reorder string python assignment

Sort a List, String, Tuple in Python (sort, sorted)

Basics of sorting in python.

In Python, sorting data structures like lists, strings, and tuples can be achieved using built-in functions like sort() and sorted() . These functions enable you to arrange the data in ascending or descending order. This section will provide an overview of how to use these functions.

The sorted() function is primarily used when you want to create a new sorted list from an iterable , without modifying the original data. This function can be used with a variety of data types, such as lists, strings, and tuples.

Here’s an example of sorting a list of integers :

To sort a string or tuple, you can simply pass it to the sorted() function as well:

For descending order sorting, use the reverse=True argument with the sorted() function:

On the other hand, the sort() method is used when you want to modify the original list in-place. One key point to note is that the sort() method can only be called on lists and not on strings or tuples.

To sort a list using the sort() method, simply call this method on the list object :

For descending order sorting using the sort() method, pass the reverse=True argument:

Using the sorted() function and the sort() method, you can easily sort various data structures in Python, such as lists, strings, and tuples, in ascending or descending order.

💡 Recommended : Python List sort() – The Ultimate Guide

Sorting Lists

In Python, sorting a list is a common operation that can be performed using either the sort() method or the sorted() function. Both these approaches can sort a list in ascending or descending order.

Using .sort() Method

The sort() method is a built-in method of the list object in Python. It sorts the elements of the list in-place, meaning it modifies the original list without creating a new one. By default, the sort() method sorts the list in ascending order.

Here’s an example of how to use the sort() method to sort a list of numbers:

To sort the list in descending order, you can pass the reverse=True argument to the sort() method:

Sorting Lists with sorted() Function

The sorted() function is another way of sorting a list in Python. Unlike the sort() method, the sorted() function returns a new sorted list without modifying the original one.

Here’s an example showing how to use the sorted() function:

Similar to the sort() method, you can sort a list in descending order using the reverse=True argument:

Both the sort() method and sorted() function allow for sorting lists as per specified sorting criteria. Use them as appropriate depending on whether you want to modify the original list or get a new sorted list.

Check out my video on the sorted() function: 👇

💡 Recommended : Python sorted() Function

Sorting Tuples

Tuples are immutable data structures in Python, similar to lists, but they are enclosed within parentheses and cannot be modified once created. Sorting tuples can be achieved using the built-in sorted() function.

Ascending and Descending Order

To sort a tuple or a list of tuples in ascending order , simply pass the tuple to the sorted() function.

Here’s an example:

For descending order , use the optional reverse argument in the sorted() function. Setting it to True will sort the elements in descending order:

Sorting Nested Tuples

When sorting a list of tuples, Python sorts them by the first elements in the tuples, then the second elements, and so on. To effectively sort nested tuples , you can provide a custom sorting key using the key argument in the sorted() function.

Here’s an example of sorting a list of tuples in ascending order by the second element in each tuple:

Alternatively, to sort in descending order, simply set the reverse argument to True :

As shown, you can manipulate the sorted() function through its arguments to sort tuples and lists of tuples with ease. Remember, tuples are immutable , and the sorted() function returns a new sorted list rather than modifying the original tuple.

Sorting Strings

In Python, sorting strings can be done using the sorted() function. This function is versatile and can be used to sort strings ( str ) in ascending ( alphabetical ) or descending ( reverse alphabetical ) order.

In this section, we’ll explore sorting individual characters in a string and sorting a list of words alphabetically .

Sorting Characters

To sort the characters of a string, you can pass the string to the sorted() function, which will return a list of characters in alphabetical order. Here’s an example:

If you want to obtain the sorted string instead of the list of characters, you can use the join() function to concatenate them:

For sorting the characters in descending order, set the optional reverse parameter to True :

Sorting Words Alphabetically

When you have a list of words and want to sort them alphabetically, the sorted() function can be applied directly to the list:

To sort the words in reverse alphabetical order, use the reverse parameter again:

Using Key Parameter

The key parameter in Python’s sort() and sorted() functions allows you to customize the sorting process by specifying a callable to be applied to each element of the list or iterable.

Sorting with Lambda

Using lambda functions as the key argument is a concise way to sort complex data structures. For example, if you have a list of tuples representing names and ages, you can sort by age using a lambda function:

Using itemgetter from operator Module

An alternative to using lambda functions is the itemgetter() function from the operator module. The itemgetter() function can be used as the key parameter to sort by a specific index in complex data structures:

Sorting with Custom Functions

You can also create custom functions to be used as the key parameter. For example, to sort strings based on the number of vowels:

Sorting Based on Absolute Value

To sort a list of integers based on their absolute values, you can use the built-in abs() function as the key parameter:

Sorting with cmp_to_key from functools

In some cases, you might need to sort based on a custom comparison function. The cmp_to_key() function from the functools module can be used to achieve this. For instance, you could create a custom comparison function to sort strings based on their lengths:

Sorting with Reverse Parameter

In Python, you can easily sort lists, strings, and tuples using the built-in functions sort() and sorted() . One notable feature of these functions is the reverse parameter, which allows you to control the sorting order – either in ascending or descending order.

