How to Fix AttributeError: can only use .str accessor with string values

The AttributeError: can only use str accessor with string values error occurs in Python when are trying to use a string accessor on a value that is not a string. String accessors are methods specific to string objects and can only be used on values that are strings.

import pandas as pd

df = pd.DataFrame({'data': [11, 21, 19]})

df.data.str.replace('x', 'y')

print(df)

Output

AttributeError: Can only use .str accessor with string values!

In this code, we got the AttributeError because the `data` column has integer values, not string values.

Python .str accessor is used to access individual characters in a string. The accessor allows you to index into a string using square brackets. For example, string[0].

The .str accessor only works on string values. If you use it on an object that is not a string, you will get an AttributeError.

How to Fix AttributeError: can only use .str accessor with string values

1. To fix the AttributeError: can only use .str accessor with string values error in Python, ensure that you are only using the .str accessor on string values. 
2. Use the type() function to check the data type of objects.
3. Ensure that you use the + operator to concatenate strings, not the , operator.
4. Make sure that you use the correct type of quotes around your strings.
5. Use the isinstance() function to check if an object is an instance of a specific data type.

Method 1: Using the type() function

The type() is a built-in Python function that returns the data type of an input object.

import pandas as pd

df = pd.DataFrame({'data': [11, 21, 19]})

print(type(df.data[0]))

Output

<class 'numpy.int64'>

You can see that the value’s data type is `numpy.int64`. Now, if you try to apply a string function on integer values, it will throw the error.

Method 2: Using instance() function

The isinstance() method checks if an object is an instance of a particular type.

import pandas as pd
import numpy as np

df = pd.DataFrame({'data': [11, 21, 19]})

print(isinstance(df.data[0], np.int64))

Output

True

You can see that the data type of value is np.int64, and that’s why the isinstance() function returns True because it’s an integer data type and not a string data type.

Conclusion

Avoid accessing a string method or attribute on a non-string object; otherwise, you might get this type of AttributeError.

Use the type() or isinstance() method to verify the object’s data type at any time.

That’s it.