Question
Asked By – Zhubarb
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?
Now we will see solution for issue: Pandas: change data type of Series to String
Answer
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)
This question is answered By – rocksNwaves
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