Can only use str accessor with string values

1

Exception Class:

AttributeError

Raise code

values = getattr(data, "values", data) # Series / Index values = getattr(values, "categories", values) # categorical / normal inferred_dtype = lib.infer_dtype(values, skipna=True) if inferred_dtype not in allowed_types: raise AttributeError("Can only use .str accessor with string values!") return inferred_dtype def __getitem__(self, key): result = self._data.array._str_getitem(key) return self._wrap_result(result) def __iter__(self):

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Ways to fix

2

This error is raised when the str attribute is called on a pandas column with a non string data type. The str accessor works only on columns whose data is a string type.

Here is how to reproduce the exception.

• Setup your virtual environment

Install pipenv

$ pip install --user pipenv $ mkdir testEnv $ cd testEnv $ pipenv install pandas $ pipenv shell

Then run the following code inside the virtual environment.

import pandas as pd d = {'name': ['apple', 'orange'], 'price': [1.3, 1.4]} df = pd.DataFrame(data=d) print(df) # We want to remove the decimal point (.). new_series = df['price'].str.replace('.','') new_df = pd.DataFrame(new_series,columns=["name","price"]) new_df["name"] = df["name"] print("\n\n",new_df)

The error message

--------------------------------------------------------------------------- AttributeError Traceback (most recent call last) <ipython-input-24-f53fc8122c19> in <module>() 4 print(df) 5 # We want to remove the decimal point (.). ----> 6 new_series = df['price'].str.replace('.','') 7 new_df = pd.DataFrame(new_series,columns=["name","price"]) 8 print("\n\n",new_df) . . . /usr/local/lib/python3.7/dist-packages/pandas/core/strings.py in _validate(data) 2155 2156 if inferred_dtype not in allowed_types: -> 2157 raise AttributeError("Can only use .str accessor with string values!") 2158 return inferred_dtype 2159 AttributeError: Can only use .str accessor with string values!

Fixed version of the code:

To avoid raising this exception or to fix this scenario use the following code instead.

Notice the line new_series =df['price'].apply(str).str.replace('.','')

That is the solution.

import pandas as pd d = {'name': ['apple', 'orange'], 'price': [1.3, 1.4]} df = pd.DataFrame(data=d) print(df) # We want to remove the decimal point (.). new_series =df['price'].apply(str).str.replace('.','') new_df = pd.DataFrame(new_series,columns=["name","price"]) new_df["name"] = df["name"] print("\n\n",new_df) name price 0 apple 1.3 1 orange 1.4 name price 0 apple 13 1 orange 14

Jan 14, 2022

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

Questions : Python AttributeError: Can only use .str accessor with string values

2022-09-26T22:41:41+00:00 2022-09-26T22:41:41+00:00

938

flights['Duration']=flights['Duration'].str.replace('h','*60').str.replace(' ','+').str.replace('m','*1').apply(eval)

However I am getting this error message:

AttributeError Traceback (most recent call last) <ipython-input-24-45eafc3e9d23> in <module>() ----> 1 travel['Duration']=travel['Duration'].str.replace('h','*60').str.replace(' ','+').str.replace('m','*1').apply(eval) 2 3 frames /usr/local/lib/python3.6/dist-packages/pandas/core/strings.py in _validate(data) 1965 1966 if inferred_dtype not in allowed_types: -> 1967 raise AttributeError("Can only use .str accessor with string " "values!") 1968 return inferred_dtype 1969 AttributeError: Can only use .str accessor with string values!

Total Answers 3

25

Answers 1 : of Python AttributeError: Can only use .str accessor with string values

Looks like your flights[ 'Duration'] anycodings_pandas column have not string value (probably anycodings_pandas its int64 or float64).

import pandas as pd df = pd.DataFrame(data=[(1, '12h 50m'), (2, '1h 12m')], columns=['id', 'Duration']) df['Duration']=df['Duration'].str.replace('h','*60').str.replace(' ','+').str.replace('m','*1').apply(eval)

Result:

id Duration 0 1 770 1 2 72

This is works well because when we anycodings_pandas create a dataframe - second column anycodings_pandas values was string type. If we have anycodings_pandas non-consistency in base data so we anycodings_pandas should be careful with results, It can anycodings_pandas be misleading. Example:

df = pd.DataFrame(data=[(1, 123), (2, 0.123), (3, '12h 30m')], columns=['id', 'Duration']) df['Duration']=df['Duration'].astype(str).str.replace('h','*60').str.replace(' ','+').str.replace('m','*1').apply(eval)

Result:

id Duration 0 1 123.000 1 2 0.123 2 3 750.000

In this example we used .astype(str), anycodings_pandas but as we see If data have various anycodings_pandas datatypes - result may be really wrong. anycodings_pandas So check your datasource for dataframe anycodings_pandas and then try transform data again :)

0

2022-09-26T22:41:41+00:00 2022-09-26T22:41:41+00:00Answer Link

mRahman

5

Answers 2 : of Python AttributeError: Can only use .str accessor with string values

What you probably want to do is more anycodings_pandas like:

flights['Duration'] = pd.to_timedelta(flights['Duration']).seconds//60

which will directly convert the time anycodings_pandas string to minutes

The method you're trying to use, with anycodings_pandas apply(eval) seems . . . very unsafe.

0

2022-09-26T22:41:41+00:00 2022-09-26T22:41:41+00:00Answer Link

joy

3

Answers 3 : of Python AttributeError: Can only use .str accessor with string values

You should first cast string to the anycodings_pandas column, using astype(str).

0

2022-09-26T22:41:41+00:00 2022-09-26T22:41:41+00:00Answer Link

miraj

Can only use string accessor with string values?

Is Dtype object a string?