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Sort the values of first list using second list in Python

Last Updated : 24 Dec, 2024

Sorting the values of the first list using the second list in Python is commonly needed in applications involving data alignment or dependency sorting. In this article, we will explore different methods to Sort the values of the first list using the second list in Python.

zip() function pairs elements from two lists and sorted() allows us to sort these pairs based on the second list.

a = ['a', 'b', 'c', 'd']
b = [3, 1, 4, 2]

# Sort a using b
x = [val for _, val in sorted(zip(b, a))]

print(x)

['b', 'd', 'a', 'c']

Explanation:

• zip(b, a) pairs the elements of the second list (b) with the first list (a).
• sorted() sorts these pairs based on the first element (from list b).
• A list comprehension extracts the sorted elements from list a.

Let's see some more methods and see how we can sort the values of one list using another list in Python

If working with numerical lists, numpy.argsort() provides a fast way to obtain indices for sorting.

import numpy as np

a = ['a', 'b', 'c', 'd']
b = [3, 1, 4, 2]

# Sort list_a using numpy.argsort()
sorted_a = [a[i] for i in np.argsort(b)]

print(sorted_a)

['b', 'd', 'a', 'c']

Explanation:

• np.argsort(b) =returns indices that would sort b.
• These indices are used to rearrange elements of list a.

For a more manual approach, we can use a custom sorting function with sorted(). This method involves sorting list by using a custom sorting function.

a = ['with', 'GFG', 'Learn', 'Python']
b = [3, 4, 1, 2]

# Using sort() with a custom sorting function
list1_sorted = sorted(a, key=lambda x: b[a.index(x)])
print(list1_sorted)

['Learn', 'Python', 'with', 'GFG']

Explanation:

• The sorted() function is used with a custom key function.
• The key is determined by finding the index of each element in 'a' and mapping it to the corresponding value in 'b'.

For tabular data or scenarios involving data frames, pandas provides a convenient way to sort one column based on another.

import pandas as pd

a = ['a', 'b', 'c', 'd']
b = [3, 1, 4, 2]

# Create a DataFrame
df = pd.DataFrame({'a': a, 'b': b})

# Sort by column 'b' and extract 'a'
sorted_a = df.sort_values('b')['a'].tolist()

print(sorted_a)

Output:

['b', 'd', 'a', 'c']

Explanation:

• A data frame is created with a and b as columns.
• The sort_values() method sorts based on column b.
• The sorted a column is converted back to a list.

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