I use Pandas 'ver 0.12.0' with Python 2.7 and have a dataframe as below:

df = pd.DataFrame({'id' : [123,512,'zhub1', 12354.3, 129, 753, 295, 610], 'colour': ['black', 'white','white','white', 'black', 'black', 'white', 'white'], 'shape': ['round', 'triangular', 'triangular','triangular','square', 'triangular','round','triangular'] }, columns= ['id','colour', 'shape'])

The id Series consists of some integers and strings. Its dtype by default is object. I want to convert all contents of id to strings. I tried astype(str), which produces the output below.

df['id'].astype(str)
0 1
1 5
2 z
3 1
4 1
5 7
6 2
7 6

1) How can I convert all elements of id to String?

2) I will eventually use id for indexing for dataframes. Would having String indices in a dataframe slow things down, compared to having an integer index?

7

10 Answers

A new answer to reflect the most current practices: as of now (v1.2.4), neither astype('str') nor astype(str) work.

As per the documentation, a Series can be converted to the string datatype in the following ways:

df['id'] = df['id'].astype("string")
df['id'] = pandas.Series(df['id'], dtype="string")
df['id'] = pandas.Series(df['id'], dtype=pandas.StringDtype)

3

You can convert all elements of id to str using apply

df.id.apply(str)
0 123
1 512
2 zhub1
3 12354.3
4 129
5 753
6 295
7 610

Edit by OP:

I think the issue was related to the Python version (2.7.), this worked:

df['id'].astype(basestring)
0 123
1 512
2 zhub1
3 12354.3
4 129
5 753
6 295
7 610
Name: id, dtype: object

9

You must assign it, like this:-

df['id']= df['id'].astype(str)

0

Personally none of the above worked for me. What did:

new_str = [str(x) for x in old_obj][0]

0

You can use:

df.loc[:,'id'] = df.loc[:, 'id'].astype(str)

This is why they recommend this solution: Pandas doc

TD;LR

To reflect some of the answers:

df['id'] = df['id'].astype("string")

This will break on the given example because it will try to convert to StringArray which can not handle any number in the 'string'.

df['id']= df['id'].astype(str)

For me this solution throw some warning:

> SettingWithCopyWarning:
> A value is trying to be set on a copy of a
> slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead

There are two possibilities:

• Use .astype("str").astype("string"). As seen here
• Use .astype(pd.StringDtype()). From the official documentation

For me it worked:

 df['id'].convert_dtypes()

see the documentation here:

Your problem can easily be solved by converting it to the object first. After it is converted to object, just use "astype" to convert it to str.

obj = lambda x:x[1:]
df['id']=df['id'].apply(obj).astype('str')

0

use pandas string methods ie df['id'].str.cat()

for me .to_string() worked

df['id']=df['id'].to_string()

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