By default, the sort() and sorted() functions will sort the elements in ascending order. To sort them in descending order, you simply need to set the reverse parameter to True . Let’s explore this with some examples.

Suppose you have a list of numbers and you want to sort it in descending order. You can use the sort() method for lists:

If you have a string or a tuple and want to sort in descending order, use the sorted() function:

Keep in mind that the sort() method works only on lists, while the sorted() function works on any iterable, returning a new sorted list without modifying the original iterable.

When it comes to sorting with custom rules, such as sorting a list of tuples based on a specific element, you can use the key parameter in combination with the reverse parameter. For example, to sort a list of tuples by the second element in descending order:

So the reverse parameter in Python’s sorting functions provides you with the flexibility to sort data in either ascending or descending order. By combining it with other parameters such as key , you can achieve powerful and customized sorting for a variety of data structures.

Sorting in Locale-Specific Order

Sorting lists, strings, and tuples in Python is a common task, and it often requires locale-awareness to account for language-specific rules. You can sort a list, string or tuple using the built-in sorted() function or the sort() method of a list. But to sort it in a locale-specific order, you must take into account the locale’s sorting rules and character encoding.

We can achieve locale-specific sorting using the locale module in Python. First, you need to import the locale library and set the locale using the setlocale() function, which takes two arguments, the category and the locale name.

Next, use the locale.strxfrm() function as the key for the sorted() function or the sort() method. The strxfrm() function transforms a string into a form suitable for locale-aware comparisons, allowing the sorting function to order the strings according to the locale’s rules.

The sorted_strings list will now be sorted according to the English (US) locale, with case-insensitive and accent-aware ordering.

Keep in mind that it’s essential to set the correct locale before sorting, as different locales may have different sorting rules. For example, the German locale would handle umlauts differently from English, so setting the locale to de_DE.UTF-8 would produce a different sorting order.

Sorting Sets

In Python, sets are unordered collections of unique elements. To sort a set, we must first convert it to a list or tuple, since the sorted() function does not work directly on sets. The sorted() function returns a new sorted list from the specified iterable, which can be a list, tuple, or set.

In this example, we begin with a set named sample_set containing four integers. We then use the sorted() function to obtain a sorted list named sorted_list_from_set . The output will be:

The sorted() function can also accept a reverse parameter, which determines whether to sort the output in ascending or descending order. By default, reverse is set to False , meaning that the output will be sorted in ascending order. To sort the set in descending order, we can set reverse=True .

This code snippet will output the following:

It’s essential to note that sorting a set using the sorted() function does not modify the original set. Instead, it returns a new sorted list, leaving the original set unaltered.

Sorting by Group and Nested Data Structures

Sorting nested data structures in Python can be achieved using the built-in sorted() function or the .sort() method. You can sort a list of lists or tuples based on the value of a particular element in the inner item, making it useful for organizing data in groups.

To sort nested data, you can use a key argument along with a lambda function or the itemgetter() method from the operator module. This allows you to specify the criteria based on which the list will be sorted.

For instance, suppose you have a list of tuples representing student records, where each tuple contains the student’s name and score:

To sort the list by the students’ scores, you can use the sorted() function with a lambda function as the key:

This will produce the following sorted list:

Alternatively, you can use the itemgetter() method:

This will produce the same result as using the lambda function.

When sorting lists containing nested data structures, consider the following tips:

• Use the lambda function or itemgetter() for specifying the sorting criteria.
• Remember that sorted() creates a new sorted list, while the .sort() method modifies the original list in-place.
• You can add the reverse=True argument if you want to sort the list in descending order.

Handling Sorting Errors

When working with sorting functions in Python, you might encounter some common errors such as TypeError . In this section, we’ll discuss how to handle such errors and provide solutions to avoid them while sorting lists, strings, and tuples using the sort() and sorted() functions.

TypeError can occur when you’re trying to sort a list that contains elements of different data types. For example, when sorting an unordered list that contains both integers and strings, Python would raise a TypeError: '<' not supported between instances of 'str' and 'int' as it cannot compare the two different data types.

Consider this example:

To handle the TypeError in this case, you can use error handling techniques such as a try-except block. Alternatively, you could also preprocess the list to ensure all elements have a compatible data type before sorting. Here’s an example using a try-except block:

Another approach is to sort the list using a custom sorting key in the sorted() function that can handle mixed data types. For instance, you can convert all the elements to strings before comparison:

With these techniques, you can efficiently handle sorting errors that arise due to different data types within a list, string, or tuple when using the sort() and sorted() functions in Python.

