“AttributeError: 'DataFrame' 对象没有属性 'dtype'” 使用 Pandas to_datetime

Question

I have been using Python 2.7.13 on a windows machine to write my code. But I am now trying to run my code on a unix cluster using Python 2.7.12-goolf-2015a .
When I run my code on the cluster with 2.7.12, I encounter an error in the pandas function to_datetime which does not occur using 2.7.13.

The error occurs when I try to convert a date entries in a dataframe to datetime.

Here is an example ot the error I get with the to_datetime command

df = pd.DataFrame({'year': [2015, 2016],
                       'month': [2, 3],
                       'day': [4, 5]})
pd.to_datetime(df)

Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/easybuild/software/Python/2.7.12-goolf-
2015a/lib/python2.7/site-packages/pandas-0.16.1-py2.7-linux-
x86_64.egg/pandas/tseries/tools.py", line 343, in to_datetime
return _convert_listlike(arg, box, format)
File "/usr/local/easybuild/software/Python/2.7.12-goolf-
2015a/lib/python2.7/site-packages/pandas-0.16.1-py2.7-linux-
x86_64.egg/pandas/tseries/tools.py", line 266, in _convert_listlike
if com.is_datetime64_ns_dtype(arg):
File "/usr/local/easybuild/software/Python/2.7.12-goolf-
2015a/lib/python2.7/site-packages/pandas-0.16.1-py2.7-linux-
x86_64.egg/pandas/core/common.py", line 2513, in is_datetime64_ns_dtype
tipo = _get_dtype(arr_or_dtype)
File "/usr/local/easybuild/software/Python/2.7.12-goolf-
2015a/lib/python2.7/site-packages/pandas-0.16.1-py2.7-linux-
x86_64.egg/pandas/core/common.py", line 2458, in _get_dtype
return arr_or_dtype.dtype
File "/usr/local/easybuild/software/Python/2.7.12-goolf-
2015a/lib/python2.7/site-packages/pandas-0.16.1-py2.7-linux-
x86_64.egg/pandas/core/generic.py", line 2083, in __getattr__
(type(self).__name__, name))
AttributeError: 'DataFrame' object has no attribute 'dtype'

The to_datetime works when I load Python/3.5.2-intel-2016.u3, but that causes other problems. I am inexperienced with unix operating systems and as I don't have admin rights to software on the cluster, I am pretty tied to using 2.7.12

If anyone has encountered this issue and has advice on how to resolve it, that would be greatly appreciated!

Thanks, Emma

Answer 1

Try joining the columns and then applying pd.to_datetime .

pd.to_datetime(df.astype(str).apply('-'.join, 1))

0   2015-04-02
1   2016-05-03
dtype: datetime64[ns]

Answer 2

DataFrame.dtypes is an attribute to list data types, for series it's a dtype.

reference: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dtypes.html