only rows where all elements match are included in the result

Multiple Data Types

You can also filter for multiple data types using a tuple ?

data = [[1, 2], ["a", "b"], [1.5, 2.5], [True, False]]

# Extract rows with only numbers (int or float)
numeric_rows = [row for row in data if all(isinstance(element, (int, float)) for element in row)]

print("Numeric rows:")
print(numeric_rows)

Numeric rows:
[[1, 2], [1.5, 2.5], [True, False]]

Conclusion

Use list comprehension with isinstance() and all() to filter rows by data type. This approach is efficient and readable for extracting specific data patterns from nested lists.