Sorting Algorithm Stability

Stability in sorting algorithms refers to the preservation of the relative order of items with equal keys. In other words, when two elements have the same key, their original order in the list should be maintained after sorting. Python offers several sorting techniques, with the most common being sort() for lists and sorted() for strings, lists, and tuples.

Python’s sorting algorithms are stable, which means that equal keys will have their initial order preserved in the sorted output. For example, consider a list of tuples containing student scores and their names:

Sorted by scores, the list should maintain the order of students with equal scores as in the original list:

Notice that Alice and Carla both have a score of 90 but since Alice appeared earlier in the original list, she comes before Carla in the sorted list as well.

To take full advantage of stability in sorting, the key parameter can be used with both sort() and sorted() . The key parameter allows you to specify a custom function or callable to be applied to each element for comparison. For instance, when sorting a list of strings, you can provide a custom function to perform a case-insensitive sort:

Frequently Asked Questions

How to sort a list of tuples in descending order in python.

To sort a list of tuples in descending order, you can use the sorted() function with the reverse=True parameter. For example, for a list of tuples tuples_list , you can sort them in descending order like this:

What is the best way to sort a string alphabetically in Python?

The best way to sort a string alphabetically in Python is to use the sorted() function, which returns a sorted list of characters. You can then join them using the join() method like this:

What are the differences between sort() and sorted() in Python?

sort() is a method available for lists, and it sorts the list in-place, meaning it modifies the original list. sorted() is a built-in function that works with any iterable, returns a new sorted list of elements, and doesn’t modify the original iterable.

How can you sort a tuple in descending order in Python?

To sort a tuple in descending order, you can use the sorted() function with the reverse=True parameter, like this:

Keep in mind that this will create a new list. If you want to create a new tuple instead, you can convert the sorted list back to a tuple like this:

How do you sort a string in Python without using the sort function?

You can sort a string without using the sort() function by converting the string to a list of characters, using a list comprehension to sort the characters, and then using the join() method to create the sorted string:

What is the method to sort a list of strings with numbers in Python?

If you have a list of strings containing numbers and want to sort them based on the numeric value, you can use the sorted() function with a custom key parameter. For example, to sort a list of strings like ["5", "2", "10", "1"] , you can do:

This will sort the list based on the integer values of the strings: ["1", "2", "5", "10"] .

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Python Sort List – How to Order By Descending or Ascending

In Python, you can sort data by using the sorted() method or sort() method.

In this article, I will provide code examples for the sorted() and sort() methods and explain the differences between the two.

What is the sort() method in Python?

This method takes a list and sorts it in place. This method does not have a return value.

In this example, we have a list of numbers and we can use the sort() method to sort the list in ascending order.

If the list is already sorted then it will return None in the console.

The sort() method can take in two optional arguments called key and reverse .

key  has the value of a function that will be called on each item in the list.

In this example, we can use the len() function as the value for the key argument. key=len will tell the computer to sort the list of names by length from smallest to largest.

reverse has a boolean value of True or False .

In this example, reverse=True will tell the computer to sort the list in reverse alphabetical order.

How to use the sorted() method in Python

This method will return a new sorted list from an iterable. Examples of iterables would be lists, strings, and tuples.

One key difference between sort() and sorted() is that sorted() will return a new list while sort() sorts the list in place.

In this example, we have a list of numbers that will be sorted in ascending order.

The sorted() method also takes in the optional key and reverse arguments.

In this example, we have a list of numbers sorted in descending order. reverse=True tells the computer to reverse the list from largest to smallest.

Another key difference between sorted() and sort() is that the sorted() method accepts any iterable whereas the sort() method only works with lists.

In this example, we have a string broken up into individual words using the split() method. Then we use sorted() to sort the words by length from smallest to largest.  

We can also modify this example and include the key and reverse arguments.

This modified example will now sort the list from largest to smallest.

We can also use the sorted() method on tuples .

In this example, we have a collection of tuples that represents the band student's name, age and instrument.

We can use the sorted() method to sort this data by the student's age. The key has the value of a lambda function which tells the computer to sort by age in ascending order.

A lambda function is an anonymous function without a name. You can define this type of function by using the lambda keyword.

To access a value in a tuple , you use bracket notation and the index number you want to access. Since we start counting at zero, the age value would be [1] .

Here is the complete example.

We can modify this example and sort the data by instrument instead. We can use reverse to sort the instruments through reverse alphabetical order.

In this article, we learned how to work with Python's sort() and sorted() methods.

The sort() method only works with lists and sorts the list in place. It does not have a return value.

The sorted() method works with any iterable and returns a new sorted list. Examples of iterables would be lists, strings, and tuples.

Both of these methods have two optional arguments of key and reverse .

key has the value of a function that will be called on each item in the list.

