In this Python article, we will take a deep dive into the Python List reverse() method – a powerful and handy technique for reversing the elements of a Python list in place.
We will cover its syntax, usage, and explore some examples to better understand its practical applications.
List reverse() method in Python
Below are the topics that we are doing to discuss in this article:
- Introduction to Python List reverse() method
- Syntax of the reverse() method
- Purpose and use cases of the reverse() method
Python List reverse() method
The reverse() method is a built-in Python method for lists, which is used to reverse the order of elements in a list object. This in-place reversal method modifies the original Python list and does not create a new one, making it memory-efficient.
It is essential to note that this method works only with Python list objects and cannot be used with other iterables such as strings or tuples.
The syntax of the list reverse() method is as follows:
Here, ‘list’ is the Python list object that we want to reverse. The method does not take any arguments, and it does not return any value, as it reverses the list in place.
reverse() method in Python List Examples
Let’s explore some examples to understand how the Python list reverse() method works.
Example#1 Reversing a list of integers
population = [327, 328, 329, 330, 331] population.reverse() print(population)
This example demonstrates a Python list of integers representing the US population in millions from 2018 to 2022. The list is reversed, which displays the population from the most recent year to the oldest.
Example#2 Reversing a list of strings
states = ["California", "Texas", "Florida", "New York"] states.reverse() print(states)
In this example, a Python list of strings representing some of the most populous states in the US is reversed. After applying the reverse() method, the list displays the states in the opposite order.
Example#3 Reversing a list of mixed data types
us_data = [331, "United States", 9.834, True] us_data.reverse() print(us_data)
Here, a Python list of mixed data types representing US data is reversed. The list contains the population in millions (331), the country name (“United States”), the land area in million square kilometers (9.834), and a boolean value indicating whether it’s a member of the G7 (True).
reverse() method is applied to the
us_data list, which reverses the order of the elements in the list.
Example#4 Reversing a list of elements for algorithms that require processing data in reverse order
avg_temps = [32, 35, 45, 55, 65, 75, 80, 78, 70, 58, 48, 38] avg_temps.reverse() print(avg_temps)
In this case, we reverse a Python list of average monthly temperatures in Fahrenheit for a US city to process or analyze them in reverse chronological order, i.e., starting from the most recent month and going back in time.
Example#5 Sorting a list in descending order by first sorting it in ascending order and then reversing it
city_population = [("New York", 8550405), ("Los Angeles", 3971883), ("Chicago", 2720546), ("Houston", 2296224), ("Phoenix", 1660272)] city_population.sort(key=lambda x: x) city_population.reverse() print(city_population)
We first sort a Python list of tuples containing US city names and their populations in ascending order by population. Then, we reverse the sorted Python list to display the cities in descending order of population, i.e., from the most populous city to the least.
Example#6 Reversing the elements of a list as a part of data preprocessing
stock_prices = [120.45, 121.32, 123.67, 125.21, 124.78, 123.45, 122.89] stock_prices.reverse() print(stock_prices)
We reverse a Python list of daily closing stock prices for a US company to analyze them in reverse chronological order. This could be useful for various financial analysis tasks, such as identifying trends or patterns in recent stock prices.
Python list reverse() method is a powerful and convenient tool for reversing the order of elements in a list. Its in-place reversal approach saves memory, and its simplicity makes it easy to implement in various scenarios.
You may also like to read the following articles:
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- How to create a list of dictionary keys in python
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