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

The AttributeError: Can only use .str accessor with string values, which use np.object_ dtype in pandas occurs if you try to replace the values of string column, but in reality, it is of a different type.

In this tutorial, we will look at what is AttributeError: Can only use .str accessor with string values and how to fix this error with examples.

AttributeError: Can only use .str accessor with string values, which use np.object_ dtype in pandas

Let us take a simple example to reproduce this error. In the below example, we have Pandas DataFrame, which indicates the standing of each cricket team.

# import pandas library
import pandas as pd

# create pandas DataFrame
df = pd.DataFrame({'team': ['India', 'South Africa', 'New Zealand', 'England'],
                   'points': [12.0, 8.0, 3.0, 5],
                   'runrate': [0.5, 1.4, 2, -0.6],
                   'wins': [5, 4, 2, 2]})
print(df['points'])
df['points'] = df['points'].str.replace('.', '')
print(df['points'])

Output

0    12.0
1     8.0
2     3.0
3     5.0
Name: points, dtype: float64    
raise AttributeError("Can only use .str accessor with string values!")
AttributeError: Can only use .str accessor with string values!. Did you mean: 'std'?

When we run the above code, we get AttributeError Can only use .str accessor with string values!.

The points column is in the float datatype, and using the str.replace() can be applied only on the string columns. 

How to fix Can only use .str accessor with string values error?

We can fix the error by casting the DataFrame column “points” from float to string before replacing the values in the column.

Let us fix our code and run it once again.

# import pandas library
import pandas as pd

# create pandas DataFrame
df = pd.DataFrame({'team': ['India', 'South Africa', 'New Zealand', 'England'],
                   'points': [12.0, 8.0, 3.0, 5],
                   'runrate': [0.5, 1.4, 2, -0.6],
                   'wins': [5, 4, 2, 2]})
print(df['points'])
df['points'] = df['points'].astype(str).str.replace('.', '')
print(df['points'])

Output

0    12.0
1     8.0
2     3.0
3     5.0
Name: points, dtype: float64

0    120
1     80
2     30
3     50
Name: points, dtype: object

Notice that the error is gone, and the points column is converted from float to object, and also, the decimal has been replaced with an empty string.

Conclusion

The AttributeError: Can only use .str accessor with string values, which use np.object_ dtype in pandas occurs if you try to replace the values of string column, but in reality, it is of a different type.

We can fix the issue by casting the column to a string before replacing the values in the column.

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