Python program to return rows that have element at a specified index

When it is required to return rows that have an element at a specified index, a simple iteration and the append() function can be used. This technique is useful for filtering rows based on matching elements at specific positions.

Basic Example

Below is a demonstration of comparing elements at a specific index ?

my_list_1 = [[21, 81, 35], [91, 14, 0], [64, 61, 42]]
my_list_2 = [[21, 92, 63], [80, 19, 65], [54, 65, 36]]

print("The first list is :")
print(my_list_1)
print("The second list is :")
print(my_list_2)

my_key = 0
my_result = []

for index in range(len(my_list_1)):
    if my_list_1[index][my_key] == my_list_2[index][my_key]:
        my_result.append(my_list_1[index])

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

The first list is :
[[21, 81, 35], [91, 14, 0], [64, 61, 42]]
The second list is :
[[21, 92, 63], [80, 19, 65], [54, 65, 36]]
The result is :
[[21, 81, 35]]

Using List Comprehension

A more concise approach using list comprehension ?

my_list_1 = [[21, 81, 35], [91, 14, 0], [64, 61, 42]]
my_list_2 = [[21, 92, 63], [80, 19, 65], [54, 65, 36]]

my_key = 0
my_result = [row for i, row in enumerate(my_list_1) 
             if row[my_key] == my_list_2[i][my_key]]

print("The result using list comprehension:")
print(my_result)

The result using list comprehension:
[[21, 81, 35]]

Finding Rows with Specific Element

Return rows that have a specific element at a given index ?

data = [[10, 20, 30], [40, 50, 60], [10, 80, 90], [70, 10, 100]]
target_element = 10
target_index = 0

matching_rows = []
for row in data:
    if row[target_index] == target_element:
        matching_rows.append(row)

print("Original data:")
print(data)
print(f"Rows with element {target_element} at index {target_index}:")
print(matching_rows)

Original data:
[[10, 20, 30], [40, 50, 60], [10, 80, 90], [70, 10, 100]]
Rows with element 10 at index 0:
[[10, 20, 30], [10, 80, 90]]

How It Works

• Two nested lists are defined and displayed on the console.

• A key (index value) is defined to specify which column to compare.

• An empty list is defined to store matching rows.

• The lists are iterated over, and if the elements at the specified index match, the row is appended to the result list.

• The filtered result is displayed on the console.

Conclusion

Use simple iteration with conditional checks to filter rows based on elements at specific indices. List comprehension provides a more concise alternative for the same functionality.