typeerror column assignment doesn't support type range

Dask “Column assignment doesn’t support type numpy.ndarray”

I’m trying to use Dask instead of pandas since the data size I’m analyzing is quite large. I wanted to add a flag column based on several conditions.

But, then I got the following error message. The above code works perfectly when using np.where with pandas dataframe, but didn’t work with dask.array.where .

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If numpy works and the operation is row-wise, then one solution is to use .map_partitions :

pyspark.pandas.DataFrame.assign ¶

Assign new columns to a DataFrame.

Returns a new object with all original columns in addition to new ones. Existing columns that are re-assigned will be overwritten.

The column names are keywords. If the values are callable, they are computed on the DataFrame and assigned to the new columns. The callable must not change input DataFrame (though pandas-on-Spark doesn’t check it). If the values are not callable, (e.g. a Series or a literal), they are simply assigned.

A new DataFrame with the new columns in addition to all the existing columns.

Assigning multiple columns within the same assign is possible but you cannot refer to newly created or modified columns. This feature is supported in pandas for Python 3.6 and later but not in pandas-on-Spark. In pandas-on-Spark, all items are computed first, and then assigned.

Where the value is a callable, evaluated on df :

Alternatively, the same behavior can be achieved by directly referencing an existing Series or sequence and you can also create multiple columns within the same assign.

pyspark.pandas.DataFrame.append

pyspark.pandas.DataFrame.merge

How to Solve Python TypeError: ‘tuple’ object does not support item assignment

by Suf | Programming , Python , Tips

Tuples are immutable objects, which means you cannot change them once created. If you try to change a tuple in place using the indexing operator [], you will raise the TypeError: ‘tuple’ object does not support item assignment.

To solve this error, you can convert the tuple to a list, perform an index assignment then convert the list back to a tuple.

This tutorial will go through how to solve this error and solve it with the help of code examples.

Table of contents

Typeerror: ‘tuple’ object does not support item assignment.

Let’s break up the error message to understand what the error means. TypeError occurs whenever you attempt to use an illegal operation for a specific data type.

The part 'tuple' object tells us that the error concerns an illegal operation for tuples.

The part does not support item assignment tells us that item assignment is the illegal operation we are attempting.

Tuples are immutable objects, which means we cannot change them once created. We have to convert the tuple to a list, a mutable data type suitable for item assignment.

Let’s look at an example of assigning items to a list. We will iterate over a list and check if each item is even. If the number is even, we will assign the square of that number in place at that index position.

Let’s run the code to see the result:

We can successfully do item assignments on a list.

Let’s see what happens when we try to change a tuple using item assignment:

We throw the TypeError because the tuple object is immutable.

To solve this error, we need to convert the tuple to a list then perform the item assignment. We will then convert the list back to a tuple. However, you can leave the object as a list if you do not need a tuple.

Let’s run the code to see the updated tuple:

Congratulations on reading to the end of this tutorial. The TypeError: ‘tuple’ object does not support item assignment occurs when you try to change a tuple in-place using the indexing operator [] . You cannot modify a tuple once you create it. To solve this error, you need to convert the tuple to a list, update it, then convert it back to a tuple.

For further reading on TypeErrors, go to the article:

• How to Solve Python TypeError: ‘str’ object does not support item assignment

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TypeError: 'tuple' object does not support item assignment

Last updated: Apr 8, 2024 Reading time · 4 min

# TypeError: 'tuple' object does not support item assignment

The Python "TypeError: 'tuple' object does not support item assignment" occurs when we try to change the value of an item in a tuple.

To solve the error, convert the tuple to a list, change the item at the specific index and convert the list back to a tuple.

Here is an example of how the error occurs.

We tried to update an element in a tuple, but tuple objects are immutable which caused the error.

# Convert the tuple to a list to solve the error

We cannot assign a value to an individual item of a tuple.

Instead, we have to convert the tuple to a list.

This is a three-step process:

• Use the list() class to convert the tuple to a list.
• Update the item at the specified index.
• Use the tuple() class to convert the list back to a tuple.

Once we have a list, we can update the item at the specified index and optionally convert the result back to a tuple.

