Python - Operation to each element in list

Given a list, there are often when performing a specific operation on each element is necessary. While using loops is a straightforward approach, Python provides several concise and efficient methods to achieve this. In this article, we will explore different operations for each element in the list. List comprehension is an efficient way to apply operations to each element in a list or to filter elements based on conditions.

Example:

a = [1, 2, 3, 4]

# Use list comprehension to add 5 to each element in the list
result = [x + 5 for x in a]
print(result)

[6, 7, 8, 9]

Let's see some other methods on how to perform operations to each element in list.

Using map()

map() function applies a function to every item in a list. We can pass a function (or a lambda) along with the list to map() and get the modified elements as a result.

a = [1, 2, 3, 4]

# square each element in the list
result = list(map(lambda x: x ** 2, a))
print(result)  

[1, 4, 9, 16]

Using a for Loop

The traditional for loop is useful for performing more complex or multi-step operations. This method allows greater flexibility when modifying list elements and appending results to a new list.

a = [1, 2, 3, 4]

# Initialize an empty list to store the results
result = []

# Iterate through each element in the list `a`
for x in a:
    result.append(x * 3)
print(result) 

[3, 6, 9, 12]

Using Numpy

NumPy is a powerful library optimized for numerical operations on lists and arrays. Here, bu using numpy we can convert the list to a numpy array, apply vectorized operations and achieve efficient performance.

Example:

import numpy as np

a = [10, 20, 30, 40]

# Convert the list to a NumPy array 
arr = np.array(a)

# Subtract 2 from each element of the NumPy array
result = arr - 2
print(result.tolist()) 

[8, 18, 28, 38]

Using pandas

pandas library is another efficient tool, particularly when dealing with data in table-like formats by converting the list to a pandas Series and directly apply operations on it.

Example:

import pandas as pd


a = [10, 20, 30, 40]

# Convert the list to a pandas Series 
#to perform element-wise operations
series = pd.Series(a)

# Divide each element of the Series by 2
result = series / 2
print(result.tolist())

[5.0, 10.0, 15.0, 20.0]