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Answer to Question #204679 in Python for Praveen

Rearrange Numbers in String

Given a string, write a program to re-arrange all the numbers appearing in the string in decreasing order. Note: There will not be any negative numbers or numbers with decimal part.

The input will be a single line containing a string.

The output should be a single line containing the modified string with all the numbers in string re-ordered in decreasing order.

Explanation

For example, if the given string is "I am 5 years and 11 months old", the numbers are 5, 11. Your code should print the sentence after re-ordering the numbers as "I am 11 years and 5 months old".

Sample Input

I am 5 years and 11 months old

Sample Output

I am 11 years and 5 months old

python4 anjali25

python25 anjali4

-1pyth-4on 5lear-3ning-2

5pyth4on 3lear2ning1

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• Reorder Pandas Columns: Pandas Reindex and Pandas insert
• February 17, 2021 December 28, 2022

In this post, you’ll learn the different ways to reorder Pandas columns, including how to use the .reindex() method to reorder Pandas columns.

Table of Contents

Loading a sample dataframe

Let’s start things off by loading a sample dataframe that you can use throughout the entire tutorial. We’ll only need to import Pandas for this tutorial:

This returns the following dataframe:

Reorder Columns by Direct Assignment

The most direct way to reorder columns is by direct assignment (pardon the pun!).

What this means is to place columns in the order that you’d like them to be in as a list, and pass that into square brackets when re-assigning your dataframe.

Right now, the dataframe’s columns are in the following order: [‘Name’, ‘Age’, ‘Gender’, ‘Education’, ‘City’].

Imagine that you want to switch out the Age and Gender columns, you could write:

This returns the following dataframe, with its columns reordered:

Check out some other Python tutorials on datagy, including our complete guide to styling Pandas and our comprehensive overview of Pivot Tables in Pandas !

Reorder Columns using Pandas .reindex()

Another way to reorder columns is to use the Pandas .reindex() method. This allows you to pass in the columns= parameter to pass in the order of columns that you want to use.

For the following example, let’s switch the Education and City columns:

Reorder Pandas Columns using Pandas .insert()

Both of the above methods rely on your to manually type in the list of columns. If you’re working with a larger dataframe, this can be time consuming and just, plain, annoying!

If you know the position in which you want to insert the column, this is a much easier way to do so.

Let’s check out how to do this using Python. For the following example, let’s move the City column between Name and Gender (as the second column).

Let’s take a quick look at what we’ve done here:

• We’ve assigned the df[‘City’] column to a series name city,
• We dropped that column from the dataframe, and finally
• We inserted that series back into the dataframe, at the first index with a column named ‘City’

Reorder Columns using a Custom Function

We can use the above method as a custom function, if you find yourself needing to move multiple columns around more frequently.

Let’s see how we do this with Python:

In this post, you learned how to reorder columns, including how to use the Pandas .reindex() method and the .insert() method. In the end, you learned a custom function to help you reorder columns, if this is something you do frequently.

If you want to learn more about the Pandas .reindex() method, check out the official documentation here .

Additional Resources

To learn more about related topics, check out the resources below:

• How to Add / Insert a Row into a Pandas DataFrame
• Insert a Blank Column to Pandas Dataframe
• Move a Pandas DataFrame Column to Position (Start and End)

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Python – Reorder for consecutive elements

Given a List perform reordering to get similar elements in consecution.

Input : test_list = [4, 7, 5, 4, 1, 4, 1, 6, 7, 5]  Output : [4, 4, 4, 7, 7, 5, 5, 1, 1, 6]  Explanation : All similar elements are assigned to be consecutive. Input : test_list = [4, 7, 5, 1, 4, 1, 6, 7, 5]  Output : [4, 4, 7, 7, 5, 5, 1, 1, 6]  Explanation : All similar elements are assigned to be consecutive. 

Method #1 : Using Counter() + loop + items()

In this, we perform the task of computing frequency using Counter(), and loop and items() are used to reorder elements according to count, and access frequencies respectively.

Time Complexity: O(n) Auxiliary Space: O(n)

Method #2 : Using Counter() + elements()

In this, we perform the task of reordering the counted frequencies using elements(), providing a concise solution.

Method #3: Using dictionary comprehension + sorted()

• Convert the list into a dictionary with keys as elements and values as their frequency using dictionary comprehension.
• Use sorted() function to sort the dictionary based on frequency in descending order.
• Create an empty list ‘res’ to store the reordered list.
• Iterate through the sorted dictionary and append each element to the ‘res’ list as many times as its frequency.
• Return the reordered list.

Time complexity: O(n log n), where n is the length of the list. This is because of the sorting operation performed on the dictionary. Auxiliary space: O(n), where n is the length of the list. This is because of the dictionary and list created to store the frequency and reordered list, respectively.

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