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How to Fix “TypeError: Series Objects Are Mutable” In Python

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TypeError: Series Objects Are Mutable

In Python, there is an error as TypeError: Series Objects Are Mutable that arises when you use mutable objects as a key for the dictionary. Mutable objects are those whose values can change and you do not have to reassign them to the same variable. let’s go and fix TypeError: Series Objects Are Mutable by using four easy method.

The hash value is a number that we get by using some operation on an object. As hashing,, an object means the object must have a constant and fixed particular value throughout the whole session.

As the mutable object changes its value at some point in the code.


How to Fix “TypeError: Series Objects Are Mutable” In Python?

Series objects in Python are mutable. This means that you can change the value of any element at any time, even while it’s being returned by calling next() on your Series object!

It causes a change in the hash value as well. It tells us that we cannot hash a list because the values in a loss can be changed.

While we can hash strings and integers as their value is fixed and does not change without reassigning it to a variable.

Here are some methods that can be used to fix this error in Python,

Method 1

We just have to implement __hash__protocol to create a list that can be hashed. This can be done by sub-classing the list and then implementing a hash protocol in it.

Here are some steps that you have to follow from collections import Iterable

class hashable_list(list):
	def __init__(self, *args):
		if len(args) == 1 and isinstance(args[0], Iterable):
			args = args[0].super().__init__(args)

	def __hash__(self):
		return hash(x for x in self)

This list can be used as a dictionary key.

Method 2

This method is used when the field value is unique like some ID number. In this method, we have to use the series object as one of its fields, not as a key.

We have a ser2 object having values of id field in the series, and now, we will check if it is possible to calculate the hash of the id field of ser2 or not. We will try to store the call sign of the agent in it.


Here we have obtained a hash value so it shows that we can create a dictionary with the field as a key.

dic1 = {ser2["id"] : "Lion"}

This method is the best way to keep the data of an agent’s call sign.

On the other hand, it is not easy to tell about the original object in a dictionary, and it does not store all data in it except the identifier.

Method 3:

You can convert the series of a mutable object into an immutable type such that in the form of a tuple. We will use a tuple to calculate the hash of ser2 by following these functions.

tup = tuple(ser2)

We can get the name of the agent also by using certain codes.


dic2 {tup: "Lion"}

namedtuple is a hashable and immutable dictionary and we will use it now. from collections import namedtuple

employer = namedtuple('employer', dic2)
em1 = employer(**dic2)
Employer(id=176450, name='William', job_title='agent',

  • Now, we will make another dictionary as dic3 in which you can refer to key fields by names.
for key in dic3:



Method 4

In this method, series will be used to create a class and then add hashing function to it. And if the hash changes, the object will stop working as a key.

class MySeries(pd.Series):
	def __hash__(self):
		return hash(tuple(self))
		myser = MySeries([176450, "William", "agent", 12000], index=["id", "name", "job_title", "salary"])
		dic = {myser: "Lion"}

{id 176450

name William
job_title agent
salary 12000
dtype: object: ‘Lion’}

Here, the dictionary key is an object of the new class MySeries but if you change the hash it will show no results and give Key Error.

Read more: How to Read Text File Line By Line Using Python

How to solve Series’ objects are mutable and cannot be hashed

Series objects are mutable and cannot be hashed because they are not stored in the database as hash values. Instead, they are stored as object references so that you can access them by name.

objects are mutable and cannot be hashed because they are not stored in the database as hash values. Instead, they are stored as object references so that you can access them by name.

When you create a series, Django creates a new Python list and inserts your object reference into the list. The list is then returned to you, and you can use it to access your object by name.

Since lists are mutable, you can change the contents of the list without affecting the underlying object reference.

Typeerror: series name must be a hashable type

When you get a TypeError that says “series name must be a hashable type”, it means that pandas can’t find an appropriate way to store your data in memory. This might happen if, for example, you try to use a Series or DataFrame as a key in a dictionary.

To fix this, you need to make sure that your series or data frame has a hashable type. A hashable type is something that can be turned into a number (usually by using the hash function). The most common hashable types are numbers, strings, and tuples. But there are also some more obscure ones like sets and frozen sets.


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