Sort the values of first list using second list in Python
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.
Using zip() and sorted()
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)
Output
['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 listb).- 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
Using numpy.argsort()
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)
Output
['b', 'd', 'a', 'c']
Explanation:
- np.argsort(b) =returns indices that would sort
b. - These indices are used to rearrange elements of list
a.
Using a Custom Sorting Function with sort()
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)
Output
['Learn', 'Python', 'with', 'GFG']
Explanation:
- The
sorted()function is used with a customkeyfunction. - The key is determined by finding the index of each element in '
a'and mapping it to the corresponding value in 'b'.
Using Pandas
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
aandbas columns. - The sort_values
()method sorts based on columnb. - The sorted
acolumn is converted back to a list.