Python indexes are zero-based, so the first item in a tuple has an index of 0 , and the last item has an index of -1 or len(my_tuple) - 1 .

# Constructing a new tuple with the updated element

Alternatively, you can construct a new tuple that contains the updated element at the specified index.

The get_updated_tuple function takes a tuple, an index and a new value and returns a new tuple with the updated value at the specified index.

The original tuple remains unchanged because tuples are immutable.

We updated the tuple element at index 1 , setting it to Z .

If you only have to do this once, you don't have to define a function.

The code sample achieves the same result without using a reusable function.

The values on the left and right-hand sides of the addition (+) operator have to all be tuples.

The syntax for tuple slicing is my_tuple[start:stop:step] .

The start index is inclusive and the stop index is exclusive (up to, but not including).

If the start index is omitted, it is considered to be 0 , if the stop index is omitted, the slice goes to the end of the tuple.

# Using a list instead of a tuple

Alternatively, you can declare a list from the beginning by wrapping the elements in square brackets (not parentheses).

Declaring a list from the beginning is much more efficient if you have to change the values in the collection often.

Tuples are intended to store values that never change.

# How tuples are constructed in Python

In case you declared a tuple by mistake, tuples are constructed in multiple ways:

• Using a pair of parentheses () creates an empty tuple
• Using a trailing comma - a, or (a,)
• Separating items with commas - a, b or (a, b)
• Using the tuple() constructor

# Checking if the value is a tuple

You can also handle the error by checking if the value is a tuple before the assignment.

If the variable stores a tuple, we set it to a list to be able to update the value at the specified index.

The isinstance() function returns True if the passed-in object is an instance or a subclass of the passed-in class.

If you aren't sure what type a variable stores, use the built-in type() class.

The type class returns the type of an object.

# Additional Resources

You can learn more about the related topics by checking out the following tutorials:

• How to convert a Tuple to an Integer in Python
• How to convert a Tuple to JSON in Python
• Find Min and Max values in Tuple or List of Tuples in Python
• Get the Nth element of a Tuple or List of Tuples in Python
• Creating a Tuple or a Set from user Input in Python
• How to Iterate through a List of Tuples in Python
• Write a List of Tuples to a File in Python
• AttributeError: 'tuple' object has no attribute X in Python
• TypeError: 'tuple' object is not callable in Python [Fixed]

Borislav Hadzhiev

Web Developer

Copyright © 2024 Borislav Hadzhiev

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Python typeerror: ‘tuple’ object does not support item assignment Solution

Tuples are immutable objects . “Immutable” means you cannot change the values inside a tuple. You can only remove them. If you try to assign a new value to an item in a variable, you’ll encounter the “typeerror: ‘tuple’ object does not support item assignment” error.

In this guide, we discuss what this error means and why you may experience it. We’ll walk through an example of this error so you can learn how to solve it in your code.

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Typeerror: ‘tuple’ object does not support item assignment.

While tuples and lists both store sequences of data, they have a few distinctions. Whereas you can change the values in a list, the values inside a tuple cannot be changed. Also, tuples are stored within parenthesis whereas lists are declared between square brackets.

Because you cannot change values in a tuple, item assignment does not work.

Consider the following code snippet:

This code snippet lets us change the first value in the “honor_roll” list to Holly. This works because lists are mutable. You can change their values. The same code does not work with data that is stored in a tuple.

An Example Scenario

Let’s build a program that tracks the courses offered by a high school. Students in their senior year are allowed to choose from a class but a few classes are being replaced.

Start by creating a collection of class names:

We’ve created a tuple that stores the names of each class being offered.

The science department has notified the school that psychology is no longer being offered due to a lack of numbers in the class. We’re going to replace psychology with philosophy as the philosophy class has just opened up a few spaces.

To do this, we use the assignment operator:

This code will replace the value at the index position 3 in our list of classes with “Philosophy”. Next, we print our list of classes to the console so that the user can see what classes are being actively offered:

Use a for loop to print out each class in our tuple to the console. Let’s run our code and see what happens:

Our code returns an error.

The Solution

We’ve tried to use the assignment operator to change a subject in our list. Tuples are immutable so we cannot change their values. This is why our code returns an error.

To solve this problem, we convert our “classes” tuple into a list . This will let us change the values in our sequence of class names.

Do this using the list() method:

We use the list() method to convert the value of “classes” to a list. We assign this new list to the variable “as_list”. Now that we have our list of classes stored as a list, we can change existing classes in the list.

Let’s run our code:

Our code successfully changes the “Psychology” class to “Philosophy”. Our code then prints out the list of classes to the console.

If we need to store our data as a tuple, we can always convert our list back to a tuple once we have changed the values we want to change. We can do this using the tuple() method:

This code converts “as_list” to a tuple and prints the value of our tuple to the console:

We could use this tuple later in our code if we needed our class names stored as a tuple.

The “typeerror: ‘tuple’ object does not support item assignment” error is raised when you try to change a value in a tuple using item assignment.

To solve this error, convert a tuple to a list before you change the values in a sequence. Optionally, you can then convert the list back to a tuple.

Now you’re ready to fix this error in your code like a pro !

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Assign alters dtypes of dataframe columns it should not #3907

Azorico commented Aug 27, 2018

• 👍 1 reaction

TomAugspurger commented Aug 27, 2018

For pandas Series, that ends up doing self._meta.assign(col=series) , which forces a reindex , which converts the int columns to float.

We should ensure that for pandas series, we pass through series.iloc[:0] , an empty series, rather than the entire series. We can either update _extract_meta to ensure we do that, or make an _extract_meta_empty if changing _extract_meta breaks too many things. Does that make sense?

Sorry, something went wrong.

Azorico commented Aug 29, 2018 • edited

mrocklin commented Oct 5, 2018

Mrocklin commented oct 6, 2018 via email.

jhb9 commented Oct 6, 2018

asmith26 commented Jul 1, 2019 • edited

jrbourbeau commented Jul 2, 2019

asmith26 commented Jul 2, 2019

Successfully merging a pull request may close this issue.

Pandas TypeError: SparseArray does not support item assignment via setitem

Understanding the error.

Encountering a TypeError: SparseArray does not support item assignment via setitem in Pandas can be a hurdle, especially for those dealing with sparse data structures to optimize memory usage. The error typically occurs when you try to assign a value to a specific position in a SparseArray directly. This guide will explore reasons behind this error and provide solutions to circumvent or resolve it efficiently.

More about Sparse Data Structures

Sparse data structures in Pandas, such as SparseArray , are designed for memory efficiency when handling data that contains a significant amount of missing or fill values. However, these data structures have certain limitations, including restrictions on direct item assignment, which is the primary cause of the error in question.

Solution 1: Convert to Dense and Assign

One straightforward method to overcome this error is converting your SparseArray to a dense format, performing the item assignment, and then, if necessary, converting it back to sparse format.

• Step 1: Convert the SparseArray to a dense array.
• Step 2: Perform the item assignment on the dense array.
• Step 3: Convert the dense array back to a SparseArray if needed.

Notes: While this solution is straightforward, converting to dense and back to sparse can be memory-intensive, especially for very large datasets. This should be considered when dealing with limited system resources.

Solution 2: Use Sparse Accessor for Direct Assignment

Another solution involves utilizing the sparse accessor .sparse provided by Pandas for directly assigning values without converting to a dense format. This method supports updating the entire array or slices but not individual item assignments. What you need to do is just using the .sparse accessor to directly assign values to the SparseArray.

Notes: It’s important to note that while this solution avoids the need for conversion, it has limitations on granularity. You can’t use it for assigning a value to a specific index but rather for assigning values to slices or the entire array.

Final Thoughts

Handling SparseArray item assignment errors in Pandas can be tricky but understanding the limitations and workarounds makes it manageable. Both converting to dense before assignment and using the .sparse accessor come with their own sets of considerations. Evaluate your specific needs and system resources to choose the best approach.

Next Article: Pandas UnicodeDecodeError: 'utf-8' codec can't decode

Previous Article: Fixing Pandas NameError: name ‘df’ is not defined

Series: Solving Common Errors in Pandas

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