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this seems to happend when there is an object type passed as well
In [55]: df = pd.DataFrame({'a':[1,2,4,7],
'b':[1.2, 2.3, 5.1, 6.3],
'c':list('abcd'),
'd':[pd.datetime(2000,1,1) for i in range(4)]})
In [56]: df
Out[56]:
a b c d
0 1 1.2 a 2000-01-01 00:00:00
1 2 2.3 b 2000-01-01 00:00:00
2 4 5.1 c 2000-01-01 00:00:00
3 7 6.3 d 2000-01-01 00:00:00
In [57]: df.dtypes
Out[57]:
a int64
b float64
c object
d object
# this is ok
In [64]: df = pd.DataFrame({'a':[1,2,4,7], 'b':[1.2, 2.3, 5.1, 6.3], 'd':[pd.datetime(2000,1,1) for i in range(4)]})
In [65]: df.dtypes
Out[65]:
a int64
b float64
d datetime64[ns]
The text was updated successfully, but these errors were encountered:
0 and 1 len ndarrays
datetimes that are single objects
mixed datetimes and objects (GH pandas-dev#2751)
astype now converts correctly with a datetime64 type to object, NaT are converted to np.nan
_get_numeric_data with empty mixed-type returning empty, but index was missing
DOC: release notes updated, added missing_data section to docs, whatsnew 0.10.2
jreback
added a commit
to jreback/pandas
that referenced
this issue
Feb 13, 2013
…eric
when a list is specified; use the Series codepath
for initial list conversion (change from using DataFrame)
TST: added test for overflow in df creation
this seems to happend when there is an object type passed as well
The text was updated successfully, but these errors were encountered: