## Problem Formulation: Replacing One Element

Given

- List
`lst`

- Element
`x`

- Index
`i`

How to replace the element at index `i`

in the list `lst`

with the new element `x`

?

## Solution Indexing

You use simple indexing using the square bracket notation `lst[i] = x`

to replace the element at index `i`

in list `lst`

with the new element `x`

.

>>> lst = ['Alice', 'Bob', 'Carl', 'Dave'] >>> x = 'Chris' >>> i = 2 >>> lst[i] = x >>> lst ['Alice', 'Bob', 'Chris', 'Dave']

But what if you want to replace multiple elements at multiple indices?

## Problem Formulation: Replacing Multiple Elements

Given

- List
`lst`

- Elements
`[x_0, x_1, ..., x_n]`

- Indices
`[i_0, i_1, ..., i_n]`

How to replace the elements at indices `i_0, i_1, ..., i_n`

in the list `lst`

with the new elements

in that order?`x_0, x_1, ..., x_n`

## Method 1: For Loop

You can use the `range()`

function to get the pair of the i-th index and the i-th replacement value in a for loop. Then, you replace all elements one-by-one.

lst = ['Alice', 'Bob', 'Carl', 'Dave', 'Elena', 'Frank', 'George'] repl = ['None', 'Foo', 'Bar'] indices = [0, 2, 5] # Method 1: For Loop for i in range(len(indices)): lst[indices[i]] = repl[i] print(lst) # ['None', 'Bob', 'Foo', 'Dave', 'Elena', 'Bar', 'George']

## Method 2: zip() and For Loop

A more Pythonic approach is to zip together the indices and replacement values and then simply iterating over them in pairs using multiple assignments.

lst = ['Alice', 'Bob', 'Carl', 'Dave', 'Elena', 'Frank', 'George'] repl = ['None', 'Foo', 'Bar'] indices = [0, 2, 5] # Method 2: zip() and for loop for index, replacement in zip(indices, repl): lst[index] = replacement print(lst) # ['None' 'Bob' 'Foo' 'Dave' 'Elena' 'Bar' 'George']

## Method 3: NumPy + Slice Assignment

Stand on the shoulders of giants! You can use NumPy’s powerful advanced indexing functionality to pass the list of indices to be replaced in the indexing scheme—and replacing those with all elements on the right of an assignment operation.

lst = ['Alice', 'Bob', 'Carl', 'Dave', 'Elena', 'Frank', 'George'] repl = ['None', 'Foo', 'Bar'] indices = [0, 2, 5] # Method 3: NumPy + Slice Assignment import numpy as np lst = np.array(lst) lst[indices] = repl print(lst) # ['None' 'Bob' 'Foo' 'Dave' 'Elena' 'Bar' 'George']

## Method 4: Python One-Liner Solution

I love Python one-liners (that’s why I’ve written a book about them). Can we solve the multiple replacement problem in a single line? Yeah, sure!

lst = ['Alice', 'Bob', 'Carl', 'Dave', 'Elena', 'Frank', 'George'] repl = ['None', 'Foo', 'Bar'] indices = [0, 2, 5] # Method 4: Python One-Liner lst = [repl[indices.index(i)] if i in indices else lst[i] for i in range(len(lst))] print(lst) # ['None' 'Bob' 'Foo' 'Dave' 'Elena' 'Bar' 'George']

- We use list comprehension
`[... for i in ...]`

to iterate over all indices from 0 to the length of the list. - We use the ternary operator
`... if ... else ...`

to check whether this index is one that must be replaced. - If the index doesn’t have to be replaced, return the original element, otherwise return the replacement element.
- We use the
`list.index()`

method to figure out the index of the element to replace the original list element.

Not very pretty, isn’t it? If you still want to learn how one-liners work, check out my book:

## Python One-Liners Book: Master the Single Line First!

**Python programmers will improve their computer science skills with these useful one-liners.**

*Python One-Liners* will teach you how to read and write “one-liners”: ** concise statements of useful functionality packed into a single line of code. **You’ll learn how to systematically unpack and understand any line of Python code, and write eloquent, powerfully compressed Python like an expert.

The book’s five chapters cover (1) tips and tricks, (2) regular expressions, (3) machine learning, (4) core data science topics, and (5) useful algorithms.

Detailed explanations of one-liners introduce ** key computer science concepts **and

**. You’ll learn about advanced Python features such as**

*boost your coding and analytical skills**,*

**list comprehension****,**

*slicing***,**

*lambda functions***,**

*regular expressions***and**

*map***functions, and**

*reduce***.**

*slice assignments*You’ll also learn how to:

- Leverage data structures to
**solve real-world problems**, like using Boolean indexing to find cities with above-average pollution - Use
**NumPy basics**such as*array*,*shape*,*axis*,*type*,*broadcasting*,*advanced indexing*,*slicing*,*sorting*,*searching*,*aggregating*, and*statistics* - Calculate basic
**statistics**of multidimensional data arrays and the K-Means algorithms for unsupervised learning - Create more
**advanced regular expressions**using*grouping*and*named groups*,*negative lookaheads*,*escaped characters*,*whitespaces, character sets*(and*negative characters sets*), and*greedy/nongreedy operators* - Understand a wide range of
**computer science topics**, including*anagrams*,*palindromes*,*supersets*,*permutations*,*factorials*,*prime numbers*,*Fibonacci*numbers,*obfuscation*,*searching*, and*algorithmic sorting*

By the end of the book, you’ll know how to ** write Python at its most refined**, and create concise, beautiful pieces of “Python art” in merely a single line.

*Get your Python One-Liners on Amazon!!*

While working as a researcher in distributed systems, Dr. Christian Mayer found his love for teaching computer science students.

To help students reach higher levels of Python success, he founded the programming education website Finxter.com. He’s author of the popular programming book Python One-Liners (NoStarch 2020), coauthor of the Coffee Break Python series of self-published books, computer science enthusiast, freelancer, and owner of one of the top 10 largest Python blogs worldwide.

His passions are writing, reading, and coding. But his greatest passion is to serve aspiring coders through Finxter and help them to boost their skills. You can join his free email academy here.